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Customers are more than their last click


Using different data in segmentation

Wendell R Smith wrote in the Journal of Marketing in 1956: “Market segmentation involves viewing a heterogeneous market as a number of smaller homogeneous markets in response to differing preferences, attributable to the desires of consumers for more precise satisfaction of their varying wants.”

This definition still holds as strong today as in 1956. However, since then the world has changed profoundly. The past three decades have seen a rate of change never before experienced. The swift and almost blanket penetration of the Internet has had a significant impact on how we live our lives and the amount of data being produced. Every second 7,600 tweets are shared, 779 photos are uploaded to Instagram, 125,406 videos are viewed on YouTube, 2,177 calls are made via Skype, 20,000 people update Facebook, 54,000 Google searches are carried out, 10,000 ads are clicked and 1,450 hours of TV are consumed on Netflix (and these data are probably growing as I write and you read!).

The good news is that as a result of increased computer power, sophisticated technology and ever more predictive analytics we can build segmentations with more dynamic data such as an individual’s last interaction with a brand; their device of choice; page views, relevant buying history and much more.

This all sounds very positive. However, the problem with all this data is that segmentation is becoming increasingly mechanical – and the last click is getting too much attention. The largest data set detailing the customer's last action can't be the only focus as we aim to build relationships. Suddenly a marketing concept established to generate insight about people becomes all about clicks and cookies. It is crucial therefore that dynamic data is used to complement data that tells us about other parts of customers’ lives. Segmentation models such as ACORN and MOSAIC tell us about the areas people live in, we know lots of data on the home, open data tell us about transport, the locality and crime, behavioural research allows us to understand what matters to people – as customers we are much more than our last click.

For us the exciting part of combining these different data sources is the granularity we can now achieve with the speed and power of AI. Our new approach to segmentation, Quanta, has 2.9 million classifications built from multiple sources of data - dynamic and static. It enables quick and effective nano-targeting. Quanta can also be combined with brands’ own data, at speed, to create proprietary and agile segmentation to constantly monitor changes in customers, enhance decision making and ultimately lead to a more customer centric organisation. And the reason that is important is that customer centric businesses are 60 per cent more profitable than those that aren’t. The question, therefore, is can you afford to ignore this new approach to segmentation?

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