Market segmentation – breaking down the pool of all (potential) customers into specific groups – has two key benefits. First of all, it leads to a better informed marketing focus on people who are more likely to become customers. Secondly, it highlights particular marketing methods and messages to particular target markets.

Businesses can segment markets in many different ways, but a few types are particularly common:

Geographic segmentation allows businesses to break down audiences by location, whether that be country subsets or as narrowly targeted as street-by-street subsets. This can apply to suppliers looking to break down business subsets as well as firms targeting consumers.

Demographic segmentation allows targeting of people of a particular age, gender, ethnic background, income level or a combination of multiple factors. Lifestyle segmentation involves consumer subsets that are more about what people do than who they are; e.g. grouping those who are physically active or enjoy particular social events.

Cultural segmentation is more about grouping those with similar ideas/customs/beliefs; e.g. a drinks manufacturer might specifically target people who are more likely to be teetotal for cultural reasons to try his non-alcoholic offerings.

Relevancy And Accuracy

At first glance, it may seem that the essence of a segmentation-based marketing strategy is the quantity of data: the more data a business gathers, the easier it is to identify groups of likely or unlikely customers. This has some truth, but with a couple of provisos. Relevancy is as or more important in data than sheer quantity; too much detail and it’s a case of not being able to see the wood for the trees.

Accuracy over time is also key. For example, at one point it seemed that tablet computers were best aimed at young tech-heads, but more recent data now shows that older people who’ve never used the internet and don’t own computers can be a viable market segment.

The Secret Ingredient

Visualising data, such as geographically, can be very effective. Because humans are so good at quickly filtering and assessing all the important detail in an image, a map can turn raw data into something more valuable. For instance, census data might show many people live within close distance of a potential pub site, but a map could highlight if those people live on the wrong side of a river or major road that might put them off what would otherwise be a short walk.