Software review: Measuring the overall effectiveness of marketing (Part 2)

Abstract This is the second part of a paper that explores how the uses of measurement systems have been evolving in marketing.

The first part looked at the impact of implementing corporate strategies on marketing and the development of marketing customer communication   strategies.

The second part explores the types of metrics that are being used to monitor the effectiveness of these customer communication strategies. It also briefly looks at the issues associated with implementing these measurement systems and types of technology that are being used to surface the   measures.


The author has spent the last two years travelling around the world, working in the USA, Europe and Asia Pacific on analytical customer relationship management (CRM) projects. One of the things that has struck him the most   is the general lack of a coherent approach to the integration of marketing strategy with corporate goals and the measurement of marketing communication performance.

This paper attempts to illustrate an approach that represents a combination of ‘best practices’ that he has seen in companies around the world.

The paper covers the following areas:

  • corporate strategy
  • marketing customer communications strategy
  • measuring marketing communication performance
  • metrics used to monitor performance
  • key performance indicators
  • customer balance scorecard

The second part of the paper looks at the:

  • types of metrics that are being used to monitor the impact of marketing customer communication strategies
  • issues associated with implementing these measurement systems and types of technology that are being used to underpin the surfacing of these measures.


The following section of the paper illustrates the types of metrics that could be used to measure the various aspects of marketing customer communication performance. It is not meant to provide   a definitive list, but to point the reader towards the key dimensions to measure.

The metrics are broken down into the following sections:

  • overall performance
  • customer performance
  • product performance
  • channel performance
  • communications performance
  • marketing team

Note: The measures are described by:

Objective function (What the organisation is trying to achieve) 

Metric (How performance is measured)

Overall performance

In most marketing organisations the primary measure of overall marketing customer communication effectiveness is return on marketing investment. The following types of metrics are typically used:

Increase return on marketing spend

Rate of return on marketing spend in period (%)

Total return on marketing spend in period (£)

The periods measured are typically month, year to date and, occasionally, rolling year.

In this case the metric only looks at marketing spend on the assumption that marketing is unable to influence spend in other areas of the business. In the past many organisations only measured the outward costs of the communication, but it is more common to see both the outward bound and response management cost being taken into account.

Where a multichannel strategy has been adopted there has been a move to take into account the indirect costs of marketing. That is, those costs that are not directly controlled by marketing but are influenced by marketing activity, eg response management through different channels.

The resulting metrics have led some organisations to steer customers to respond down preferred channels and/or refine the response management process, eg reducing hand offs through a sale cycle in a retail branch network.

The following types of metrics are becoming more common:

Increase return on corporate spend

Rate of return on corporate spend in period (%)

Total return on corporate spend in period (£)

The periods measured are typically month, year to date and, occasionally, rolling year.

Budgets have been common in most marketing departments for a long time, but they have not been tightly controlled in many cases. This is changing as   finance starts to tighten its grip on this area of spend.

The following types of metrics are common:

Improve budget process performance

Total marketing spend in period (£) Total spend by communication channel in period (£)

Total spend by business initiative in period (£)

Total spend by business unit/product area in period (£)

Total spend by segment in period (£) Total spend per customer in period (£) (average, max, min, mean)

The periods measured are typically week, month and year to date. Budgets are normally set and monitored for spend. In some cases a bid process drives allocation of budget on a campaign-by-campaign basis.


Understanding the dynamic nature of the customer base is essential in any organisation. The following metrics are used:

Increase number of customers

Total number of customers in base at start of period

Total number of customers in base at the end of the period

Net change in customer numbers in period

Rate of net change in customer number in period (%)

Number of new customers gained in period

Number of customers retained in period

Number of customers recovered in period

Number of customers lost in period Number of customers at risk during period

The periods measured are typically week, month and year to date. These numbers would also be expressed as a percentage of the base at the start of the   period.

Where customers are managed by business   units,   the   customer metrics above would be available by business unit. It is still surprising how many organisations are still unable to provide the metrics described above. Where a strategic   segmentation   system  is   in place   the   customer   metrics   above would be required by segment. Targets are sometimes set for acquisition, migration   and   retention   of   customers for segment managers. If this is the   case then there   would   be   measures against   these targets.

Migrate customer to optimal segment

Number of net new customers in segment in period

Number of customer acquisitions to segment in period

Number of net lost customers from segment in period

Number of lost customers in period from segment

Number of lost customers in period to other segments

Number of customers migrating between segments

The periods measured are typically month and year to date.

A key measure for most organisations is the value of the customer; a wide range of methods are used to determine value. These include:

  • total sales
  • total gross profit (contribution)
  • total net profit
  • net present value.

The choice of method would depend on the business.

In addition organisations may want to measure:

  • historical value
  • planned value (if customer keeps current product)
  • potential value (if customer grows product/service portfolio).

The following types of metrics are typically used:

Maximise value of customers 

Total value customers in period (£) Value of customer in period (£)

The periods measured are typically month and annual. These customer data may be aggregated by a number of dimensions including:

  • segment
  • business unit
  • source channel

A key driver of customer value is the number and value of product relationships. This leads to a set of metrics around this subject matter. The following types of metrics are used:

Increase value customer product holdings

Number of product involvements Number of products sold to existing customers

Value of products sold to existing customers (£)

Number of products sold to new customers

Value of products sold to new customers (£)

Number of products sold to recovered customers

Value of products sold to recovered customers (£)

Number of products at risk Value of products at risk (£) Period product held (max, min, average and mean)

The periods measured are typically week, month and year to date.

These metrics are normally available for the customer base, segments, customers and households if appropriate.

The issue with product holding is   often the definition of product, but this   is a business issue that has to be resolved if an effective measurement system can be put in place.

The value of a customer in many cases is driven by the period the product is held, so most organisations have some measure of product and customer tenure.

The following types of metrics are used:

Maximise length of customer relationship

Period as customer (max, min, average and mean)

The periods measured are typically week, month and year to date. These tenure data may be aggregated by a number of dimensions including:

  • segment
  • business unit
  • source channel.

In many organisations the cost of customer acquisition is a major driver of customer value so a variety of metrics is used to monitor these costs.

Reduce cost of acquisition

Number of customers by acquisition channel in period

Total cost of acquisition through channel in period (£)

Cost of customer acquisition in period (ave, max, min, mean)

Cost of sale by stage in sale cycle (£): enquiry; quotation; application; sale

The periods measured are typically week, month and year to date. These data may be aggregated by a number of dimensions including:

  • business initiative
  • segment
  • business unit
  • source channel.

Monitoring the effectiveness of the sales channel in converting an enquiry into a sale is usually measured, as part of the sales process but these data are often valuable if the marketing department is to understand how to optimise the use of a channel.

Improve conversion rates

Conversion rates for stages in the sale cycle: enquiry; quotation; application; sale

The periods measured are typically week, month and year to date. These data may be aggregated by a number of dimensions including:

  • product
  • business initiative
  • segment
  • business unit
  • source channel.

Product performance

In most organisations the metrics for measuring product performance are well catered for. It is the customer metrics, which are often difficult to get and integrate.

Increase value of product holdings

Total number of product involvements in base at start of period

Value of products in base at start of period (£)

Number of product involvements in base at end of period

Value of products in base at end of period (£)

Net number of products gained in period

Net number of losses in period Number of new product involvements in period

Value of new product involvements in period (£)

Number of lost product involvements in period

Value of lost products in period Number of products retained in period Value of products retained in period (£) Number of products recovered in period

Value of products recovered in period (£)

Number of products at risk at start and end of period

Value of products at risk at start and end of period (£)

The periods measured are typically week, month and year to date. These data may be aggregated by a number of dimensions including:

  • product group
  • business unit.

Improve product acquisition by channel 

Number of products sold by channel Value of products sold by channel (£)

The periods measured are typically week, month and year to date.

In many cases it is difficult to measure product upgrades but it is important that measurement systems are put in place as they can increase the value of a relationship and reduce customer churn. The metrics are similar to those of product.

Increase product upgrades

Number of upgrades sales by product combination

Value of upgrades sales by product combination

The periods measured are typically week, month and year to date. These data may be aggregated by a number of dimensions including:


  • product group
  • business unit.


The whole issue of channel management is becoming more important as organisations try to manage the complex mix of communication channels available today.

Ensuring optimal resource allocation and utilisation is becoming essential if business and CRM objectives are to be met. The following metrics are typically used:

Reduce cost per communication in channel

Total number of communications by channel

Total cost of channel (£)

Cost of communications by channel (ave, max, min, mean)

Number of marketing communications by channel

Total cost of marketing communications through channel (£) Costs of marketing communications by channel (ave, max, min, mean) Marketing communication contact rate (success rate) (%)

Conversion rates by channel for stages in sale cycle (%)

The periods measured are typically week, month and year to date. These data may be aggregated by a number of dimensions including:

  • channel
  • business unit
  • product.

Other metrics typically used include:

Maximise sales per channel

Number of sales by channel in period Value of sale by channel in period (£) Cost of sale by channel in period (£) Number of new customers by channel in period

Value of new customers by channel in period (£)

The periods measured are typically week, month and year to date.

Reduce cost per sale

Cost per sale by channel in period

The periods measured are typically week, month and year to date.

Improve channel ROI 

Rate of return on channel spend in period

Total return on channel spend in period

The periods measured are typically month and year to date.

In addition to standard metrics that allow cross-channel performance comparison, a number of metrics may need to be developed for specific channels, eg

  • telephone: length of call, missed call rate
  • e-mail: number of hard and soft bounce backs
  • web: period on web page.

Communications performance

At a more operational level, organisations will have to put in a series of metrics to measure the performance of marketing communications. The following metrics are typical:

Reduce cost per communication

Number of marketing communications in period

Cost per communication in period   (£)

The periods measured are typically day, week, month and year to date. These data may be aggregated by a number of dimensions including:

  • business unit
  • campaign manager
  • campaign
  • channel
  • product.

Perhaps the most commonly used measure for marketing performance response rates needs to be seen within the context of a range of metrics to improve effectiveness.

Increase response rates

Number of responses to communication by campaign in period Total value of responses to communication by campaign in period Response value by campaign in period (ave, max, min, mean)

Reduce cost per sale

Cost per response to communication by campaign in period (£) Conversion costs per stage in the sale cycle for campaign (£)

Improve conversion ratios

Conversion rate per stage in the sale cycle for campaign (%)

The periods measured above are typically day, week, month and year to date. These data may be aggregated by a number of dimensions including:

  • channel
  • business unit
  • product
  • business initiative
  • campaign
  • communication.

In some markets campaigns are planned, partially executed then cancelled. This often results in wastage, which needs to be measured.

Reduce cost of wastage in communications

Cost of campaigns aborted in the period

The periods measured are typically week, month and year to date.

Improve campaign ROI

Rate of return on campaign spend in period at campaign and communication levels

Total return on campaign spend in period at campaign and communication levels

The periods measured are typically week, month and year to date.

In this example a campaign may consist of one or more communications. The rate of return may be aggregated in a number of dimensions. These could include:

  • business initiative
  • product category
  • segment
  • business unit
  • campaign manager.

The important thing about this approach is that common sets of metrics are used     to monitor campaign performance. This allows cross-campaign performance and therefore resource allocation to be more effectively managed.

Other metrics may be used to measure the impact of direct communications on brand and customer perceptions. These include:

Improve brand awareness and consideration

Brand awareness levels in period Brand consideration index in period

Improve customer perception of marketing communications

Marketing communication satisfaction index


Organisations have started to monitor the effective utilisation of staff resource in marketing. This has not been popular, as it requires the keeping of time sheets and the allocation of time against specific campaigns. But those companies that have introduced these types of measure have found them very valuable, in many cases justifying an increase in staff resource. The following metrics are typical:

Reduce time to market

Period between key milestones in a campaign life cycle (days) (ave, max, min and mean)

These data may be aggregated by a number of dimensions including:

  • business initiative
  • type of campaign
  • campaign manager.

These type of data have helped in refining the campaign management and associated processes.

Reduce staff resource required to execute a campaign

Man days of resource required to execute campaign, broken down by campaign stage

These data may be aggregated by a number of dimensions including:

  • business initiative
  • type of campaign
  • business unit.

The main driver for improvement in this area has been improvement in marketing processes and the introduction of campaign management technologies which have allowed more of the process to be automated.

