Throughout this series we have been building insight, and if customer insight is correctly interpreted, it will inevitably lead to higher ROI. We have started to examine exactly why data is fundamental to the process of insight development and why the wrong choice of data could cost much more than the cost of a campaign.
Over the last 18 months there have been a number of interesting data product developments that are aiding the process of this insight development. Last month we looked at DNA a product that is revolutionising the way suppliers view the UK small business market.
This month I want to talk to you about business geo-demographics and its value in B2B.
When considering the development of analytical insight products, we first reviewed the data sources available to assist us, and what has worked historically in B2C. If you’ve been reading this page in preceding months, I hope I’ve managed to drive through the message that useful data is scant in B2B!
In B2C classification history, you won’t have to read much past ‘Page 1’ to see that geo-demographics have played an important role since the mid 70s. In fact, geo-demographics have been around a lot longer than that. We tracked the source to a Victorian philanthropist called Charles Booth, who mapped poverty in London in the late 19th Century. Based on primary data collected by schools and police, the ‘Poverty Map’ clearly shows that neighbourhoods shared close similarities in terms of poverty or need. A classification was developed on the data to describe those clusters. Although coarse in terms of granularity, the classification established the principle that ‘birds of a feather flock together’.
This is the same principle that B2C marketers adopt when applying geo-demographics for marketing. Based on statistical clustering techniques applied to the census data, now layered with other real or derived data sources, the new systems for marketing assume that basically, neighbourhoods will broadly share the same attributes and characteristics and broadly the same needs. That still seems relatively sane.
If you look out of your office window, you can quickly confound that theory in its application for B2B. If you are in a business neighbourhood the thought that geographical location means that you share the same needs ,doesn’t stack up at all. If you’re in a city centre area, there will be many different types and sizes of business all around you at a level, oblivious to each other. But that’s not the end of the story.
In thinking this through, I started to recall my old geography lessons, and about the mining industry in South Wales. We learned that all of the industries and businesses associated with mining tended to be in the areas where the coal was in the ground including smelting, rolling, cutting, transporting etc. These were mixed with the type of businesses that support the local communities (retail, catering etc).
Bringing this up-to-date we started to examine other industries and found that the marketing and advertising industry itself is a good current example of this. Many advertising agencies are based in Central London close to the higher proportion of large corporate head offices. Close by the agencies, you’ll typically find lots of nice pubs, clubs and restaurants, as well as businesses supporting the business of advertising including printing and finishing, photography, design, production etc.
We therefore concluded that certain businesses seemed to be in close proximity to others and that patterns could be identified in other cities albeit on a smaller scale. Hence in business-to-business terms, geo-demographics wouldn’t be characterising neighbourhoods as birds of a feather: instead, characterizing business mix at a small geographic level.
Applying the same clustering techniques to test the hypothesis validated exactly that; that business areas in Bristol for example could be replicated in other city geographical landscapes and vice versa. It also validated that having an understanding of this would provide a new insight into customer behaviour, and assist in supporting a new range of marketing and operational tasks such as market demand modelling, sales territory planning and media targeting. This has certainly been borne out amongst our customers.
Perhaps it’s the term geo-demographic that confuses as directly associated with that is the ‘birds of a feather’ principle. Perhaps therefore we ought to coin a new term for characterising business mix: geo-mixographics’?
