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.