Increase the number of campaigns per full time equivalent (FTE)

Number of communications per campaign (ave, max, min, mean) Number of campaigns per marketing FTE

Number of communications per FTE Marketing spend per FTE (£)

The introduction of workflow and other planning technologies in marketing is facilitating these types of measurement.

There is a pool of evidence that shows that satisfied employees are more productive. The costs of losing skilled marketing staff have pushed some organisations into establishing more effective metrics for monitoring staff satisfaction. These include:

Improve marketing staff satisfaction

Staff satisfaction index

Number of days lost due to sickness Number of employees in department at start and end of period

Number of FTEs in department at start and end of period

Number of employees resigned during period by reason type

Number of employees recruited during period

Cost of recruiting new employees (£) Value of investment in employees

The periods measured above are typically month and year to date.


The previous section provides a list of the type of metrics that are being used   to manage a marketing operation. There are too many for a marketing manager to use effectively. There will be a small number (five to ten) that will provide key indicators of the team’s performance (KPIs). These should be surfaced to management on a regular basis in the form of a flight deck, with exceptions visually highlighted. It should then be possible for management to drill down into the supporting metrics when appropriate to investigate underperformance. This approach avoids data overload of management team.


There are a number of vendors that supply reporting or business intelligence technologies. The following are just a few:

  • Business Objects
  • Cognos
  • Hyperion
  • SAS.

The key issue for marketing is to understand what is being measured and how this integrates with the marketing strategy, before going out and buying a stack of reporting tools. It is important to look for both business and technical support from a supplier; many have developed industry-specific templates which will fast track the delivery process. When buying technology it is not only looks that count. It is substance. Things   to look for are:

  • financial viability
  • future vision
  • industry domain knowledge
  • richness of functionality
  • data integration capability
  • forecasting and predictive capability
  • delivery capability
  • references.


There is need for marketing organisations to align what they are doing with corporate strategy. Ensuring that there is a documented marketing strategy and marketing plan is just the first   step.

Putting in place the necessary measurement systems is the next. Few organisations that the author has worked in would claim to have a comprehensive set of metrics to monitor the performance of marketing. Even fewer have formulated these as a simple set of key performance indicators that can be used to manage the business on a day-to-day basis. If the right measures are not in place the business cannot be managed effectively. What cannot be measured, cannot be managed.

Software review: The components of a marketing automation solution in a multi-channel real-time environment

Abstract This paper describes the key components of a marketing automation   solution. It aims to provide a framework for discussion on the components needed to support   the marketing function in a multi-channel, real-time environment.


The last few years have seen the campaign management vendors repositioning their applications as marketing automation solutions. One of the reasons for doing this is to differentiate their solutions from the traditional campaign management applications that have little or no automation capability. At the same time it has become clear that marketing automation needs to go beyond campaign management and needs to look at supporting a wider range of processes within the marketing function.


The introduction of high end campaign management applications with scheduling functionality provided marketing teams with the ability to significantly increase the volume of communications (tenfold is not uncommon) while maintaining, and in some cases reducing, the size of the marketing team. Adding to this armoury the tighter integration of the novel real-time communication methods such as e-mail and short text messaging (many with significantly reduced unit cost per communication), has resulted in a situation where the same marketing team could potentially deliver 100 times more communications. The issue now is that many of the other marketing processes cannot cope with the increasing power of the core marketing communication engine. Wider automation of the marketing function is, therefore, inevitable.

This paper explores the key components and potential scope of a marketing automation solution.


The central component of any marketing automation solution is the client repository. This holds information on prospects, customers and ex-customers, allowing the relationship with the individual to be managed through each stage in the customer life cycle. The type of data held on the client will depend on the nature of the business but in general will include the following data categories:

  • client profile, eg date of birth
  • client grouping, eg household key
  • client contact details, eg e-mail address
  • communication preference data, eg do not mail indicator
  • product/services involvement
  • product/services usage
  • inward and outward bound contact history
  • response data
  • behavioural model scores
  • reference data

Where the repository is to support business-to-business activities, the following additional data categories would normally be present:

  • organisation, eg registered company name
  • site, eg branch ID
  • client site relationship data

The client repository should hold current data for each of the data categories identified above, in addition a history will also be maintained for some data items, eg current account status code over time.

With the growth in real-time marketing and the demands of the novel communication methods such as those provided by the Internet and wireless application protocol (WAP) technologies there is a need to move to real-time maintenance of data in the client repository.

The technology used to store these   data will depend on the requirements and IT strategy of the business. The use of ‘open’ data warehouses and data marts is common but more distributed solutions are being adopted particularly by global operations. The need for real-time maintenance of the client repositories is resulting in a number of new system models being developed.

A number of technologies have evolved to meet the requirements to build and maintain client repositories these include:

  • ETL tools: for the extraction, transformation and loading of data
  • RDBMS: relational database management systems for the storage of data
  • name and address processing applications for the standardisation and validation of this type of data
  • matching applications for the on-line and batch matching of name and address data
  • client key management systems which are concerned with issuing and maintaining unique client IDs.


One of the primary functions of any marketing automation solution is to determine which client should receive what communication when and by what communication method. This communication decision process is at the heart of direct marketing. The processes described below will be supported.

Maintaining communication reference data

This process is concerned with maintaining reference data for communications. These data are used to control and monitor the performance of marketing communication activities. The reference data should include target key performance indicators (KPIs).

Determining client communication eligibility

This process is concerned with using the available data in the client repository to determine whether a client is eligible to receive a specific communication. The inputs into this process include behavioural model scores.

Depending on the nature of the data used to select a client for inclusion in a target audience the solution will be able to support a range of marketing activities including:

  • customer life stage, eg marriage
  • product life cycle, eg policy renewal
  • trigger, eg change in purchase behaviour.

Determining client communication priority

This process is concerned with applying one or more business rules to determine which of the eligible communications a client should receive. The inputs into   this process include behavioural model scores, product and/or client profitability measures and KPIs.

Determining client communication delivery mechanism

This process is concerned with determining the most appropriate communication delivery vehicle for the client specific communication. The inputs into this process include behavioural model scores and channel capacity constraints.

Determining client communication cell involvement

This process is concerned with aggregating individual clients into communication cells or breaking groups of clients (target audiences) into communication cells that are used to monitor the performance of specific communication and channel combinations.

Traditionally, this communication decision making process has been performed for groups of clients as part of a batch process. But, with the move to real-time marketing, there is a need to ‘decision’ an individual client at the point of contact real time. This presents   a number of significant technical problems that are further exacerbated by the general move to multichannel business models.

A number of technologies have evolved to meet the requirements for communication decision making. These include:

  • behavioural modelling
  • data mining
  • campaign management.


Once it has been decided what communication a client is to receive the next stage in the process is to execute   the communication. The subsequent processes to be supported will depend on whether the marketing communication is proactive, where the communication is sent directly to the recipient, or passive, where the communication is received by the recipient when they next make contact with the organisation. The latter case requires the details of the communication and/or any associated business rules to be made available at all possible points of contact. The following processes will be supported.

Maintaining communication delivery reference data

This process is concerned with maintaining:

  • delivery mechanism reference data, eg available capacity
  • communication or campaign specific reference data required to deliver the communication
  • the delivery system or process, eg data required to personalise a letter.

These data are used to control the communication delivery system or process.

Transferring required data to communication delivery system

This process uses the communication delivery reference data and the campaign reference data to determine what data should be transferred to the communication delivery system (e-mail production engine) or process (direct sales force) and when this should happen.

Executing communication

This process is concerned with executing the communication where the process is proactive. In the case of a passive communication activity, the system or process waits until the client contacts the organisation and the communication execution is triggered. A simple example of a passive communication is a personalised message on an automatic telling machine (ATM) screen.

Maintaining contact history

In order that the effectiveness of marketing communications can be measured it is essential that an accurate record of all communications to and from the client is held in the client repository. This process is concerned with maintaining a record of all inward and outward bound communications with a client. The outward bound communications could be proactive or passive.

Automating and optimising communication execution

This process is concerned with automating the tasks that collectively form a campaign. This involves both the communication decision making and communication execution components.

A natural evolution in this automation is to move to communication optimisation. At the moment the automation is mainly concerned with allowing tasks to be executed in a sequence without human involvement.

The next step is to establish performance criteria and allow the system to optimise the communication decision making and execution processes. This subject raises a number of interesting business issues around ‘what are we trying to optimise?’ Is it return on investment, customer profitability or customer retention levels?

A number of technologies have evolved to meet the requirements for communication execution, these include:

  • data replication
  • data messaging
  • artificial intelligence
  • campaign management.


The last few years have seen an   explosion in the available communication methods to the average marketing manager. With this has come a requirement to manage the resource utilisation in these communication channels better and to improve the integration between them. A comprehensive marketing automation solution should support these utilisation and integration requirements.

The primary focus of the integration is   to ensure consistent treatment of a client regardless of the organisation contact point.

Consistent treatment does not mean that the same data are available at all points of contact. Providing credit reference data to a teller operator in a bank may be valid but the bank may not want to make these data available to a client as part of a personalised view on a website. The key is to disseminate the corporate understanding of the client resulting from the analysis of the data in the client repository to the rest of the organisation in a form relevant to the recipient.

The technologies that have supported this component of the marketing automation solution have tended to be independent of the communication decision process, but there has been a move to tighter integration of these systems to make more effective use of the channel resource. Perhaps the best example of this is the move from daily batch transfer of data into an outward bound call centre to a situation where the results of each call are fed back to the communication decision engine and the resulting target audience being continuously refined real time.

A number of technologies have evolved to meet the requirements to manage communication channels these include:

  • data replication
  • data messaging


Monitoring the effectiveness of the marketing communication activities is an essential component of a marketing automation solution. If a process cannot be measured then it cannot be managed.

This component is concerned with the creation, maintenance, scheduling and execution of both paper and screen-based reports used to monitor various aspects of the marketing process.

The reporting element should use all the data available in the client repository including target KPIs held as part of the campaign or communication reference data.

A number of technologies have evolved to meet the requirements to monitor communication performance, these include:

  • decisional support system (DSS) applications
  • on-line analytical processing (OLAP) applications
  • relational on-line analytical processing (ROLAP) applications
  • integrated reporting within campaign management applications

The move to real-time marketing means that other methods of presenting performance data are starting to appear, these use multimedia and novel data visualisation techniques to present information to campaign managers in a real-time interactive environment.


The adoption of the core marketing automation technologies often results in a significant increase in the volume of communications sent to clients. Where this communication involves physical collateral, eg letters and brochures the  management of the creation, storage and distribution of these materials can become   a problem. A range of technologies can be used to support these processes.

Archiving copies of communications has proved to be problematic for most organisations. The last few years have seen a growth in marketing encyclopaedia systems aimed at solving this problem.

These systems allow marketing and customer contact personnel access to electronic images and/or copies of communications received by a client. These systems work well where the original collateral was paper-based but the novel communication techniques such as multimedia e-mail are stretching the current technologies.

Another area that is starting to get some attention, particularly where the communication delivery system is web-based, is physical content. Managing voice and multimedia components is proving problematic particularly where they are being used across multiple channels. The technology in this area is still embryonic.


The disciplines of process analysis and design have started to be applied to marketing. This work has shown that many of the processes in marketing, particularly those associated with the planning, execution and evaluation of marketing communication activities can be structured, documented and system supported. Two key technologies have started to be deployed in both small and large marketing teams, these are:

  • task management
  • workflow

In some cases this type of functionality is being added to campaign management systems.


The role of behavioural modelling in the communication targeting process is well established. This process is concerned with the development and deployment of model scores onto the client repository, either as part of the refresh process or as a dynamic part of the communication decisioning process.

As we move to a greater degree of automation and real-time marketing it is essential that models can be developed and deployed with relative ease.

A number of technologies have evolved to meet the requirements to build and deploy models in real time, these include:

  • data mining
  • DSS
  • ETL.


The developments in communication delivery technologies have resulted in an explosion in an organisation’s ability to communicate with its clients. Coping with these and real-time marketing will force organisations to look hard at how the marketing process is managed. The result of this analysis will show that it has implications for people, process and technology. Meeting these demands of real-time marketing will mean that much of the marketing process will need to be system supported and automated.

Marketing automation will, therefore, impact on the whole of the process not just those parts traditionally supported by campaign management applications.

The role of interaction management systems in the management of customer relationships

Abstract This paper explores the evolution of customer interaction management systems and their possible place in the support of customer relationships.


