What is a Single Customer View?

Is there such a thing as a Single Customer View?

Answering the question – “what is a customer?” is fundamental in the development of a Single Customer View. It is the question that must be answered very early in the development cycle. Moreover, the definition of the customer and how a single customer is identified is one that must be agreed upon across all business functions that require to benefit from the availability of a Single Customer View.

The definition of a customer will obviously vary from business to business. Lets look at some examples.

For many retail businesses there is no concept of a customer as such. People walk into a shop, they purchase a product and they walk out again. They purchase and then they are gone. If they come back then there is no reliable way of knowing what they previously purchased. In order to develop any form of Single Customer View you have to capture some sort of electronic information about the customer. You need data.

If your business is 100% internet based it maybe that the only piece of information that you collect and need is an email address (verified of course). With a correctly designed database you can ensure that the email address is unique and so this becomes your Single Customer View primary key – the email address is your customer. However there may be nothing to prevent a person registering on your site with multiple email addresses – work, private etc. And some email addresses are shared – husband and wife use the same address. And email addresses are not necessarily persistent. Digital identities such as email addresses and IP addresses are useful pieces of data and should certainly be considered as part of your definition of a customer. But it is important to acknowledge the transient qualities of such items.

For most businesses that wish to engender a true customer relationship it is necessary to establish a business-customer link via some form of customer ID or Loyalty Number. But if these identifiers have been  (or are being) assigned prior to adequate controls (to prevent duplicates entering the system), or if the intention is to bring data from separate silos together or if the requirement for the Single Customer View is as a result of merger or acquisition then more often than not the identification of individual customers will depend on the contact / personal details held. In other words the Name (business or personal), Physical Address, Date of Birth etc. Email Address, Telephone numbers can be used with care.

So in a B2C environment a single customer might be:-

  • A single individual person i.e. for life insurance type products
  • The family unit i.e. for household items
  • The physical address i.e. for such items as fitted kitchens

Though it is easy to see how a business might want to make use of all three definitions for different purposes.

Similarly in a B2B business the different business functions may have different requirements. Lets say you are a business selling PPE to building / maintenance companies. To the salesman out on his rounds, his customer might be “Big Eric”¬† who works out of a portacabin on a particular site. To the head of regional sales the customer might be the head of procurement in that particular region. To the head of finance the customer might be the finance director for the parent company.

So I suppose the question that arises is – “Is there such a thing as a Single Customer View?” Or are there different views of the customer base required for different purposes?

In my opinion it is and always has been the latter. This is especially true when you bring data quality into the equation but I will discuss this in forthcoming posts.

Suffice to say (and at the risk of repeating myself) gaining absolute clarity on what your business needs from a Single Customer View solution is without doubt the most important task to be undertaken at the requirements gathering stage of any Single Customer View program.

In my next post we will start to look at the “dark art” of matching, how matching decisions are made and the impact that data quality has on the decision making process.

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