Polygons? : the cluster analysis revolution

Marketers have always been clustering. Companies simply can’t connect with all their customers, but dividing them into groups with similar characteristics, they can position themselves to appeal to these unique segments.

For ages companies have generated clusters based on demographics variables such as: gender, age, country of origin, but  with the markets transformation and the consequent evolution of the consumer, companies have been forced to adopt segmentations based on psychographics and behavioural variables.

 “Marketers are used to thinking and speaking in demographics, since slicing a market up by age, gender, ethnicity and other broad variables can help to understand the differences and commonalities among customers… but psychographics, which measure customers’ attitudes and interests rather than ‘objective’ demographic criteria, can provide deep insight that complements what we learn from demographics.”

Arguably, any segmentation is better than none, but demographic segmentation assumes that everyone that has the same age and gender thinks and acts alike, which we know is definitely not the case.

So, why do marketers still use demographic segmentation?

Because its easier. 

Gender, age and country are information easy to acquire, however it is not as easy for consumers’ interests.

But now something is changing: the traditional psychographic segmentation models are based on surveys and that means they are, yes effective but also very expensive.

Fortunately, with the arrival of digital consumer intelligence and the possibility to use web data to analyse customers, the psychographic segmentation becomes easier.

Starting with listening to web and social conversations, softwares such as KPI6, are able to analyse the audience behind the fenomena. Thanks to artificial intelligence, with one click,it  is possible to extract interests and personality traits from users’ feeds simplifying a process that required months of work with traditional techniques.

In the last  years KPI6 has worked hard to make marketers’ life even easier. 

We added another piece to our puzzle, Polygons.

Polygons is a new feature that allows companies to understand how much two audiences are similar or different. So you can understand how and how much two different clusters differ one from another.  

Polygons has a huge number of possible use cases in every industry.

Some practical examples could be:

• Understanding if the audiences of your competitors are different from yours;
• Comparing the audiences of different products within your line or between the competitors to understand how to target advertising campaigns (both in terms of audience segment and creativity);
• Understanding the overlaps of electors’ groups in politics;
• Taking benchmark products or brands and comparing them to yours in order to understand where your Market Position is.

Customers like SKY, CocaCola, ENI are already part of the revolution, don't wait any longer and embrace the digital consumer intelligence. 

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