Since early 1999 there has been an explosion in the number of technology vendors touting ‘customer interaction management systems’. In many cases it is campaign management or call centre or web personalisation technology under another name. But there are a few who have taken a novel look at a growing business problem, coping with real time interactions across a wide range of customers points. For most organisations the idea that there should be consistent and/or relevant treatment of clients (customer and prospects) across the organisation’s touchpoints seems logical, but for most marketing managers it is just a dream. Yet again, technology is ahead of most organisations’ ability to deliver the other pillars of success, the people, process and technology changes. In some cases the technology being promoted is ‘slide ware’ with little real substance — buyer beware.

This paper explores some of the approaches being taken by the technology vendors to solve this growing business problem.


In the last five years the introduction of high-end campaign management applications with scheduling functionality provided marketing teams with the ability significantly to increase the volume of communications (tenfold is not uncommon) while maintaining and in some cases reducing the size of the marketing team. Adding to this armoury the tighter integration of the novel real-time communication methods such as e-mail and short text messaging, (many with significantly reduced unit costs per communication) has resulted in a situation where the same marketing team could potentially deliver 100 times more communications. The issue now is that many of the other marketing processes cannot cope with the increasing power of the core marketing communication engine. Wider automation of the marketing function and the evolution of customer interaction management systems is therefore inevitable.

In an earlier paper the requirements for a marketing automation solution were examined,1 this paper identified the key components and the functions to be supported by such a solution. The functions to be supported are:

  • managing client information
  • managing communication decisioning: maintaining communication reference data; determining client communication eligibility; determining client communication priority; determining client communication delivery mechanism;determining client communication cell involvement
  • managing communication execution: maintaining communication delivery reference data; transferring required data to communication delivery system; executing communication; maintaining contact history; automating and optimising communication execution
  • managing communication channels
  • monitoring communication performance
  • managing communication content
  • managing the marketing process: task management; workflow
  • managing model development and deployment.

This paper expands on the requirements to manage communication channels.

The last few years have seen   an explosion in the communication methods available to the average marketing manager. With this has come a requirement to manage the resources utilisation better in these communication channels and to improve the integration between them. A comprehensive marketing automation solution should support these utilisation and integration requirements.

The primary focus of the integration is to ensure a consistent treatment of a client regardless of the organisation touch point.

Consistent treatment does not mean that the same data are available at all points of contact. Providing credit reference data to a teller operator in a bank may be valid but the bank may not want to make these data available to a client as part of a personalised view on a website. The key is to disseminate the corporate understanding of the client resulting from the analysis of the data in the client repository to the rest of the organisation in a form relevant to the recipient.

The technologies that have supported this component of the marketing automation solution have tended to be independent of the communication decision process, but there has been a move to tighter integration of these systems to make more effective use of the channels. A whole class of technology solutions is being developed to meet this business requirement generically called customer interaction systems.

The following section explores the requirements for a customer interaction management system (CIMS).


The customer interaction management system (CIMS) plays a central role in the execution of client dialogue. It receives information from the organisation’s touchpoints, processes these through policies or business rules that determine how to respond, and sends appropriate content back to the touchpoint for delivery to the client. The CIMS should support the following key processes:

  • obtaining data from the touchpoint
  • processing data through a communication decision engine
  • communicating the outcome to the touchpoint system
  • maintaining a record of communication
  • monitoring communication effectiveness.

Meeting these requirements raises a number of technology issues as follows.


Most organisations have a large number of possible customer touchpoints. The CIMS would therefore have to interface all the possible touchpoint systems.

Where this is the case, the CIMS would be able consistently to manage the customer dialogue across the whole enterprise. This is the core objective of this type of system.

Before a customer interaction can be managed the touchpoint system has to collect and pass the necessary data to the CIMS.

The following technical solutions have been proposed.

Modify touchpoint solution to collect and transfer the required data

In this case the touchpoint system is modified so that it generates a message that is consistent with the application program interface (API) built into the CIMS.

This approach provides the implementer with the greatest flexibility, since it means the CIMS can work with any touchpoint system that can generate an appropriate transaction. It also means, however, that a significant amount of work is required by the customer organisation to add each new touchpoint system to the overall solution.

CIMS manages the communication with the touchpoint

In this case the CIMS provides an application that itself manages communications with the touchpoint. This approach moves the development effort to the CIMS vendor but does facilitate integration with any of the common touchpoint technologies.

For example, one could provide HTML snippets that can be embedded in a Web page; these call the customer interaction management system when the page is requested, transfer information such as the customer ID and context, and display as part of the Web page whatever message the CIMS determines is appropriate. These applications are called ‘adapters’ or ‘connectors’.

Middleware technology translates data between the touchpoint system and the CIMS APIs

In this case a middleware application would be used to translate data between the different system APIs, without building a point-to-point connection between each touchpoint and the CIMS. These technologies do exist, although this strategy has not been adapted by any of the main interaction management vendors. This generic approach may not be attractive to the vendors who want to own this key part of the process. It does, however, allow the customer organisation to deliver a flexible architecture that allows each of the components to be changed with ease.

Monitor data in non-touchpoint system

Some CIMSs avoid any touchpoint integration at all by scanning for   significant transactions outside the context of a particular touchpoint process.

For example, a system might scan a stream of bank deposits, regardless of which touchpoint hosted them, and select those over $10,000 for closer examination. This could be done by reading inputs to the deposit system, which might actually be linked to a number of different touchpoint systems.

In many cases some degree of transaction filtering is deployed into the touchpoint integration mechanism, so the CIMS is only called when a decision is truly required. This could be accomplished by building screening rules into either the touchpoint logic that calls the CIMS’s   API, or the CIMS application embedded in the touchpoint.


The type of data passed from the customer touchpoint will vary depending on the nature of the customer interaction. As a minimum the following types of data are implicated:

  • client reference data, eg client ID (unique customer or prospect reference)
  • channel reference data, eg channel ID (unique reference for the touchpoint)
  • interaction transaction

In many cases the touchpoint system will collect significant amounts of data on the interaction including contextual information such as the path the client took to get to the present location, and specific information such as replies to questions.

If integration is achieved using a CIMS API, then the design of the API will determine how many data can be captured. Systems that integrate via connectors built for specific touchpoints are governed by whatever types of data the connector has been designed to process. The maximum data available is usually determined by the touchpoint system’s API, but fewer data may be transferred if the connector accepts only a subset of what the API presents.

A business rules engine is used in the CIMS to determine what the most appropriate response is to the current dialogue request. In its simplest form this could be a lookup of the client ID in a   list of eligible campaigns or communications. This campaign list could be held in the CIMS (most likely) or locally in the touchpoint sytem. The latter results in control issues when campaign involvement is changed in the CIMS.

The touchpoint system must continue to operate even if the CIMS fails to respond. Such a failure could occur for any number of reasons. If the CIMS is functional it should first test other content or campaigns to see if they are available; if not, it should deliver a default content or campaign.


The CIMS accepts information from the touchpoint and generates additional information about its own activities, such as movement of a client through a campaign sequence or which messages a client has been sent. Persistent storage is important in campaigns that walk a client through a sequence of messages or that use changes in a customer’s behaviour or status to trigger interactions.

This has implications for:

  • the types of data stored
  • user control over data
  • storage format
  • accessibility
  • data transfer to other

all in real time. Accessing these data sources represents a significant technical problem. This is further compounded by the potential need to execute complex decisioning processes including channel optimisation.


The following is a sample list of vendors claiming to have technology that supports customer interaction management:

Allink Agent
Black Pearl
Data Distilleries
Prime Response
Recognition systems
Yellow Brick

Even though each vendor/product offers a different combination of functions, the systems appear to fall into two clusters. Products in the first group (Yellow   Brick, Verbind, Revenio) offer complex, multi-step marketing campaigns that are delivered through one or more touchpoints, but driven by the CIMS itself. The second group (Epiphany, Black Pearl, Manna, Data Distilleries, Intrinsic) delivers recommendations in response to touchpoint requests. In these, the touchpoint itself is the main driver. Note that all the products in this group provide integrated modelling, while none in the first group do.

The one product that falls into neither group, Allink Agent, is indeed an oddity, designed less for real-time interactions than to identify marketing opportunities and react through outbound messages.

Products in the recommendation group may find themselves competing less with the other CIMSs than with recommendation engines like NetPerceptions and modelling products like MarketSwitch and Quadstone. This assumes the modelling vendors deliver real-time scoring solutions that are easy to deploy.

Similarly, products in the multi-step campaign group may eventually find their primary competitors are conventional campaign managers and marketing automation systems, particularly as these re-engineer to integrate with multiple touchpoints in real time. However, the division between one-time and multi-step CIMSs itself may not last, if vendors in each group add the key capabilities provided by the other.

An analysis of the key vendors of customer interaction management technology clearly shows that there is:

  • no best practice approach: no two vendors have the same strength and weaknesses. This variation in approach reflects the newness of this technology category and the lack of an accepted best practice approach in the industry
  • no comprehensive solution: no single vendor has addressed all the key business requirements. This reflects the fact that few vendors have given this area a high priority. It is also technically a complex problem, particularly when it comes to handling real-time decision making. The scope of the current solutions tends to reflect the background of the vendor company or the design team
  • mainly small specialist vendors: most of the products in the market are provided by small (early adopter) organisations, with many being less than two years old. The fragmentation of the market among multiple vendors suggests that any significant market expansion will be accompanied by consolidation, or more likely, acquisition of vendors by larger CRM firms
  • immature market: no vendors appear to have more than a dozen sites up   and running. This would indicate that the market is still immature and in   the early adopter stage.


The desire by organisations to manage client interaction across all touchpoints will drive technology vendors to develop systems to meet this business requirement. There are significant technical issues surrounding access to data from multiple sources in real time and the complex decision process and these problems will slow the evolution of these systems, but they can be solved. The bigger issue is that few organisations have the ability to deliver the other pillars of success, ie the people, process and technology changes.

Software review: How is geography supporting marketing in today’s commercial organisations?

Abstract The wider availability of Geographical Information Systems (GIS) for use in marketing is encouraging growth in the business application of these technologies. This paper explores how geography is now being used to support marketing activities in a range of industry sectors.


A Geographic Information System (GIS) is a tool that allows data that can be referenced spatially, ie data that can be tied to a physical location, to be organised and analysed. Many types of data have a spatial aspect, including demographics, marketing surveys and epidemiological studies.

GIS software generally use two basic types of data:

  • spatial data: containing the coordinates and identifying information describing the map itself
  • attribute data: containing information that can be linked to the spatial data, for example, matching addresses or coordinates in the spatial


Spatial data contain the coordinates and identifying information for various map features. Three types of features can be represented in the map:

  • points
  • lines
  • areas

The various physical aspects of the   map

  • political boundaries, roads, railroads, waterways, and so forth — are organised into layers according to their common features. For example, the collection of points that represent park locations can be organised into a parks layer, the collection of lines that represent streets can be organised into a streets layer,   and the collection of areas that represent census tracts can be organised into a tracts layer. A layer can be either static or thematic. Static layers use the same graphical attributes (colour, line width, and so forth) for all features in a layer. Thematic layers can use different graphical attributes to classify the features in the layer. For example, a thematic area layer representing sales regions could use different colours to show the quarterly sales performance of each region. A thematic line layer representing highways could use different line widths to show the classes of roads.


The second type of data used in a GIS is attribute data. With most GIS software, data sets or data views can be associated with the map through links to the spatial data. For example, the spatial data might represent a county and contain information for city boundaries, census tract boundaries, streets, and so forth. An attribute data set with population information for each census tract can be linked to a map by the corresponding tract value in the spatial data.

There are two main ways in which the attribute data can be used. These include using variables from the attribute data as themes for layers — for example, an attribute data set containing population data could provide a theme for a map of census tracts — and   creating actions that display or manipulate the attribute data when features are selected in the map.

The actions can range from simple ones, such as displaying observations from an attribute data set that relate to features in the map, to complex ones, such as submitting procedures from statistical software to perform statistical or special analyses.


Typical end-user functionality for business users would include the following:

  • pan and zoom the map extent
  • query spatial and attribute data
  • create a buffer around features
  • measure distances on the map
  • add map notes, such as text, graphics or images, to the map
  • make edit notes to map spatial and attribute data
  • locate an address
  • viewers also feature legend, overview maps, saving and retrieving projects, and map printing

One of the key concepts with GIS software is selecting features from the map and then performing actions on the attribute data associated with those features. Actions can be defined to:

  • display observations from the attribute data sets that relate to the selected map features
  • open additional maps that relate to selected map features
  • display graphic images that relate to the selected map features
  • subset interactively the attribute data sets according to the subset of selected map features
  • submit statistical programs for processing subsets of the attribute data that relate to the selected map features.


