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What We Do

Segmentations and Modelling

Significant tools in understanding your customer base

You have many customers, they come to you to buy your products and services but do so for different reasons. Using segmentations can help your customer understanding through grouping similar types of customers together, giving you the ability to gain a deep understanding of the segment.


It is this understanding that gives you the power to communicate with your customers in a targeted and relevant way. If you understand more about what makes them tick, you can say the right thing at the right time. Effective marketing is all about relevancy, which good segmentations help you achieve.

Great segmentations take it further and help you with getting your timing and communication channel right too. It helps you make the most of your budget, getting the best response rate, ROI and just as importantly your customers feel much more understood and that you recognise them as an individual, not just a contact to receive the same as everyone else.

Not all customers are the same

The approach to segmentations shouldn't be either

Segmentations can be simple or complex, it is about finding out what approach works for your business and your customers. Quite simply, they are tools for understanding buyer behaviour, the triggers for purchase and personalising the experience you offer your customer.

Adding modelling into the data preparation stage can add further depth and understanding. In a perfect world all data will be present and correct, but this is rarely the case and using modelling techniques to fill gaps in data can be useful in developing segmentations and personalisation strategies.

Modelling can also include the processes and calculations that define campaigns and reviewing their effectiveness. Useful models are based in data and help organisations to understand their customers, their organisation, their touchpoints and customer experiences. The best value to be gained from modelling is to have a clear view of your objective and then work out how the resulting model can help to deliver on your objectives.

The combination of segmentation and modelling can create powerful assets that drive activity, improving your ability to deliver personalised and relevant communications.

Targeted sales and marketing activity starts by being more effective with your resources, but ends with your customers getting relevant communications at the right time, feeling more understood and feeling more valued. They get a better experience from you, which leads to loyalty and growth.

Case Study

Customer Value Segmentation

Segmentation image.png

With finite budgets and a large customer base, our client required a segmentation to help understand the shape of their database. They wanted to understand the value of an individual customer in order to compare them and establish whether to include or exclude them from marketing campaigns based on the objectives of the activity  

Understanding a customer's rank would enable decisions to be made around the level of investment made. This would not only be limited to marketing spend, but sales representative and branch staff time. 


The starting point was to look at existing techniques for VIP and engagement models. As the segmentation needed to be easily understood and actioned by branch staff and sales representatives, in addition to marketers, a decision was taken to move away from typical Recency Frequency Monetary (RFM) modelling. This would meet the objective of using the segmentation outside of the marketing department, where concepts such as RFM are more easily understood.  


A dynamic calculation was chosen as the method of segmenting, the closer to 100 the score, the better the customer. A second angle was added in the form of a Red/Amber/Green (RAG) status to show the progression of the customer over time. 


The results of the model development were tested not only with the marketers, but also with branch and sales staff to gauge the level of immediate understanding and usefulness.  


Clustering techniques indicated groups of customers within the scoring and enabled profiles to be created, helping people across the business better understand the customer base. This supported the marketers by enabling them to understand the behaviours within the clusters and became useful in excluding customers for direct marketing activity.  


The final model was automated so that the scoring rebuilt on a regular basis and could be accessed by analysts within the business to support the marketing, sales and branch activity. The RAG status became especially useful as a method of highlighting sales opportunities for branch staff to use as it prioritised their outbound sales call lists. This became a key component in a branch support programme and was well received by branch staff and well supported by commercial and operational management within the business. 

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