Behavioural Segmentation looks at the transactional data that is all around us from actions such as website visits, purchasing habits etc, through the analysis of this data you can then segment your target and current customers based on their behavioural patterns.

You might wish to group your customers by:

  • The frequency in which they buy from you, grouping ‘regular’ customers together and those who only buy from you on special occasions.
  • Grouping customers who have a higher interaction with your different marketing channels and may be more likely to convert.
  • The different occasions/events which prompt purchase.

& more

Three use cases for Behavioural Segmentation

  1. Identify engaged users – As a general rule of thumb the more engaged a prospect is, the more likely they are to convert. If you have data on email opens, time on site, past purchases etc, then you can segment your database/marketing list by this attribute. Not only can this help you to decide which prospects your sales team should engage, but it can also show you what content and channels are having the most impact.
  2. Improves targeting – If you can identify the customers who spend more/ more frequently then you can more easily improve the ROI of any marketing by adding on a transactional lens. If you understand who is likely to spend money with you, and the products/services they are interested in, personalisation becomes a lot easier.
  3. Budget Allocation – You should always align your most expensive resources with customers most likely to convert and go onto have a high lifetime value. Sales calls are significantly more expensive than emails for example and should be reserved for the right targets. Behavioural segmentation makes this easier.


Behavioural Segmentation is particularly useful when considering the customer’s journey. By understanding the ways in which different users interact with you, you can identify at an individual level the buying stage that your customer might be in, their role in the purchasing process, the obstacles they are facing, the incentives they’re most likely to respond to. etc.

This can then allow your marketing team to optimise the different elements of your customer journey for maximum effectiveness. For example it could be that potential customers often visit the ‘about us’ page before enquiring, which may inform marketing that more material is needed about the organisation’s history and pedigree.

Transactional data from marketing channels has also been useful in establishing a ‘burn time’ for customers. This is how long it takes a prospect to convert into a customer and the steps they take to get there. In the past many organisations would only become aware of a prospect when they enquired, but today they can track different interactions through multiple touchpoints. By analysing this data,  brands can form strategies to reduce the ‘burn time’ and make their customer onboarding journey as smooth as possible. This could be for example, establishing common questions that prospects have and ensuring this information is available in a variety of formats.


While transactional data is definitely useful, it only tells you you’re wet after it’s been raining, it doesn’t tell you anything about the needs and motivations behind actions. For example it might reveal that a particular customer had suddenly started visiting multiple times a week, instead of their usual weekly shop, but why? Do they need to do additional shopping for a party? Do they have guests coming over? Understanding the needs, motivations and events behind purchases would give us a much clearer picture of the action we as a business should take.

It also only gives you a consumer’s behaviour within the context of your brand, and it is difficult to tell if this is such activity is typical for that person. As an example, there may be a perceived correlation between newsletter opens and interest, but there is no data that would tell you whether an individual may simply read all of the newsletters which they receive. This has meant that behavioural segmentation is still reliant on generic information and industry trends when considering buying patterns.

Another issue with Behavioural Segmentation is it also heavily reliant on people interpreting the data correctly and understanding/being empathetic to the thought process and decision making process for customers.

While Behavioural Segmentation has its uses, its rare in today's complex world that we would ever advise looking at your customers through one lens or another. It's only through some advanced data crunching and multiple analytical lenses that you can build up a detailed picture, get closer to your customers, and better serve them.

Learn the basics of Segmentation in our series of articles.

Find out more

Understanding moments that matter with occasion-based segmentation

Webinar on demand

How segmentation is rising to the occasion

Read article

Contact us today

Get in touch today for a no-obligation meeting with a member of our team. All information is treated as confidential and we are happy to offer our opinion or point you in the right direction.