If I were to ask you which of your customers are most likely to convert tomorrow, would you have the answer at hand? Or at the very least, the data available to provide an accurate answer? 

The problem: an increasingly complex digital ecosystem 

Part of the problem stopping you from understanding and reaching consumers is that the digital space is becoming increasingly saturated as customers are bombarded with advertisements. It’s now more important than ever to advertise effectively by sending individuals the right message at the right time. 

However, a generalised marketing mix cannot provide the answer to your market’s diverse consumer needs. Indeed, it is necessary to target users with a personalised marketing mix, or at the very least, a personalised message delivered at the right moment. Simply having a better understanding than your competitors of your customer base, their behaviour and their needs is a competitive advantage on its own. And it pays off! According to Harvard Business Review personalisation can help return 5 to 8 times your marketing investment and increase sales by 10% or more. 

Secondly, thanks to modern technologies, consumers are navigating the digital ecosystem at an extremely fast pace. But you might not have the processes in place to keep up – or in other words, to take timely, strategic marketing decisions based on relevant data to send the right message to the right person at the right time.  

Remember, not all your website visitors will consume your products and services at the same pace or in the same way. Some may even change behaviour over time. It’s therefore important to know who they are and how they are distributed throughout your market segments at any point in time. Nonetheless, gathering the necessary data, analysing it and laying out your marketing accordingly can be a very time consuming and inaccurate process if you aren’t able to access this information. 

This is particularly true for your segmenting efforts, which can present a real problem, as getting your segmentation right is paramount to the success of your targeting and positioning strategies further down the line.  

The 5 keys to a strong segment 

Thankfully for us marketing professionals, marketing theory lays out common characteristics which successful marketing segments share. 


1/ The homogeneity of consumers within each segment  simply put, its important consumers within each segment have similar needs and/or behaviours. As you develop a tailored marketing mix to respond to each of your segments needs, you want to be sure your users will react in a similar fashion.

2/ Sufficient heterogeneity between groups of consumers – in plain words, you want to make sure consumers’ needs and behaviours differ between groups. Why? So you don’t waste resources and time designing different marketing mixes for consumers who, at the end of the day, have the same needs.

3/ The segment’s accessibility and your firm’s ability to act on a segment. There is no point targeting a segment that your business will not be able to reach. For example, if you’re communicating with a specific audience via mobile ads but they don’t use smartphones, they will never see your ads. Therefore, it’s important to make sure you can connect with your end users.

4/ Ensure your segments are measurable. Indeed, once your segment is defined it’s important you can accurately evaluate its potential worth to your business.

5/ Once you have evaluated a segment’s worth, make sure it is substantial enough to justify your business’ attention. Several KPIs will enable you to establish worth and benchmark segments against each other, in addition to measuring the turnover generated: consumer churn rate within segments, customer life time value.

Segmenting by consumer purchasing behaviour

As a company’s bottom line is closely linked to its ability to sell products, perhaps one of the most interesting dimensions when segmenting consumers is their purchasing behaviour. A successful methodology for this is RFM: segmenting consumers based on recency of last purchase, frequency of purchase and monetary value, or total amount spent, which illustrates their willingness to spend money with your business. In the RFM segmentation process, users are classified into several segments with other users who performed similarly against the dimensions mentioned previously.


However, the resources required to calculate segments and their potential worth on a daily basis can prove costly. If, like many businesses, you lack the time, resources or data necessary for a clear understanding of your customers, we have a solution for you.

Deciphering purchase behaviours & customer value

At AT Internet, we have always provided the freshest and highest quality digital analytics data. Our most recent challenge was to go a step further and illustrate and transmit this user behaviour data in a digestible and easily actionable format.

Enter RFM, our new “smart” segmentation module which clusters users and provides predictions of their future value. Built using the proven RFM marketing methodology for segmentation and data science models developed by our experts, RFM is fully automated and updated daily. Your active online customers are classified into easy-to-use and actionable customer segments with peers who share the same purchasing behaviour, such as “recent trial buyers”, “skepticals” and “most loyal”.


By using the RFM methodology, our tool naturally ensures the homogeneity of users within segments, and the heterogeneity between segments, while at the same time making them measurable by combining this information with your website data.

With RFM, you also get automatic predictions on users’ future value (user churn for example) based on proven and tested data science models we’ve developed. By integrating this data with turnover figures for each segment, you can measure the potential future profitability to make sure segments are substantial enough to be worth your time and investment.

User behaviour data is both rich and complex to decipher. The RFM tool makes it understandable to all and easy to leverage by exporting the data and determining the appropriate resulting marketing actions.


For example, imagine these cases:

  • You’re reaching the end of your marketing campaign with some budget left over; however, you still have some ways to go before meeting your campaign sale targets. To optimise how your remaining budget is spent, extract information from RFM on your most efficient converting customers who will provide you with the most bang for your buck: your “Stars” user segment.
  • Price-based messaging can be very effective with direct marketing when targeting the right users with the right price message. Using RFM’s heatmap with the “average revenue per paying users” metric, you can tell on average how much each user in each segment spends over a given period. With these insights, you can push tailored price-based messaging for specific segments at a much more detailed level, thus optimising your direct marketing actions.
  • You’re launching a fresh marketing initiative aimed at retaining users and reducing churn. Use RFM to extract information on users who were once located in a very active segment but who have migrated into a less attractive segment over time. Take things a step further by analysing RFM’s churn predictions and targeting users who are unlikely to return to your site.

How you choose to design your marketing strategy is up to you; however, one thing is for sure: the digital ecosystem is increasingly complex and proper customer segmentation as a first step to understanding your consumers isn’t just a best practice – it’s a necessity. Unfortunately, the reality is marketing professionals do not often have a clear understanding of their customers’ needs, often due to a lack of time and resources. Therefore, it’s important to equip yourself with tools that can deliver the right data at the right time, helping you uncover the insights necessary for informed marketing decisions.

Analytics Suite 2 Digital Analytics reinvented

With five years of experience consulting on the digital ecosystem and with an academic background in marketing, Fabien thrives on the challenges posed by web marketing and analytics. As a Product Manager at AT Internet, Fabien focuses on producing relevant and actionable data science products by keeping consumers front of mind.

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