Clusters got its start, back in the spring of 2006, because we didn’t think it made sense to throw away millions of dollars
There are countless methods and tools available to conduct a segmentation, but only some will deliver robust results. At Clusters, we see that as a problem. Why invest time and money in a segmentation solution that is not representative of your target market?
Part of the problem is that these tools focus on the wrong things, dividing audiences up in ways that don’t get to the heart of what truly influences their decisions. But the biggest issue is that these tools are only about 60-70% accurate, and give different answers each time they are run.
And when you’re talking about a brand like Disney – one of our first clients – with a marketing budget in the tens of millions, potentially wasting at least a third of that on targeting the wrong people with the wrong messages would be a hugely expensive mistake.
So we developed a completely new approach to segmentation. Designed specifically to overcome the known flaws in many mainstream methods.
And, when we put our new method to work, it revealed some amazing results – moving the Disney Channel in the UK from a poor #3 position to unchallenged market leadership in just 18 months, all while spending less on marketing.
Our focus is on creating proprietary tools that can give businesses truly meaningful and reliable data. The two most significant are HuPa and Neural Conjoint+.
HuPa is our deep-learning modelling tool, specially adapted for segmentation-based market analysis and geo-modelling. It’s particularly known for its strong clustering capabilities (which is where we got our name from) and its almost-complete lack of human bias. And its 98% accuracy rate means that it’s still the most consistent, reliable segmentation tool in our industry.
Neural Conjoint+ is our more advanced version of traditional conjoint analysis, which completely revolutionises the standard approach to designing a brand or product proposition. It can not only pinpoint which features, functions, and benefits are most important to different groups of people (or segments), but also tell you which combination of attributes will be most effective in growing sales (rather than just reporting on preferences).