What is audience segmentation?
Marketing and advertising commonly concentrate on reaching the largest possible audience, but this scattershot approach is increasingly seen as wasteful compared with more targeted strategies: online conversion rates remain as low as two to three percent, compared to in-store rates of 20 percent or more. It makes sense, therefore, to take a more focused approach, aiming to target the right customer with the right product at the right time, based on an informed idea of what that individual’s motivations and needs might be. Pitching your marketing activity at a generalized audience or even a notional “average” customer just won’t cut it.
Of course, you’ll rarely know all about your individual users. Modern data capture techniques make it possible to address remarketing emails personally to an existing customer, which hugely increases click-through rates and consequently the odds of a successful conversion. You’ll still need to spread the net more widely to grow your business, however. The solution lies in the fact that large customer bases can be divided along clearly definable lines into “segments”, which can then be targeted more specifically than the entire audience. Market segmentation gives you the opportunity to more efficiently deploy resources and develop messaging that resonates with specific segments.
Before you decide to go down the road of audience segmentation, there are a few basic criteria to consider, which will necessitate some initial investment in research or even undertaking a class with Imparture!
What criteria should be considered when defining Google Analytics segmentation?
- Market size: your market must be large enough to justify segmenting.
- Difference: there must be a measurable difference between the segments.
- Accessibility: the segments you determine must be logistically reachable.
- Profitability: you need to be confident that there will be a projected net profit after the additional costs of segmented marketing.
- All market segmentation needs to be based on solid user data. you can expect better results, however, if your divisions are more nuanced and more highly tailored to the psychological and emotional characteristics of your users, not simply their location and gender.