Segmentation is part of the language and fabric of marketing strategy and a fundamental platform for effective planning and campaign execution. But, when it is referred to within the industry, it is often taken as read that marketers are all thinking about the same thing. The reality may be different.
There’s a definite disconnect between two schools of thought as to what segmentation is and does.
Firstly there is data-driven segmentation which attempts to represent ‘the reality’. This is based on real information, or as close to ‘real’ as can be ascertained, for example, from customer characteristics and transactional histories held in CRM databases.
It aims to create groups and assign individuals to them on the basis of their age, where they live, what they buy, and so on. But ‘reality’ by definition is historic, it looks backwards. This is generally fine as the basis of segmentation when looking to inform an immediate decision, particularly with regard to targeting of communications, but it may be too static to properly understand marketing opportunities in the longer term.
Then, on the other hand, there is the conceptually-driven segmentation, relying upon inferences about consumer attitudes, aspirations and potential future intensions. This has valuable applications, particularly in establishing and refining creative treatments, but is less tangible and potentially lacking a secure real world footing. It may say with some degree of flair, for example, via pen portraits, what each group of customers looks like, but also be very unclear as to how many customers each group represents, both now and in the future.
So a question has to be asked as to whether these alternatives can and should co-exist, and if so in what context – from overall marketing strategy down to specific campaign planning? After all, they both aim to group similar customers together with a view to treating them appropriately according to which group they fall within. But is it practical to make them co-exist, and would their relative strengths be overly compromised in attempting to do so?
In answering this question it is critical to fully understand the overall objective, or more likely the relative importance of several overlapping objectives. Questions arise such as: does the segmentation have to apply to customers alone or are we also seeking to assign prospects to segments? How long do we plan to use the solution for, is it a once-off campaign or a longer-term programme? How granular should the solution be, for example, are we seeking to separately create solutions specific to certain products or services, or cover the entirety of the customer base in one solution?
Once a decision is made on how the results will be used, it becomes easier to plan the basis of the segmentation. There is a trade-off between trying to achieve precision, versus aiming for a comprehensive representation.
If the objective is to segment all customers, for example, with a view to contacting all of them but with different campaign executions, this will compromise on precision since it is rare to have all relevant data fields populated across the entire customer base. Alternatively, selecting only those customers with relevant data fields populated will drive up precision but result in a potentially large subset of customers not being assigned to a segment.
To conclude, segmentation shouldn’t just be taken to mean one thing. It is important that as marketers, we are clear about exactly what we mean by the term and that before we start segmenting we are confident about what the results will be used for. By doing this we can go a long way to improve the targeting of campaigns and, ultimately, deliver a far better return on investment for our clients.
Simon Steel is insight and digital director at Eclipse Marketing
