In the world of big data, it’s tempting to think that every problem can be solved if we just throw enough data at it. Sometimes maybe that is true, but there are a whole set of questions out there that demand a different response. These questions start with *”Why…”*.
Segmentation is a particular example of this. Traditionally, market segmentation was an attempt to balance the need to market to a large number of consumers with limited resources. To do it in a targeted and more efficient way. It’s tempting to think that in today’s world, with the promise of big data, cloud computing and AI, that this is no longer a problem, and sometimes you’d be right. Using all of the data they collect and store, companies can market to their customers in a hyper-targeted way, picking the right product to push at the right time.
The issue is that all of this is looking backwards. Companies predict future customer behaviours based on what customers have done before. How does that work when something unexpected happens? What if a disruptive challenger brand enters your market? Or there is a major change in the political environment in your key market? Or an unexpected global pandemic? If we want to understand how customer behaviours are going to change we need to ask why a customer is a customer in the first place.
A segmentation that encapsulates not just what a consumer does, but why they do it has a key role to play here. If you understand both sides of the coin you’ll find yourself in a unique position of being able to predict behaviours in uncertain circumstances.
When we were challenged to update a leading technology brand’s segmentation, we worked with them to understand the relationships between attitudes, motivations and behaviours. This ground work lead to a set of segments on which we could start to plan for behavioural changes.
So, next time you’re thinking about consumers, don’t just stop at what they are doing, but ask yourself why.