The following section of the paper explores some of the business applications of GIS in a database marketing context.

Location information

It is becoming quite common for organisations, as part of a marketing campaign, to include details of local branches where goods and services can be purchased. In the past this communication may have consisted of:

  • the address of the branch
  • a standard generic

Now with the integration of campaign management and GIS technologies it is possible to provide the customer or prospect with:

  • the address of the branch
  • a personalised map
  • a personalised route guide

of the nearest location providing products or services. This personalisation being based on the customer’s home or work address.

Neighbourhood marketing

A number of the direct insurance companies now regularly promote insurance to prospects living in the neighbourhood of an existing customer. Making reference to the benefits that the customer (neighbour) has been able to achieve through the product or services provided by the organisation. In some cases the personal details of the customer are included in the communication (with the customer’s permission) to bring the proposition to life. In the past this targeting has been done using postal geography but with the wider availability of detailed street level data this type of marketing is now being targeted using GIS technologies.

Targeting using drive time

As most retailers know, the length of time it takes a customer to drive to a location can significantly impact the performance of marketing communications aimed at stimulating a customer or prospect to visit a specific location. It is now becoming quite common for organisations to use expected drive times as part of the selection process for inclusion in a campaign.

In some cases these drive times are being used as inputs into behavioural models, which in turn are being used to target communication activities as part of the campaign selection process.

The quality of drive time algorithms has improved over the last few years primarily because of the quality of data available. This is allowing drive times to be refined to take into account time of day and time of year. As anybody who commutes to work will confirm, these factors can have a big impact on how long it takes to get to or from a location.

Catchment area analysis

Perhaps the most common application for GIS systems in marketing is retail catchment area analysis. Information on customers and/or prospects is combined with purchase and spatial data to map out the catchment areas for retail locations.

These catchment area definitions are then used to support a range of marketing activities including:

  • customer or prospect profiling
  • forecasting branch revenue or potential
  • instore space allocation
  • defining local merchandise mix
  • store categorisation
  • campaign selections
  • branch network planning or rationalisation
  • sale territory

Geodemographic analysis

The wider availability of census and other attribute data sets has led to the development of a number of advanced geodemographic systems. These systems can be used to classify the people (or households) living or working in a particular area. In many cases these geodemographic codes can easily be attributed to individuals, allowing a range of marketing and analysis activities to be supported.

Their use as inputs into behavioural models has proved very effective where the internal data available on individuals are poor. Even more advanced solutions are likely to be developed in the UK, once the 2001 census data are made available for commercial use.

Supply and demand side forecasting A good industry specific application of GIS is provided in the telecommunications sector by supply and demand forecasting. Here information on network capacity by geography is matched against information on demand by geography. The resulting network capacity gaps are used to drive a range of activities. These include:

  • targeting localised special discounts
  • changes in tariff structures
  • promotional activities for local dealers
  • special promotional events.

Where there is likely to be excess capacity in the medium term, the information is used for:

  • network planning
  • dealer recruitment
  • retail location planning
  • local marketing

External information on businesses is combined with the internal information on customers in capacity rich areas. GIS is then used to locate target business for sales and marketing activities. External profile data on workforce (in terms of type of employment and method of travel to work) is used to model the potential and rank the prospects within the catchment areas. This allows limited sales resource to be well targeted.

Location-based marketing

With advances in digital technology, will be seen the increasingly frequent and sophisticated use of location-based marketing. GIS is a core component of this approach to marketing.

Modern cellular communications technology allows the location of the mobile device user to be identified to within 50 feet. This has led to the development of a number of location-based services. One of these is two-way short message services (SMS). This technology allows communications to be sent to an individual based on their physical location. To date the application of this technology has concentrated on information provision, a small number of organisations have started to use this technology for marketing communications. The two-way nature of the technology means that an individual can respond with ease.

Although there are a number of data protection and privacy issues that will need to be addressed, a number of organisations in Europe are running pilot projects where the information is being used to drive marketing communications. If this technology becomes more widespread the application of location-based data may become the norm in some sectors, eg the automotive sector.

Location-based marketing will be important for companies such as retailers, banks or media that want to attract customers to a physical location, such as     a retail store, branch or cinema. For example, if a supermarket chain knows that one of its loyalty card shoppers is in the vicinity of one of its supermarkets, it can send a message telling the shopper about special offers.


As with most aspects of intelligent marketing solutions, analytics will play an important role in the effective use of GIS systems in marketing. Companies will need to analyse customer behaviour and transactions to build up catchment areas for location-specific campaigns.

These catchment areas will take into account customers’ common routes of travel — home, work, shopping etc. —   in order to target customers appropriately. Analysis will be important for predicting patterns of movement. For example, a customer sitting on a train travelling to work could well be in the right place at the right time for an SMS message campaign.

Analytics will also help marketers determine the optimal time at which to issue location-based messages — for example, is it better to target a concert-goer with a promotion when they are on their way to the concert, or when they are actually there?

Marketers need to respect their customers’ right to privacy. Even customers who ‘opt-in’ to receiving communications will not want to be bombarded with irrelevant marketing messages. Accurate information about customers is vital to ensure that customers receive communications that are of value to them so that they remain opted-in.

Increased automation between analytics and campaign execution will be vital   since location-based marketing is not only location specific but also time specific. The rules-based analytical engine selecting customers for particular campaigns must be integrated with the campaign–execution front-end in order to get the message out to the customer while they are still at the   location.


GIS technologies will become an important component in enterprise marketing automation solutions, as the need to understand the geographic dimension of marketing become more important. A key driver for this will be the move to using location-based marketing techniques such as those provided through SMS and the technologies following behind. When GIS is integrated with analytics and campaign management the resulting capabilities provide a powerful mechanism for sustaining competitive advantage though location-based marketing.

Software review: The system requirements and process impact of event-based marketing in financial services

Abstract This paper identifies the system requirements and marketing process impacts   of trigger or event-based marketing in promoting products and services in a financial services organisation.


A framework for classifying customer communications was described in a previous paper.1 This framework described five basic types of communication that need to be supported by a marketing database solution. These were:

  • strategic communications
  • tactical communications
  • customer life cycle events
  • product life cycle events
  • customer trigger

In the case of strategic communications the marketing activities are part of an ongoing programme aimed at meeting a specific strategic objective such as:

  • development of the brand
  • growth of a new customer segment
  • launch of a new product or service
  • managing customer profitability
  • migrating customers to the e-channel.

In the case of tactical communications the marketing activities are used to address a specific business issue, which is transient or short term in nature. Typical tactical communications are associated with:

  • new branch opening or closure
  • exploiting short-term competitive advantage
  • spoiling competitive activities
  • meeting business shortfalls
  • changes in legal or government regulation
  • changes in market environment.

The marketing activities in the case of customer life cycle events are focused around a customer or prospect life cycle event. Typical customer life cycle events are:

  • birthdays
  • changes in family status
  • changes in employment status or type
  • changes in wealth
  • inheritance

For product life cycle events the marketing activities are aimed at product life cycle events for current or historical customers. These events are normally associated with key dates or product-based transactions. Typical product life cycle events include:

  • account opening
  • account closure
  • anniversary dates
  • maturity dates
  • renewal dates
  • acquisition of a particular product combination.

In the case of customer trigger events   the marketing activities are aimed at customer trigger events for current customers. These trigger events are generated as a result of an inward-bound communication from the customer (or third party, eg a solicitor) or a change in customer–bank behaviour. Typical customer trigger events would include:

  • change of core customer data e.g. address changes
  • customer complaint
  • product or service information request, eg deed request, tax status change
  • account activity, eg abnormal transaction.

This paper focuses on the last three types of communication. Collectively called trigger or event-based marketing their importance is growing as organisations recognise the value of making communications timely and relevant.


The terms ‘event’ and ‘trigger’ have been used interchangeably. For the purpose of this paper the following definitions are used:

  • a trigger is a change in data that could provide input into an event definition, eg change of address
  • an event is defined by one or more triggers, eg change of address combined with change of marital status implying a customer life cycle event: marriage.

A trigger or an event may be used to drive a marketing communication where they provide evidence of a financial need that can be served by an organisation.


Product life cycle events have played an important role in the past in driving marketing communications as they have been easy to execute, even when the organisation’s system(s) are productcentric. Customer life cycle and customer trigger events on the other hand, have required the organisation to   be able to execute customercentric communications. Generally speaking this is now becoming the norm, certainly in most financial service organisations and is facilitating customer life cycle and trigger event marketing activities.


If effectively executed these event-based marketing communication activities significantly out-perform traditional targeted communications covering a similar subject matter. The primary reason is that these communications are more likely to be timely and relevant. The trigger or event provides both time input and context input for the communication.


The following section explores the key components required to support event-based marketing. These are:

  • event analysis
  • event detection
  • event-based campaign management
  • event opportunity

The following section looks as these components in more detail.

Event analysis

The identification of triggers and events was based on business rules with little or no statistical analysis going into identifying potential triggers or events. A number of organisations have, however, started using advanced statistical techniques to identify potential triggers on the marketing database. A range of statistical techniques have been used either to validate that a business rule-based trigger was predictive or to identify previously unknown triggers or groups of triggers (events).

The following statistical techniques should be supported:

  • regression analysis
  • tree analysis
  • cluster analysis
  • associative analysis
  • neural networks
  • pattern searching
  • text

Text mining has been used to search the content of e-mails being sent to a service centre to detect key words or combinations of words, which act as triggers for follow-up marketing communications.

A solution that is going to be used to support event-based marketing should be able to support the statistical validation of a business rule-based trigger and/or provide a statistically robust process for the identification of triggers.

The solution should include a set of business processes that structure the event analysis process for both business rule-based and statistically-derived triggers.

Event detection

Having identified that a particular trigger or set of triggers defines an event, the organisation has to put in place the necessary procedures to detect customers who have exhibited a particular trigger or group of triggers. This requires the application of rules against the customer base on a regular basis or in real time.

The following types of data may be implicated:

  • customer profile
  • account
  • account history
  • customer account involvement
  • account transactions
  • operational contact

The detection process can be problematic. The following are some examples of the issues that may have to be addressed as part of any solution.

Change history

One of the difficulties with some trigger types is that they require the detection process to look for changes in a particular data item. This is difficult, as many marketing databases do not hold history of changes at a data item level, eg change in marital status. In such cases processes will need to be created that detect these changes or maintain a history on key data items.

Query performance

Looking for a particular pattern of transactions in a large marketing database, with 100m transaction records will have implications for performance if not correctly architected. The solution must be designed with these performance requirements in mind. This may be achieved using ‘raw horse power’ and/or good database design.

Volume of trigger rules

Over time many businesses develop large libraries of trigger rules that need to be applied to the database. This will have implications for system performance and communication   prioritisation.   The solution should be able to apply a large number of rules on a daily basis and facilitate the maintenance of the trigger rules. The issue of prioritisation is covered later in the paper.

Model scores

Some organisations have found that changes in model scores provide valuable triggers for events. This means that large numbers of behavioural models (statistical procedures) may need to be run against the marketing database on a regular basis. This may have implications for system performance and the maintenance of model score history. The solution should support the use of models to drive trigger-based campaigns.

The solution should facilitate the estimation of trigger volumes so that a commercial assessment (business case) can be made before event-based campaigns can be established.

Event-based campaign management Once a trigger or set of triggers has been identified the next step is to use these triggers to drive the execution of event-based campaigns. A single trigger could be used to drive a number of campaigns. The solution should support the following campaign management processes:

  • maintenance of campaign reference data
  • identification of target audience for campaigns
  • prioritisation of campaigns
  • application of global contact rules
  • creation of communication cells within campaign
  • definition of data requirements for communication
  • execution of communication by relevant channel
  • scheduling of campaign repetition
  • campaign performance

The development of a large number of event-based campaigns often results in the need to prioritise the communications that should be sent to a customer or prospect. This prioritisation process needs to take into account other communications that a customer is due to receive in the defined time window. If this is to be done the business needs to establish a consistent metric (eg target ROI or propensity to purchase) or set of business rules that the system can apply either at the campaign level or customer level.

