Moving on from our previous post, let's talk about lifestyle modelling.
There are a number of ways in which you can use the data that you hold on your customers to build up a more accurate picture of the type of lifestyle and habits they are likely to have. This can be a very powerful way of determining how you should talk to these customers, what offers will suit them and, of course, how you can maximise the income from your program.
These segmentation methods are based on the finding of a deeper level of data analysis. Deeper analysis of your data will identify patterns that can be used to build customers into groups which tend to exhibit similar behaviours. These groups are most likely to be based on:
- Buying patterns
- Age groups
- Regions in which they live
- The types of products browsed and purchased
As every company has a different set of customers and products, it's very often quite different factors which work for one organisation in comparison to another.
This level of analysis can be very costly and time consuming and can often also be dependent on other data being available within your organisation.
What's next? Bringing it all together in our implementation post.
Source: Digital Marketing Association - Whitepaper "A Guide to Data Analysis and Segmentation"