In Customer Management Level I, we discussed the different segmentation techniques that banks have used to segment their customers into groups that they can then target with offers.
The process is:
Typically, banks have hundreds of thousands or millions of customers, all using their products and services in slightly different ways, generating millions of datapoints that, if understood would help the bank allocate its finite resources to create value.
In this module we will now focus on how banks use behavioural segmentation to understand where to allocate resources to acquire new customers, grow existing customers and keep customers from moving to a competitor – asking questions to develop what they need to do to direct resources to where value will be created.
This begins with the selection of a suitable base. Depending on the purpose of the segmentation exercise, it could be the entire population of adult consumers, or a sub-set of them, or their current portfolio of customers. Marketers are looking for a means of achieving internal homogeneity (similarities within segments) and external heterogeneity (differences between segments) to minimise the differences between members of a segment and maximise differences between each segment.
The process must yield segments that are meaningful for the specific purpose. It requires a good understanding of the market to be segmented. Segments must be:
In undertaking the above, the bank may determine that some segments in its portfolio of customers aren’t currently actionable or valuable. It’s not uncommon for senior executives and others to demand that the bank withdraws from or closes certain customer segments. However, the fact that the segment may not be valuable now isn’t an automatic reason to close or withdraw, but a challenge for marketers to find a way that turns these customers into valuable ones.
Instead, executives should ask how the bank can reverse the situation by allocating resources to where customers are asking for solutions to problems, help in achieving their dreams or where the segment is currently losing money.
We discuss the subject of how to allocate resources in more detail later in this module.
In Customer Management Level I, we described behavioural segmentation as “Using behaviour exhibited towards your organisation, include the products and content consumed, and interaction frequency.”
Customers with the same set of products, using the same channels can behave differently.
The bank usually has an idea who their ideal customer should be. It sometimes comes as a shock that they don’t have the customers they thought they did. This may explain why they aren’t meeting their strategy or plan and will lead to a radical rethink to deal with the reality.
The earlier section on Customer Data describes the typical data that a bank must collect and make available for segmentation and other analysis. The data used must cover a reasonable period, for example a six months to twelve months period.
Data quality is crucial. However, it is usually at this point that the bank realises it has data quality issues that must be fixed before behavioural segmentation can be undertaken.
Depending on the purpose of the segmentation, this will include:
We have discussed the capabilities of both the analysts and their platform. Both must be capable of handling more advanced data mining, integration and analysis techniques using machine learning, artificial intelligence, and advanced visualisation techniques.