It should be possible to integrate event-based campaigns with other campaign types within the same campaign management application. This will facilitate:

  • planning and management of all campaigns
  • prioritisation across different campaign types
  • consistency in measurement processes
  • effective use of marketing and channel resources.

Event-based campaigns do drive some incremental requirements that the solution should support. These include the ability to:

  • do test counts
  • project future volumes for event-based campaigns (on a monthly, weekly or daily basis)
  • prioritise within campaign type and then across campaign types
  • apply global contact rules (these are rules that are used to frame the prioritisation process)
  • execute small-volume campaigns (often requiring a higher degree of automation and tighter integration with channels)
  • support more complex reporting requirements as the campaign may run for a longer period of time
  • support more complex personalisation of the communication (the trigger provides an excellent context for the communication).

Event opportunity measurement The use of global contact rules and campaign prioritisation results in a number of events not being progressed as opportunities. In order that the impact of these two processes can be measured and refined over time, there is normally a requirement to monitor the number of event-based opportunities that have not been progressed. The solution should:

  • record all event-based opportunities detected
  • flag those opportunities that have not been progressed and why
  • allow the potential business value of the non-progressed opportunities to be determined
  • simulate the impact of changes in: global contact rules; campaign priorities; customer communication priorities.

The solution should facilitate the recording of the lost opportunities and allow them to be progressed at a later stage where resource and business priorities allow.


The adoption of event-based marketing affects both the technology and marketing business processes. The following section explores the impact that this type of approach has on the marketing processes.

The following is a typical process flow for marketing campaigns and the impact that event-based marketing has on the processes.

Agree marketing plan

The lack of clear understanding of the potential numbers of event-based communications that will be initiated in the coming year makes planning very difficult. This means that assumptions need to be made on likely volumes and response rates for a type of marketing activity that is primarily driven by the customer and not the business.

Produce campaign plan

The longitudinal nature of event-based marketing campaigns means care has to be taken to ensure that they do not

conflict with other campaigns that are going to run in the year. Campaign priorities also need to be established at this stage to ensure that any likely conflicts can be taken into account during the planning stage. Some organisations also agree global contact rules at this stage in the process.

Produce campaign business case

An organisation’s lack of ability to predict accurately the volumes and performance of event-based marketing campaigns means that they often make the business case using a range of values. These values are then used to set thresholds for campaign performance. If a campaign performance falls below these thresholds then the campaign will be terminated.

Produce campaign brief

The timely nature of event-based communications means that service level agreements (SLA) with both internal and external suppliers are often much tighter than for traditional campaigns. In order that these SLAs can be met, business processes will need to be refined.

Manage Response from Supplier

 Separate contract frameworks are often used for the support of event-based marketing activities allowing the procurement process to be streamlined.

Execute campaign

The campaigns tend to be executed on a daily basis. This means that there is often a higher degree of automation and tighter integration with the communication delivery channels. The sign-off processes are also streamlined to allow things like copy and collateral to be revised in a more timely manner. Resource planning also has to be tightened to ensure sufficient resource is available to exploit the opportunities.

Monitor campaign

It is essential with event-based marketing campaigns that tighter monitoring processes are put in place to ensure that marketing can rapidly respond to changes in campaign performance. This is more critical because of the automated nature of the processes.

Analyse campaign performance

Post-campaign analysis often looks at additional marketing metrics surrounding lost opportunities, service levels and campaign performance. This is often complicated by the use of refined offers as the event-based campaigns are being executed.


Event-based marketing has an important role to play in driving customer communication in a modern financial services organisation. The timely and relevant nature of these communications means that performance is normally better than for traditionally targeted marketing communications. Delivering event-based marketing has an impact on the technology and processes supporting marketing and other functions. These need to be addressed if the final solution is to deliver business benefits.


Software review: A process change model to meet the Enterprise Marketing Automation (EMA) vision

Abstract The last few years have seen an explosion in the technologies to support the Enterprise Marketing Automation Vision (EMA), as an important pillar in meeting   corporate customer relationship management (CRM) objectives. Much of the effort spent by organisations is on the selection and deployment of these technologies with little recognition of the central importance of people and process changes to the success of these projects. This paper outlines a framework for looking at the process change issues affecting the realisation of the EMA   and CRM benefits.


The last five years has seen the evolution of technologies to support the marketing process. These initially started as campaign management systems. They were extended to allow key elements of the communication execution process to be automated, hence the term marketing automation systems. Over the last year or so these systems have evolved further and   are being used to coordinate marketing and non-marketing communications, eg arrears communications across the whole of an enterprise. This technology   is generally called Enterprise Marketing Automation (EMA).

These systems are still expanding at such a rate that this term does not really describe the full extent of integration with other elements such as:

  • workflow
  • behavioural analysis
  • decision support
  • content management
  • channel

Screen Shot 2016-03-01 at 10.26.15 AM

The result is the continuous evolution of the technology to support the marketing communication process. The growth of real-time marketing will continue to fuel this evolution process further.

What has happened over the last few years is that the technology is changing at such a rate that most marketing organisations cannot cope and the technology is not being deployed effectively, with few organisations realising the full potential. The key hurdle is no longer the technology, it is the ability of an organisation to use it. Perhaps the reason for this failure is that little serious effort is going into managing the organisational, people and process change implications.

To enable this transition a framework for the management of change is required to ensure that a balance is achieved between the three pillars of an implementation: human resources, business aims and information technology (IT)/processes (see Figure 1). The key to success is a balanced transformation that takes into account the three elements.


A key factor in delivering successful change is the development of both hard and soft change deliverables. These should focus on the work itself rather than on the abstractions such as culture or behaviour. Indeed, the softer aspects of the change process are largely   a by-product of the delivery of clear hard products that support the EMA implementation.

Change activity should be directed towards:

  • planning marketing business requirements and involvement in the technology procurement process
  • understanding the use of technology and the cost of its ownership; exploiting it to meet the business objectives stated
  • defining clear roles and responsibilities for the project and its management after delivery
  • changing processes to enable teams to concentrate on high-value activities and transferral of learning

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  • training, development and user support through clear communication structures across IT and EMA users
  • flexible tools that reinforce marketing business

The main objective should be to shift people from the current organisation structure and processes to a customer- centric framework that is proficient in the use of the EMA technology, has a clear understanding of data and can maintain a focus on the new marketing business objectives.


The foundations of success in a change management programme lie in a number of key factors that have to be in place at   the project initiation stage:

  • pressure for change
  • leadership and vision
  • capable people
  • actionable first steps
  • effective

It is important to recognise that if any   one factor is missing any potential statement of the success of the project   will be compromised. More importantly, any future business requirements and technology development will be hindered by a retrospective project and cynicism, which will be difficult to overcome.


The framework represented in Figure 2 shows the production and change delivery streams for an EMA project.

Each has a range (though not exhaustive) of the products that need to be delivered to move from the current organisation to the new EMA marketing model. The attributes of the new organisation are constructed from a combination of activities that derive from a balanced approach to management of human resources, business aims and IT/marketing processes, throughout the EMA project.


The change delivery team should comprise people chosen from across the EMA project stakeholder departments. Team members should typically be users and managers of the marketing department, and representatives from associated functions.

It is also essential that IT is   represented at both a management and delivery level. It may also be appropriate in some cases for back office functions to be represented as well as third parties, eg suppliers.


Some of the team can perform dual roles on both the production and change delivery teams. It is important that both teams maintain the business objectives of the project so that changing human resource activities and IT and business processes will reflect these outcomes.

Team members should be from across the organisational hierarchy and all activities should be strictly managed using a ‘flat structure’ environment. If necessary the project sponsor should reinforce this point by attending change delivery stream meetings and setting an appropriate example.


Both production and change management delivery streams should report directly to the departmental sponsor. If the project has a steering committee or project board then direct reports to these bodies will be necessary, however. Deploying this structure will have the following benefits:

  • the most fundamental aspect of this type of change structure is that it re-defines processes of communication and reporting from a hierarchical model to a model which is not hampered by traditional lines of communication and reporting. The change delivery team will be critical in the monitoring and evaluation of   the project after implementation. This will ensure that the change management stream benefits are realised
  • the team as a group should in time achieve consensus on the business objectives, processes and human resource needs. Bridges will be built across departments where previously they may not have existed. These ‘associations’ will prove invaluable in reaching agreement on how the cost of system ownership will be managed and will drive out the roles and responsibilities to support the project when it has gone live.


This initial stage of the change management process will set the scale and scope of activities within the change management stream. It will need to:

  • define changed roles and responsibilities
  • propose a system to log and manage issues and risks
  • develop a change management project implementation

In Figure 2 business objectives are clearly placed within both the production and change delivery streams. Strict assessment, agreement and version control of these outcomes needs to be maintained.

Activities during this phase include an analysis of the current marketing organisation, utilising questionnaires, interviews and focus groups, to assess where it is now. Then, using gap analysis, the team will need to compare this with its desired state. Key areas and deliverables will be:

  • review and development of marketing business objectives: a marketing objectives report should be prepared with a quantification of benefits to be provided, the priority attached to each and the level of difficulty to implement them assessed
  • the learning and skills needs analysis of those who will be using and managing the EMA system(s) should be constructed to which a set of actions should be mapped in the project plan
  • communication: how and what messages will be communicated? How will the project be maintained in people’s minds? What progress messages need to be delivered? How will problems be communicated and what mechanism will the project use for receiving information, eg user suggestions? The change management team will need to ensure for staff that there is a legitimate procedure to manage their concerns and to create a supportive environment in which fears can be openly expressed. This will   also bring people’s resistance to the change to the surface. A resistance management strategy should be identified. Reference should also be made to proposed recognition and reward structures
  • roles and responsibilities: who will be accountable and responsible for activities in marketing processes? What and how are other stakeholders to be consulted and informed of decisions and outputs?
  • skills and processes support: for example, across the project different stakeholder groups will have a varied set of requirements for new skills. The marketing manager will require a more in-depth knowledge of the new system and its components than a user will.

Discovery activities and their development towards the change management deliverables of the project will involve the change team in running workshops and facilitating meetings with people from across the organisation. This   is an informal launch of the change activity and an opportunity to involve people in the process so that they own the deliverables as they are developed.


Each of the areas described above will need to be developed towards the outcome that has been decided upon. How will each of these activities be taken forward? For example, commitment to the business objectives by users can be fostered through ‘business’ workshops where objectives and their implementation can be discussed. Learning and skills needs having been assessed will need to be discussed with the relevant training departments and/or suppliers of the technology. The IT department should be involved in this process by talking to users/others about:

  • the architecture of the system
  • what data will be incorporated into the system
  • software demonstrations
  • the setting of expectations at an early stage of what users can expect the system to do when it goes

As plans and activities are decided upon so should the way that project messages and information will be communicated to marketing project stakeholders. There should be a symbolic end to ‘the way things are done now’, opening the debate and dialogue about the future.

Several communication messages will be required as different people will be at different stages on the change curve, addressing their concerns and providing the answer to the question, ‘what does the change mean for me?’.

A visual identity for the project may be developed, with workshops and focus groups run to develop awareness and understanding of it. The deliverables of this phase are a:

  • vision of the future state of the marketing operation, quantified to high level structures, processes and the types of roles and responsibilities envisaged
  • statement about the technology that is being implemented, how it will help the marketing operation
  • communications plan and the delivery of the above messages in a range of launch events
  • project identity, name and, perhaps, logo.


This is the implementation stage of the change project. Its objectives are to ensure that the individuals and groups who are affected by the change programme are supported throughout the process, and that their commitment to the changes is sustained once the formal project has finished.

This phase of the project may include activities outside the scope of this framework, such as user training on the new system, business awareness workshops, or new business process implementation. Many of these activities will be covered by the production delivery. The deliverables of this phase are:

  • identified ‘straw-man roles and responsibilities’ workshops with all stakeholders
  • new process and procedures being supported by workshop and seminar activities to discuss and understand how the new process will support the agreed marketing business objectives to a detailed level
  • training and development activities for the technology and processes, supplier coaching, development and construction of support materials
  • data awareness workshops by the IT department.

This phase is about delivering products, the system is of course the key deliverable for the production stream.

The change stream will deliver marketing business process guides, mapped roles and responsibilities to new processes, and training and coaching events. (Giving users the opportunity of ‘playing’ with the system pre go-live with their data).


It is important that the change programme has a formal end, rather than just drifting to a close once the project has gone live. Although people will have been involved, there will be some trepidation and anxiety at using the live system.

