In direct marketing there are very different challenges for the marketing manager, depending on whether they wish to approach the general public (“Business to Consumer” or “B2C”) or to communicate with other businesses (“Business to Business” or “B2B”).
One of the key differences is in market segmentation. It is of course true that some of the ways of slicing up data are common to both business and consumer markets. For example, recency/frequency/value of past sales is one way of segmenting a data list that can be applied to both B2B and B2C data.
However, beyond this the B2C data can be cut in a myriad of ways to provide the marketing manager with an almost infinite number of ways to ‘slice the cake’ and find common attributes, behaviours and values between markets to build better quality direct marketing campaigns.
Lifestyle and demographic segmentation
For example, some people have been known to segment according to political persuasion. Others may slice according to religious belief or what brand of beer the prospect prefers. Such ‘lifestyle data’ questions are of course meaningless when applied to a B2B setting. However when B2C lists are segmented according to such apparently random factors, the results can yield lists of amazing value to the marketing executive.
Consumer modelling and analytics methodologies can determine common lifestyle and demographic elements among customers. A model of a typical current customer can be used to find ‘look-alike’ prospects with similar lifestyles and demographics. One of the best know models in B2C data is the ACORN classification, which describes the typical behaviours of people living in a neighbourhood that a postcode has been matched to. For example, people living in Richmond upon Thames and St Albans (both ACORN group 19) are more likely to take holidays in Canada than people living in Harrow (ACORN group 31). This very specific piece of B2C data would prove of real value to those working in the travel industry who might wish to promote their latest deals on flights to Canada or similar destinations.
Another way of slicing B2C data is to look at purchase information to build a picture of buyer behaviour. This insight can be used to plan how best to influence purchases for greatest profit. Timing a promotion to coincide with when a customer is more likely to make a purchase of a certain type.
Intelligent use of B2C data reaps huge reward for the smart business.
Greater profit through enhanced understanding of customers
Segmentation allows businesses to create special offers, products, and deals for groups of customers with similar needs that solves their particular problem or want. Ultimately the aim is to generate greater sales due to a better understanding of what a customer wants, when they want it and at what price.
Knowing how consumers change over time is also important. Keeping track of say when they may change jobs through promotion could indicate a higher disposable income and therefore a new desire by them for status goods. Or if they start a family a whole new set of selling communication and selling opportunities presents itself. This B2C data is invaluable in maintaining relevant and constant communication to maintain customer loyalty.