Academics say they have distilled the secrets of CRM, but complex models operating on guesswork are no substitute for readily volunteered information
The L in the formula, reproduced below, is the likelihood of purchasing a particular product, and it is derived from a number of variables, particularly R (the number of times the customer has purchased other products (j) from the company before, plus how and when). Keep to this formula, write three professors in a recent Harvard Business Review article, and you too can dramatically increase revenues, slash marketing costs, and improve ROI (return on investment) by anything between 150% to 200%. And for those of a mathematical bent, here’s how it looks:
They say that if you use Bayesian maths rather than linear regressions to analyse your data, you can address the problem companies commonly face – which is that they “lack enough data on all their customers to estimate meaningful relationships between various drivers of purchasing behaviour”, so their resulting marketing activity “hardly justifies the costs of having a CRM system in the first place”.
Another attempt to tackle the same basic problem comes from CACI with its recently-launched Ocean database: containing data from 20 different sources that brings together 100 million records to help companies build better predictive models – and combat falling response rates.
Ever more data. Ever more sophisticated maths. Is this really the way forward for direct marketing?
Here’s a suggestion: the direct marketing industry has a big problem. A very big problem. But the problem doesn’t lie in poor maths or poor data sources. It lies deep in the unstated assumptions by which the industry currently operates.
Let’s look at three of them.
First, that good marketing is about effective messaging: if only we can find the right message we can be assured of the right response. Thus CACI’s ads for Ocean ask “Does your consumer data push the right buttons?” as if “the consumer” was an automaton where, if you press the right buttons, the right response is guaranteed.
gathering more effective data
Second, that the secret of effective messaging lies in better data, so increased effectiveness depends on gathering ever more data and mining and analysing it in ever more sophisticated ways. Hence the professors’ beautiful formula.
Third, that consumer data is a natural resource like fish in the sea – there to be harvested and used by anyone who has the technology to do so (subject to the laws of the land, of course). And since the only entities capable of making these investments are companies, DM naturally revolves around companies harvesting data off consumers.
So what’s wrong with these assumptions?
Well, first, as sentient beings with their own purposes and priorities, individuals don’t always respond well to having their buttons pushed by others – especially by hundreds of different button-pushers all at the same time. The real secret of marketing effectiveness does not lie in bigger, better button-pushing. It lies in offering consumers better value.
Second, rather than seeing consumer data as a common asset, perhaps we should see it as a private, personal asset. In which case, the main benefits of this asset should accrue to the asset’s creator and generator: the individual.
This alternative view is about shoulds and oughts as much as it is about technicalities and possibilities, but its practical effects are real. It lies behind Information Commissioner research that shows protecting people’s personal information is now the third highest priority issue for UK citizens, behind improving education and crime. And it lies behind legal changes which mean that one third of the electoral roll database is no longer available to direct marketers.
Third, if the first two alternative views are right, then the future for direct marketing and CRM lies not in harvesting, selling and using consumer data. Instead, it lies in encouraging and facilitating individuals to volunteer information about what they are planning to do, and when.
There are two points to note about this alternative. First, while possible future behaviour can be guessed at from historical data, there is only one entity that actually knows the answer: the individual himself. Even the best predictive models are exercises in guesswork, and most of the effort that goes into them is spent reducing levels of error and waste.
Second, individuals will only bother volunteering significant amounts of information in a sustained fashion if they have a good reason for doing so (if they profit from it and can trust it) and if it is easy for them to do so.
Why suggest an alternative now? Because, until recently, marketers had no alternative but to do direct marketing the traditional way, as the mechanisms and infrastructure for sustained information volunteering did not exist.
personal information management industry
But today, every technology, public opinion and legislative trend is pointing towards this alternative. A new personal information management industry is emerging, which adds value for individuals by helping them access the right information about the right things at the right time and to acquire, collect, store, secure and protect, analyse, pass on the information they want and need to manage their lives better.
As this industry matures – driven mainly by technology providers, not marketers – the centre of data gravity is likely to shift; from many organisations holding small, isolated bits of information about many individuals (and desperately struggling to fill the holes by modelling and data fusion), to individuals holding ever larger amounts of data about themselves, and letting chosen organisations access and use discrete elements of this data on a permission-only basis, for clearly defined purposes of clear benefit to the individual.
As with the rise of on-demand media, this shift is currently in its infancy. It will take time for the necessary mechanisms and models to evolve and reach critical mass. Right now, it’s an R&D project.
But in the future, where should you be investing? In the professors’ clever formulae for more of the same? Or in a new model of marketing with the consumer as its biggest, most active ally?