The change team should act as coaches at this stage, always close at hand   if people have questions or want to talk through something. Additionally, the production delivery stream will have provided for IT and supplier time to troubleshoot issues. What is important is that, after implementation, the team faces that people are used to seeing do not disappear.

During this process the initial performance and behaviour of the organisation should be reviewed against the objectives set. The activities during this phase are to achieve sign-off for the project from the sponsor, measure the benefits accrued, and run post-project learning days where and when required. The key deliverables of this phase are the provision of a benefits report and a learning report and action plan.

The change management team should also drive the publicity, presentations and awards to thank people publicly for their efforts and promote the new marketing organisation internally   and externally.


In this paper a framework to enable successful change in an EMA project has been introduced and discussed. Successful change revolves around three simple components. People, people and people. Good technology and effective processes help, but, essentially, it is people’s understanding of the data, the technology and the use of these that matter.

For every EMA project, individual organisations will need to define what success means to them. The authors believe that it goes beyond technology and training being delivered on time, beyond creating an organisation that enables marketing teams to exploit process and systems change. These are significant, but, ultimately, success is about creating a marketing organisation that thrives on change.

Software review: Auto-ID technology in retail and its potential application in marketing

Abstract This paper describes the Auto-ID technology and its key components. It explores some of the issues associated with its widespread use. Finally it explores its potential business applications in marketing.


The Auto-ID Center at Massachusetts Institute of Technology (MIT)1 announced the launch of version 1.0 of the EPCglobal Network in September 2003. This was a key milestone in the launch of a global set of standards and technologies that allow individual items to be tagged with microchips or radio frequency identification (RFID) tags.

These tags carry the electronic product code (EPC), which allows these objects to be uniquely identified and, through wireless technology, detailed information to be maintained on the object. Thus, the products on the shelf can not only talk to you, they have a distributed memory.

This paper describes the Auto-ID technology and its key components and explores some of the issues associated with its widespread use. Finally it discusses the potential business applications in marketing.


The primary focus of the Auto-ID technology is to embed the EPC into product items; this results in objects that are intelligent and can communicate.

There are several components that make up Auto-ID technology.2 These include:

  • eTag, an electronic tag
  • EPC, a unique identifier
  • object name service (ONS)
  • Savant systems
  • physical markup language (PML)
  • business applications


The EPC is a corner stone of Auto-ID technology. It is a string of numbers that provides a unique identification; for instance, instead of referring to a class of products — as universal product codes (UPCs) do — the EPC refers to a specific instance of a product.


To facilitate Auto-ID, the EPC is embedded in a memory chip contained within a smart tag (eTag) on individual products. The chip in turn is connected to an antenna. This allows the eTag to be scanned by a radio frequency reader, which transmits the embedded identity code of the product to a network, where the detailed information on the product is kept.

This detailed information can then be communicated from the network to provide whatever information is necessary about that product.

RFID is the basis for current Auto-ID technology. It is important to note that the baseline functionality of these eTags provides read-only access to the EPC. No detailed information need be kept on the eTag.

The current technology and standards do not preclude other tags with read–write functionality or even more advanced capabilities. However, as additional functions and capabilities increase, so will the cost of eTags. At the present time, read–write tags tend to be slower and have a shorter range than   their read-only counterparts.

The implementation of EPC does not depend on RFID technology; any way of quickly and easily reading a unique ID from a product will work. RFID is the most common option at the moment, but other technologies are being tested.


The next link in the Auto-ID chain is the ONS. The ONS tells computer systems where to find information about any object that carries an EPC.

ONS is based in part on the internet’s existing Domain Name System (DNS), which routes information to appropriate network interfaces. The ONS will likely be many times larger than the DNS, serving as a lightning fast ‘post office’ that locates data for the trillions   of objects that will eventually carry an EPC.

Savant systems

Savant is a software technology that acts as the ‘central nervous system’ of the EPCglobal Network. Savant manages and moves information in a way that does   not overload existing corporate and public networks.


PML is a new standard language for describing physical objects, in the same way that hypertext markup language (HTML) is the common language on which most internet web pages are based. The PML describes the physical characteristics of an object and almost anything can be contained within the description, such as weight or calorific content, repair instructions and audit trails. PML will allow manufacturers and retailers to specify and customise the information tracked on products. (It is also technically possible for the consumer to start to collect information on the objects that they own.)

There will not be a vast repository of PML descriptions. Ultimate implementation of the PML descriptions will result in highly distributed data.

Manufacturers, retailers and consumers will all have unique views to data.

Business applications

Potential application for Auto-ID in business are numerous. They include:

  • manufacturing process control
  • inventory management
  • supply chain optimisation
  • regulatory compliance
  • recall management and

In all these areas, Auto-ID offers the potential for significant savings, as well as new sources of incremental revenue.

New services will start to emerge as objects start to become smart and interactive. As the technology becomes pervasive, benefits will extend

throughout the entire value chain and for the consumer.

Auto-ID technology has the capability to redefine the global marketplace by embedding intelligence, identity and internet connectivity into everyday objects. The EPC unites elements of the entire supply chain, making it an interactive, dynamic cycle from raw material and distribution to

point-of-purchase and recycling, and back to raw material. Products equipped with smart tags will interact with manufacturers, their trading partners and each other to form an optimally efficient cycle of direct, real-time supply and demand.


The primary focus of Auto-ID applications has been the supply chain, where   it   is   believed   the   highest benefits will come. But Auto-ID and similar technologies have a number of unique   features   that   could   provide value for marketing. These include the ability to:

  • uniquely identify an object
  • integrate data from a wide range of sources
  • read the EPC wirelessly
  • provide communication during the product purchase decision
  • access the consumer after a purchase is made.

These features allow the marketer to explore a number of new activities. Many of these can be grouped under the concept of a ‘personal shopping assistant’. Examples of these applications in the store and in the home are discussed below.

In the store

Select an item and view product attributes such as:

  • where it was made
  • how long it has been in the store
  • its expiry date
  • what the calorific value is
  • what it

Select an item and

  • remotely look up the contents of the home larder and confirm if the item is required, alerting the customer where appropriate
  • alert customer about products to which they may be allergic, eg contains peanuts
  • alert customer that they have a discount voucher for an

Select an item and view usage information, such as:

  • a recipe for an item
  • product survey information
  • product instructions
  • comparison of prices at other

Prompt customer with location of item:

  • pre-defined shopping lists can warn customer when they are in the proximity of a required item
  • a selected recipe can warn the customer when they are in proximity of the required

Select an item and receive a promotional offer:

  • provide the customer with a promotional offer at the purchase decision point based on the current contents of their basket
  • provide the customer with a promotional offer at the purchase decision point based on previous purchase

In the home

Automated shopping lists can:

  • use information about items in household and consumption patterns to automatically create a shopping list for a particular store
  • use information about pricing to optimise shopping based on price comparisons.

Select an item and:

  • warn if an item has gone past its expiry date
  • alert customer to a product to which a member of their household may be allergic, eg contains

This is just a short list of potential marketing applications; the key point is that this technology will allow us to integrate data from a wide range of sources wirelessly.


As with any revolutionary technology, there will be challenges to overcome in Auto-ID implementation. Some challenges are technological in nature, some economic, and some societal. Issues include:

  • privacy
  • accuracy
  • interference
  • performance
  • frequency availability
  • security
  • data

These are discussed in more detail below.


Perhaps the most controversial issue is that of privacy. The ability to track an item after it has been purchased raises a number concerns for consumers. Although there are limits to the current technology, in the future it may be possible to trace clothing stolen from a store for example. If this then gets sold on to an individual who   visits a location with a radio receiver, the system could then ‘check’ to see if it had been paid for.

As consumers see value in the technology, and if these genuine privacy concerns are addressed by the industry, acceptance is likely to increase.

There are also some legitimate competitive issues that come under the heading of privacy. For instance, since the EPCs will be global and unique, it may be possible to determine specific product   information   from   the   EPC given enough data. Imagine gaining knowledge of your competitors’ shelf assortment and inventory levels by walking   through   a   store   accompanied by   a   hand-held reader.


Readers cannot be guaranteed to be able to communicate with all tags in a volume all of the time. Environmental issues, the make-up of the products being tagged and the volume of tags to be read all impact on read accuracies. The degree of concern is proportional to how much an enterprise relies on absolute data. RFID offers many advantages over manual or semi-automated data collection processes. Any shortcomings in accuracy can be mitigated through the use of redundant readers, information auditing and process redesign.


As readers proliferate, more occurrences of interference will be seen. Depending on the frequencies and powers used, devices such as mobile phones, wireless handsets and industrial equipment may be affected. As such a widespread penetration of radio frequency (RF) technology has not been undertaken before, it is difficult to state categorically what will be impacted.

The perceived health risks of this many RFs may also be a concern. While there is no evidence that there are any negative effects at the power and frequency levels associated with RFID, it has not yet been rolled out on such a large-scale. More research and monitoring will need to be conducted to address the public’s concerns in this matter.


Smart objects could generate tremendous amounts of data. This much data will not be accessible if stored in a massive central repository, so some distribution of data will be necessary. This raises a number of performance issues.

Auto-ID is based on RFID technology. Anyone who has used a mobile phone will be aware of the issues associated with access to a network. In order to work therefore, the data associated with EPCs will need to be available on demand, anywhere.

Frequency availability

Since RFID currently uses sections of the unlicensed RF spectrum, the available parts of the spectrum that are usable for RFID are an issue. Although there are some frequencies that are common, there is no universal standard.

13.56 MHz and 2.45 GHz are both worldwide standard industrial, scientific and medical (ISM) frequencies. These are available in most parts of the world, albeit at slightly different regulations.

More useful in terms of read range and speeds are tags operating at roughly 915 MHz, or ultra-high frequency (UHF). The UHF spectrum around 900 MHz is not universally available at the same frequency and power levels worldwide, however.

This issue will be addressed through two potential methods. The first alternative is multi-frequency readers — overall RF system design (integration of antenna, readers and tags) is the most difficult part of the problem here. The second is to select a common frequency. Obviously, since this involves millions of stakeholders, the lead-time on this will be considerable. This does not, however, deal with the fact that not all frequencies work well for every application (although some work well across virtually all applications).


Security will be paramount and may be viewed at a number of levels, including:

  • read security (or being able to read the tag)
  • security of the data
  • other security

For users of the technology to feel comfortable, there will need to be assurances that no one will be able to ‘hack’ into a smart object. As long as tags are read-only and are difficult to counterfeit, then security will be high. Users of Auto-ID technology will also need to rely on the security of Auto-ID data on the network.

Data ownership

Related to security, data ownership is an issue. Who owns the massive amounts of event information associated with an object?

It is clear that the manufacturer owns the design specifications and other PML-type data for a given product. It is clear who owns captured data — the owner of the reader that reads the tag. It   is less clear, however, how information will be shared.

Many parties will be privy to, and will update, the data for an object as it passes though a supply chain. Will those collecting the data ever want to share data? Does an end-user (consumer) ultimately own a product and its data   and, if so, how does use of that data for process improvement or data mining impact privacy?

Lastly, although killing a tag when purchased has been discussed as an option, this method eliminates future recycling benefits. It also introduces the potential for tags to be killed maliciously or by accident, before they should be.


The ability to uniquely identify an item through the use of an EPC is a natural extension of the UPC. Allowing this   EPC to be wirelessly read and integrated with detailed data across a global network is a major leap in functionality, which will provide manufacturers, retailers and consumers with significant benefits.

The development of Auto-ID technology is evolving, but widespread use is unlikely for many years. The early adopters are likely to be industries where the value of a unit is high and tracking individual items is important. Prime targets include pharmaceuticals and the automotive sectors.

To date, the focus has been on improving supply chain management. Little attempt has been made to explore the potential marketing applications of this technology. The author believes that it has a number of unique features that will prove valuable to marketers when developing point of sale communications. It also offers the opportunity to extend   the marketing communication process into the home environment and access the full product lifecycle.

Software review: Using a business case to secure the gestation of an analytical CRM project

Abstract In the author’s experience few analytical customer relationship management (CRM) projects ever see light of the day. One of the key causes is that the project advocates do not understand the central role of a solid business case and senior management engagement in the gestation process. This paper describes how a solid business case was used to drive the creation of a successful analytical CRM project      and facilitate senior management engagement. As an added benefit the business case development process enabled the project team to identify key capabilities that could be used to materially differentiate the technology   vendors.

