Could marketers view historical customer data like an archaeologist?

Could marketers view historical customer data the same way archaeologists view excavating a historic site? It may sound daft but we believe that the answer is a decided yes!

Archaeologists view a site that they are excavating as a series of layers. With each layer representing a distinct historic period –  this dating approach is known as stratigraphy.  They use this to associate different items of evidence with each other and can, for instance, differentiate Bronze Age pottery from Iron Age by how deep they find it in the ground at a particular site.

But the preservation of remains and artefacts within a layer tells much more. For instance, petrospheres are now known to have been used for smashing large bones to extricate the marrow. This is because these spherical stones and the broken bones have been found together in the same layer of Palaeolithic sites in the Middle East.

So, we marketers can look at historical customer data in a similar way. We can see what customer behaviour has taken place in each time period, in response to what stimuli, and learn vast amounts from that.

For this to work we need to make sure that our ‘stratigraphic’ customer data has been carefully collected and maintained. Clients need to ensure that all transactions, contacts and customer attributes [such as their source of recruitment and demographics] have not been discarded along the way.

What will this customer data tell us? What Tutankhamen can we expect to uncover?

If we take a group of customers recruited in a specific time period, we can look at the order value they on average provided in their first, second and third year from recruitment.  This will the help guide us to understand how much we can spend on recruiting them.
historical customer data acquisition chart

Now some of these customers will have only purchased once, and others will have purchased more often. Having uncovered the different groups we can start asking what differentiates them.

historical customer data retention chart

Often the source or channel of recruitment is the biggest factor in determining what their future value will be. Will a Facebook derived customer be worth more or less than one that comes from Google PPC? Their age at time of recruitment and their geodemographic can be of great significance.

Looking at the different customer layers we can start to ask questions about how the external environment has impacted their behaviour. Customers recruited in 2008 and 2020 cannot be expected to behave like customers recruited in more normal years. And when the economy shrinks, we can look to see whether demand has just been postponed or lost forever.

Could marketers learn a trick or two from archaeologists? Historic customer behaviour data sets are a gold mine if used properly.  To extract the value you will need both the customer data store, and the data archaeologists who can uncover the buried secrets.

In marketing we call these archaeologists data scientists.

We have developed our company UniFida along the lines of an archaeological dig; we collect and store our clients’ customer data (protected by UKFast, UK-based data centres ISO certified, PCI DSS compliant and secured to UK government IL4 standards) in our cloud-based technology, and we then deploy data scientists to extract meaning and learnings from that.

Please don’t hesitate to get in touch if you are sitting on a customer data site that needs careful ‘excavation’.

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UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.