Journal of Database Marketing & Customer Strategy Management (2007) 14, 258–262. doi:10.1057/palgrave.dbm.325005


I often get asked how you drive an   analytical customer relationship management (CRM)  project  to  gestation  in  a  typical slow moving organisation. My first reply is often — move to another more dynamic organisation. If that is not an option, then building a solid business case and using that as a tool to build senior management commitment to the project is probably the next best thing.

The following paper illustrates how a business case can be developed and used to secure the deployment of an analytical CRM project.

It is based on a US telecommunications company. The client has asked that we modify the details to prevent  any confidential information from being released.


The original opportunity surfaced as a need for a CRM solution. With little real understanding of the potential costs the client decided to issue an RFI (Request for Information) for a comprehensive CRM solution. This RFI was completed by a number of vendors and high-level capabilities and costs determined. The project outline was then surfaced at the board level and rejected on the grounds of overall costs. The CIO agreed with the board that a smaller focused analytical CRM project should be initiated.

The analytical CRM project covered the following:

  • Design and build of a marketing data mart.
  • The deployment of an analytical CRM technology covering
    • Data mining
    • Campaign management
  • Integration of this environment with the appropriate communication delivery channels, these included:
    • Direct mail
    • Email
    • Statement inserting
    • Statement messaging
    • Telemarketing (Outbound).
  • Process changes required to exploit the environment.


The information gathered from the original RFI was used to define business and technical requirements for the analytical CRM solution. An RFP (Request for Proposal) was then issued to five vendors after initial screening using data from the CRM RFI.


After the aborted CRM project started the project team was very worried that the analytical CRM project would go the same way. So a small team was put together to qualify and validate the viability of the project. This core sales team consisted of the following:

  • Project Manager;
  • Business sponsor;
  • analytical CRM domain expert with knowledge of the telecommunications industry;
  • financial analyst with experience in developing business cases for technology solutions.

After reviewing the documents and background on the scaled-down project the project team’s assessment was that there was real business opportunity to create business value and that the technology vendors solution fit was good.

The project team was then expanded to include:

  • Technology specialist(s)
  • Technical architect
  • Business domain

The enhanced project team then issued the RFP and engaged in the evaluation process. The following were the key stages:

  • Initial solution presentation by vendors;
  • Technical architecture review with the vendor and internal IT team;
  • Discussions on project phasing and delivery;
  • Preparation of outline project plan and resource requirements;
  • Vendor shortlisting;

(At this stage two main vendors were shortlisted)

  • Final vendor

In parallel with this process the core project team had started building the business case and engaging with the business.


It was agreed early on in the process that the development of the business case would provide a valuable tool during the project development cycle and subsequent project delivery.

The financial analyst and the domain expert had determined that the proposed solution would provide business benefits in the following areas:

Increase operating income due to:

  • Automating the marketing campaign process
  • Better business intelligence
  • Capability to run new types of campaigns
  • Analytical insight — ability to better target marketing

Reduction of operating costs due to:

  • Improvements in data

A full business case document was prepared.

A range of data sources were used including:

  • Corporate web site
  • RFI and RFP documents
  • Corporate financial reports
  • Industry data
  • Experience of the business domain expert.


The following section describes the business benefits in more detail.

Automating the marketing campaign process

The campaign management component of the solution would allow the client to automate many of the existing campaigns. A campaign summary was prepared using information proved in the RFP and discussions with the client campaign manager(s).

The business case assumed improvements in the following areas:

  • additional cross sell campaigns;
  • improvement in average conversion rate for retention and win back campaigns.

These improvements highlighted specific capabilities that would be required that were only present in one of the vendor solutions. This fact helped with the shortlisting process.

These capabilities included:

  • Global contact rules
  • Campaign prioritisation
  • Access to disparate data

Better business intelligence

The business intelligence component of the solution would provide better ability to monitor campaign performance. This would allow the client of refine campaigns through the resulting learnings.

The business case assumed improvements in the following area:

  • Current campaign response

These improvements highlighted specific capabilities in one solution, not supported by the other vendor. These included:

  • Response management
  • Campaign performance forecasting
  • Extensive reporting capabilities
  • Access to disparate data sources
    • contact, promotional, response and order fulfillment data required for daily marketing performance

Capability to run new types of campaigns

The campaign management component of the solution would allow the client to run campaigns that the current solution could not support.

The business case assumed improvements in the following area:

  • Ability to run new campaign

These improvements highlighted specific capabilities in one solution, not supported by the other vendor. These included:

  • support for automated event/trigger- based campaigns;
  • support for multi-channel multi-stage campaigns.

Analytical insight — Ability to better target marketing activities

The data mining and campaign management components of the solution would allow the client to better target the marketing communications. This would result in improved response rates and above average response rates for the new campaigns.

The business case assumed improvements in the following area:

  • Response rates for current

These improvements highlighted specific capabilities in the solution, not supported by both vendors. These included:

  • support for complex data mining;
  • flexible data mining environment;
  • support for integration of the results of the data mining process into reporting and campaign management environments.

Improvements in data quality

The data quality and Extract Transform (ETL) components of the solution would allow the client to significantly improve the quality of the data used by the campaign management, data mining and reporting components of the solution.

The business case assumed improvements in the following area:

— Reduction in data quality errors.

In this case, one of the vendors had limited or no capabilities in this area.

So the development of the detailed business case also helped the evaluation team identify key capabilities that could be used to differentiate the technology vendors.


The results of the individual benefits areas were combined with costs data to produce the Investment analysis.

This summary included:

  • Profit and loss (five years)
  • ROI calculation
  • Payback period
  • NPV at 9 per cent weighted average cost of capital
  • Monthly cost of delaying the project by one

Impact on client financial statements

  • Annual increase in revenue (steady-state)
  • Annual increase in operating income (steady-state)
  • Common shares outstanding
  • Recent market capitalisation
  • Increase in market capitalisation
  • Recent share price
  • Increase in share price
  • Percent improvement in share


A template for the business case was created by the domain expert and used to engage   in dialogue with the marketing team.

Once an initial set of numbers were   agreed it was reviewed with the CMO, who then facilitated a review meeting with the CIO. The CIO and CMO took joint ownership of the document with support from us (the project team) and presented to the CFO. The final version of

the business case was eventually used by the client to justify and monitor the delivery of the project.

In the end the business case allowed the project team to engage with the:

  • Marketing team including the CMO
  • IT team in particular the CIO
  • Finance team including the

At each stage the document was refined to meet specific business or personal requirements of the stakeholders.

This collaborative approach to the development of the business case ensured that it was seen as a realistic plan.


The development of the business case allowed the project team to enter into a broader dialogue with the business.

The business case allowed the project team to

  • show that the successful delivery of

the analytical CRM solution would provide the client with significant financial value;

  • differentiate the vendors and place financial value on the unique vendor capabilities;
  • build a richer relationship with the business;
  • show that the project team had a clear understanding of the business and the business issues that the project was trying to address;
  • show the importance of time to solution delivery, this was latter used to show the potential impact if delaying a decision on the

But most of all it provided the CIO with a valuable tool that he could use to

  • validate why the project was right for the business;
  • drive through the


In my experience, few analytical CRM projects ever see light of the day. One of   the key causes is that the project advocates do not understand the central role of a solid business case and the importance of senior management engagement in the gestation process.

To ensure your project gets the required resource and support:

  • develop a solid business case;
  • link capabilities in the solution to direct business benefits;
  • use the business case to engage senior management;
  • ensure that senior management buys into the business case and benefits realisation process;
  • use C-level management to sell to other members of the

Once you have secured the project, use the business case to show successful delivery, do not leave it in the bottom drawer.

Software review: Is there a role for Activity Based Costing (ABC) in database marketing?

By Shaun Doyle

The author has been involved in a number of projects around the world where database marketing teams have been establishing Key Performance Indicators frameworks (KPI) for monitoring the effectiveness of direct marketing activities. These have ranged from simple campaign performance reporting solutions to complex customer orientated balanced scorecards.
One issue that appears to be poorly managed in most cases is the treatment of indirect costs (picked up by other departments) when monitoring the effectiveness of marketing activities. This paper looks at the basic principles of Activity Based Costing (ABC) and explores its potential application in database marketing.

The following is a simple definition of ABC. Activity-based costing (ABC) provides organisations with a means to measure and improve its processes. ABC is a technique that identifies the costs of specific activities based on their use of resources. It allows management to compare costs of activities based on process rather than the traditional departmental or functional approach to cost measurement.

Activity-based costing (ABC) provides organisations with a means to measure and improve its processes. ABC is a technique that identifies the costs of specific activities based on their use of resources. It allows management to compare costs of activities based on process rather than the traditional departmental or functional approach to cost measurement.

ABC has been popular in the manufacturing sector for many years and its use is well established. But the last few years have seen the use of ABC spreading to other business functions. Its use in marketing is still very embryonic but this will probably change as marketers start to understand the value that this technique provides.

The following are the potential application areas for ABC in database marketing:

— customer profitability analysis
— channel profitability analysis
— channel optimisation
— campaign performance analysis
— response management.

ABC was developed as a practical tool to solve a problem faced by most companies today. Traditional cost accounting systems have evolved primarily to serve the function of inventory valuation (satisfying the generally accepted accounting principles (GAAP) standards of ‘objectivity, verifiability, and materiality’), for external audiences such as the financial regulatory authorities, Inland Revenue, creditors and investors. These traditional systems have many failings, however, especially when used for internal management purposes. Two especially important failings are their inability to:

— report individual product or process costs to a reasonable level of accuracy
— provide useful feedback to management for the purpose of operational control.

As a result, managers of companies selling multiple products through multiple channels are making important decisions about resource allocation based on inaccurate and inappropriate cost information.
Traditional cost systems focus on the product, function or organisational unit in the costing process. The costs are traced to the product, because each product item is assumed to consume the resources in proportion to the volume produced. Therefore, volume attributes of the product item, such as the number of direct labour hours, machine hours or material dollars, are used as the ‘drivers’ to allocate overhead costs. These volume drivers, however, fail to account for product diversity in the form of size or complexity. Also, there is not always a direct relationship between production volume and cost consumption.

By contrast, ABC focuses on activities in the costing process. Costs are traced from activities to products, based on the product’s demand for these activities during the production/sales process. Therefore, activity attributes such as hours of set-up time, number of tasks or number of times handled are used as the ‘drivers’ to allocate overhead costs. As the number of activity measures used increases, ABC is better able to capture the underlying economics of the business’s operation, and the reported product sales and marketing costs or marketing process costs become more accurate.

Examples of marketing process costs include:
— cost of executing a communication by direct mail or e-mail
— cost of managing a response via a call centre or branch
— cost of managing returned direct mail.

These process costs may have very different drivers. For example, the costs of outward bound call may be driven by:
— hit rate (number of calls making contact)
— duration of call
— time of day
— skill requirements for the proposition.

The cost of executing a sale through the branch network may be driven by:
— number of handoffs
— location of branch
— skill set of staff in branch
— complexity of product selected.

Another important distinction between traditional cost systems and ABC is the scope of operations. Traditional systems, being concerned primarily with business functions, eg marketing, track only those costs incurred by the function, eg campaign-related spend. ABC theory contends that all the costs incurred by the organisation in managing the end-to-end customer communication process should be taken into account. Examples of these process costs in marketing include:
— campaign planning
— campaign execution
— response management
— campaign monitoring
— campaign analysis.

This means that costs may be picked up from other business functions and not just marketing. Possible sources of cost data include:
— logistics (where appropriate)
— customer service
— general administration
— production
— technology
— distribution
— sales
— financial administration
— information resources.

Many managers understand intuitively that their accounting systems distort product and process costs, so they make informal adjustments to compensate. Few managers, however, can predict the magnitude and impact of the adjustments they should be making. ABC was first developed as a solution to these problems by two professors at Harvard, Robin Cooper and Robert Kaplan. They identified three independent but concurrent factors as the prime reasons behind the need for, and the practicality of, ABC: changes in cost structures; increased competition; and availability of technology.

Changes in cost structures: The cost structure process has changed dramatically. At the beginning of the 20th century, direct labour accounted for about 50 per cent of total product costs, with material being 35 per cent and overhead 15 per cent. Now, overheads typically comprise about 60 per cent of product costs, with material being 30 per cent and direct labour less than 10 per cent. Obviously, using direct labour hours as the allocation basis made sense 90 years ago, but it has no validity at all given today’s cost structure.
Increased competition: The level of competition that most organisations face has increased dramatically. Knowledge of real product or process costs is key to surviving in this new competitive situation.

Availability of technology: The cost of measurement has fallen as information processing technology has improved. Even 20 years ago, it would have been cost prohibitive to accumulate, process and analyse the data necessary to run an ABC system. Today, however, such activity measurement systems are not only affordable, but many of the data already exist in some form within the organisation. Therefore, ABC can be extremely valuable to an organisation, because it provides information on the range, cost and consumption of operating activities.

The following are some of the specific benefits of ABC and potential strategic uses of this type of information. The first is that more accurate product or process costs enable better strategic decisions regarding:
— product pricing
— product mix
— process design
— process automation
— channel organisation and strategies— marketing spend
— investments in R&D.

Secondly, increased visibility of the activities performed (because ABC maps the activities and traces costs to them) enables a company to:
— focus more on the management of activities, such as improving the efficiency of high-cost activities
— identify and reduce non-value-added activities.

There are a large number of well-documented ABC methodologies.1 As a general rule they follow the key steps below.

Project initiation
This stage of the project is concerned with determining:
— objectives of the project
— scope of the study
— project team members
— project plan listing key tasks and timescales
— deliverables
— assumptions.

This information would normally be documented in the project terms of reference or project definition document.
Example scope: cost of using call centre for outward-bound calls.

Process documentation
This stage of the project is concerned with:
— defining the key processes
— defining the relationship between the key processes
— identifying parties implicated in the process execution
— roles of parties in the processes
— input to the processes
— output from the processes
— process descriptions.

This information would be documented as a process map and associated descriptions.
Example processes: set up campaign, set up script, brief telemarketing team, execute calls, monitor call performance.

Activities breakdown
Where a process is complex it may be necessary to decompose it into the individual activities, these may be system or people supported.
— defining the component activities for the key processes
— defining the relationship between the various activities with a process
— identifying parties implicated in the activity execution
— roles of parties in the activity
— input to the activity
— output from the activity
— activity descriptions.

This information would be documented as an activity map and associated descriptions.
Example activity: set up campaign
(process), produce campaign business case, produce supplier brief, manage supplier responses, enter campaign reference data in campaign management tool, select target audience for campaign, set up campaign performance reports (Activities). The key for ABC is to break down the processes to the right level, too detailed and the marketer ends up with too much data.

Determination of cost driver for activities
This stage of the project is concerned with determining what factors drive the costs of executing a specific activity. In most cases these drivers are determined from business understanding, but where the drivers are complex predictive modelling techniques may be used. This information is normally recorded in an ABC modelling tool.
Example cost drivers: execute call (process) call length, time of day, hit rate, skill of operator, product being promoted (Cost drivers).

Collection of cost data
This stage is concerned with collecting the necessary data to model the costs of activities. This may mean that new measurement systems need to be put in place to allow the input data to be collected. The resulting data provide input into the ABC modelling process.
Example cost data: call duration 8 min, operator grade 1, hourly rate £3.00.

ABC model development
This stage is concerned with running the model and assessing the model’s sensitivity to the key cost drivers. In most cases the model(s) would be developed on a sample of data then tested against another sample. This ensures that the data inputs into the original model are not biased in any way.

ABC model validation
The final model(s) will need to be validated with the business to ensure that what the model surfaces make sense from a business perspective. It may also be necessary to run the model using data from different time periods, to ensure that it is robust and to assess any impact over time. In most organisations ABC studies tend to be undertaken as pilots in the first place. The results of these pilots often blow away some historical assumptions about the business. This in itself can be a very powerful exercise.
In many cases the pilot itself can produce some very valuable cost data that can be used straight away to refine processes.

ABC roll out
Having built and validated a model this stage is concerned with putting the ABC model into production and enhancing the reporting process so that it can be used for management of the business (AB management). In some cases the ABC data are integrated with the enterprise balance scorecards and surfaced to the senior management on a regular basis.

ABC has an important role to play in improving understanding of a number of marketing processes. The following are potential application areas for ABC in marketing:
— customer profitability analysis
— channel profitability analysis
— channel optimisation
— campaign performance analysis
— response management.

A wider application of ABC methodologies and associated technologies in the marketing functions
is likely to be seen. The early adopters will be organisations that are executing
complex multi-stage, multi-channel campaigns. It is these organisations that
are starting to realise the issues associated with measuring campaign effectiveness in
today’s marketing environment.

Recommended reading
The following site provides a wide range of material on ABC and associated subject areas: online resource centre for Activity Based Costing.
The following papers provide good examples of the application of ABC:
IBM Sales Force Benefits from Automation with ABC, by David L. Carreon. IBM Corporation 2002.
Willards Foods: Managing Customer Profitability with ABC Information. Keith Phillips, National Brands Ltd. Kevin Dilton-Hill, World Class International 2002.
ACB An Introduction by Chris M Pieper, SAS, 2002
These can all be found on the site.

1 Many of these methodologies are covered at

Download The Full PDF Here

Affiliate Marketing 2014 – Opportunities for Entertainment/Leisure/Casino Businesses

By Greg Powell and Shaun Doyle

Customer Acquisition via Affiliate Marketing

Today, a vast majority of customers make their decisions on holidays, vacations and entertainment as a result of a review or personal testimony read online.

While some of these reviews are personal reviews, most of this content is created to steer potential customers to businesses via affiliate links.

This trend has caught the attention of marketing executives worldwide, and as a result, many have developed Affiliate Marketing Programs as a cost effective, results based marketing strategy. Many publically traded companies’ attribute more than 65% of their customer acquisitions to their affiliates’ marketing efforts. An Affiliate Program opens up the company brand to a vast audience of customers who may sometimes be impossible to reach through inhouse marketing campaigns.

Affiliate Marketing is a type of performance-based marketing in which a company rewards its affiliates for each customer brought to them by the affiliate’s own marketing efforts. There are four core participants in the process:

  • The merchant (retailer/brand)
  • The network (contains offers for affiliate to choose from and issues payments)
  • The publisher (aka the affiliate)
  • The customer

Affiliate Marketing has become the linchpin of online marketing due to the guarantee that you ONLY pay for successful advertising. Rather than paying upfront, you pay only when that advertising is successful and your company has profited. The affiliate’s payment (via a referral fee or commission) is a results-oriented function, e.g.: if a customer performs the desired action (i.e. pay-per-click, pay-per-lead, pay-per-sale) through the affiliate’s link to the merchant’s website, the affiliate is rewarded for bringing that customer to the company.

Possible Business Plan for US Casinos & Online Poker Platforms

A large majority of the online poker operators in Europe have built their player databases through Affiliate Marketing Programs. Because of the vast number of affiliate websites already dedicated to gambling, there is no faster way to reach a mass audience than by allowing affiliates to promote brands and offers on their sites.

In the US, all signs point to a significant interest for a regulated online poker and casino market, whether on a state or intrastate level. In states like New Jersey, Delaware and Nevada there are thousands of customers already playing real money games online. These players are generating great new revenue and will continue to grow rapidly in 2014.

In New Jersey, for example, where online gambling was most recently approved, online gambling sites are seeing a weekly growth rate of new players and analysts predict this trend will continue to grow as more players are introduced to the online games. Affiliates have been building sites and collecting data of NJ players since 2011 when the legislation was first being presented.

There is no question that in the new online landscape, gaming operators will adopt affiliate marketing to grow their customer base. Once an affiliate program is launched, the operator will choose between two primary commission models for their affiliates:

  •  CPA (Cost per Acquisition) for each new player who makes a deposit; or
  • Revenue Share, where the affiliate receives a percentage of the ‘rake’ generated by each player per month.

All existing, large poker software providers (real money online poker/casinos) have an Affiliate Marketing Program to support their internal marketing efforts for new players. One prime example is the growth of From their early days they embraced affiliate marketing as their primary sales force. In 2008 at the Casino Affiliate Conference in Amsterdam, a presenter acknowledged that 85% or more of new players who registered at that year were brought in through their Affiliate Program.

Affiliate Marketing is the top marketing strategy for online poker and casino sites to acquire players – and building a database of customers can be done exponentially cheaper and faster by allowing affiliates to promote each company’s offers and promotions.

Before selecting an online gambling site, online poker and casino players will research and evaluate where to spend their gambling dollars. Many of their searches will lead them to affiliate websites and they will take the reviews and recommendations into account when choosing which gambling site to join. Operators whose brand is displayed across hundreds of affiliate websites will increase their brand awareness, traffic and ultimately new registrations.

Online Gambling in New Jersey

The New York Times gambling analysts say the regulation of online gambling is the most significant development since casinos opened in Atlantic City over three decades ago. Upon the launch in late November 2013, Governor Chris Christie estimated that the States casinos would generate over $1 billion in the first year. Even the most conservative estimates place revenues in year one to over $300 million.

Online Gambling in Delaware

Delaware is yet to attract the same levels of interest that has been recorded in fellow regulated states New Jersey and Nevada. As of January 23, 2014 Delaware was averaging just 18 players online at any given time during the previous seven days. Popular websites in Nevada and New Jersey on the other hand record an average of several hundred players. Delaware officials have announced that online gambling in their state generated just $253,000 during its first two months of operations. These figures leave Delaware well short of its goal of generating $5 million in revenue during the first year of online gambling. The state will collect 100% of the first $3.5 million generated in online gaming revenue, meaning that casinos in Delaware are yet to receive any of the income.

Online Gambling in Connecticut

Online poker is a possibility for the State of Connecticut in 2014. After the 2011 decision from the Department of Justice regarding the Wire Act being inapplicable to Internet gambling or poker, Connecticut began to investigate the opportunity. Governor Dannel Malloy recently acknowledged that Internet gambling was inevitable because, ‘if one state legalized it, everyone else would as well’. The State Legislature’s Public Safety and Security Committee held a hearing in February 2012 to examine the issue, and while legislators were not enthusiastic, the two primary tribes in Connecticut were supportive of online poker. The Governor and Legislators are in ongoing discussions with the tribes to work out a possible agreement.

The State currently benefits greatly from the receipt of 25% of tribal casino revenue. In 2011, reports note that Mohegan Sun turned over more than $186 million in slot machine profits to the State, and Foxwoods added another $174 million to that. Should online poker and gambling be legalized in Connecticut, those numbers would grow exponentially.

Some casinos, in Connecticut, have already built fully functional websites and platforms: players register and play free games that can be redeemed for hotel prizes (concert tickets, restaurant coupons, etc.). Once approved by state legislature, these games could immediately be turned into real money games. To incentivize affiliates to send players to free online money games – a small commission is paid per unique registration. Then, once real money gaming is allowed, affiliates will gain real value by tagging players to their account for life.

Current Affiliate Marketing Landscape

Casinos and hotels are using Affiliate Marketing to reach audiences they were previously unable to access. Affiliates use a variety of ways to promote products and services within the terms of each respective Affiliate Program, and tend to specialize in various forms of marketing, such as: search engine rankings, blog posts, social media, pay per click, content marketing.

A search through Google will show just how many major US hotel and casino groups have embraced Affiliate Programs. There are countless review sites, blogs and trip report content pages being added to the web every day – and most of these sites have an Affiliate Program linked to them to promote offers in a variety of ways.

Launching your own Affiliate Marketing Program

To launch and start operating an Affiliate Marketing Program a company will need to:

  • Create goals and expectations on what it would like to gain from launching an Affiliate Program (i.e. sales, revenue, new customers, other metrics, etc.).
  • Select the right affiliate network or software package based on the goals above.
  • Identify which affiliates would make a great addition to the program and what type of marketing message/medium is required to attract producing affiliates into the program.
    •  An example of hotel/casino affiliates would be:,,,,
    • Online Poker and Casino affiliate examples:,,,,, • Create marketing tools affiliates will use to take offers to market (in-house/outsourced).
  • Launch a marketing campaign to promote the new Affiliate Program, making it feel exclusive and inviting. The goal is to create a buzz in the affiliate community and encourage early affiliates to promote the brand.

The biggest mistake a company can make when launching an Affiliate Program is selecting the wrong network, tracking platform and marketing strategy. It takes experience to know what affiliates are looking for in specific markets, and more importantly where to find the right affiliates who will promote specific brands. There are dozens of affiliate networks and software providers and they offer a variety of services including sales tracking, reporting, payments and more. Selecting the right provider is crucial to each programs success.

For more information on how to launch an Affiliate Marketing Program, please contact Cognitive Box Consulting LLC.