Consumer data is emerging as an unspoken battleground among the many emerging routes to the digital music market place. New models for making money out of recorded music continue to grow and proliferate, and no single model yet seems to be winning out. But lurking in the digital undergrowth, the recurring theme of consumer profiling is cropping up all over the place. It’s not surprising, given the long hazy years of little two-way relationship between recording artists and their fans, that in our new data driven day businesses are rushing to try to fill the gap.
Interestingly in the music space, there is little open talk of CRM yet, most are still experimenting with how to make new distribution or aggregation models work and with trying to create consumer offerings that are more compelling than p2p. The focus is still on trying to monetise the transaction at the front end securely, on how to reduce friction and margin-slicing in the transfer from final mix to consumer or on trying to substitute the consumer transaction for an advertising based solution.
And yet lurking in the business models of many of these new players is a growing sense that data about consumer behaviour is going to be a driving force and a most valuable one. And it is massively needed by the marketeers. Anything that can help bring down the cost of launching a new artist will be hungrily received by the artists themselves, their managers or the labels they might consider signing to. Of course, the unpredictability of fashion and of the “kids on the street”, means that risk will never be eradicated from this story, but that only serves to increase the value of anything that can reduce it. Intuition, street awareness, being “one of them” – and occasionally actual market research – have been the main ways that labels have understood the interests and behaviour of their fans in the past. But as that behaviour has migrated more aggressively online, so it has become more trackable and potentially much more valuable – even if it’s never ultimately second-guessable.
Understanding the different paths that fans take to different pieces of digital content alone starts to help, understanding everything about what they buy and do online would be even better. Connecting that with their real world actions would almost complete the picture. It might well be that dubstep fans in London tend to be quite eclectic, sample clips but rarely buy except ring tones which they use for mashups and then maybe buy a few psychedelic wallpapers. Conversely, grindcore fans in Milwaukee might well turn out to be more encyclopaedic in their purchases of everything available for a much narrower selection of acts. Matching these behaviours to digital interactions, digital purchase data and to concert attendance will be a compelling means to closing the loop. Knowledge of this kind will be a powerful driver in honing new marketing campaigns, customer acquistion and retention programs based on more than just a product manager’s one or two painfully hip factors.
Once you have access to data of this kind on a statistically meaningful scale and if you also have access to the individuals, then you start to know much more precisely the manner in which you should most successful reach out to them. You’ll know if they are the kind of fan that wants to engage in an interactive, blog driven dialogue with an artist or a community around a band – or if they just prefer to be told when the new stuff is coming out and then they’ll just go buy it. In this kind of environment, the more permission-based access to highly profiled music fans you can assemble, the more powerful a marketing tool your business can become.
Forrester Research forecast sales of generic CRM process software will reach $2.7 billion by 2009 and that of course is an estimate focussed largely on the trending sales of the big players like Siebel, Peoplesoft, Salesforce, etc. Music related software sales would only be a small portion of that, but the real value of developing a business around this data driven model is to be derived from the other businesses that implement it and sell on their aggregated knowledge to artists, managers and labels.
The new mobile services from Nokia and Sony Ericsson are going to have pretty tight data-lock in with their customers as they accumulate ownership of music on their system. Combine that knowledge with the new mobile phone based ticketless concert-entry purchase systems and the potential is rapidly apparent. No doubt the deals the major labels have just all done with the mobile operators includes a high degree of data sharing in the aggregate. But of course even as Europe continues to lead in developing sophistication of its mobile consumers’ behaviour, the tightness of consumer data protection legislation here means that the mobile operators will have a signficant benefit over the majors – they will know who the customers are – and where they live – not to mention the destinations of the phone calls they make.
Interesting questions start to arise as we see the massive and diverse proliferation of products, services, platforms and widgets that each are capable of generating customer data in different formats across different but frequently not matching areas of consumer activity. And so right now, every business that is even thinking of signing up fans and artists is also dreaming, if not salivating at the prospect, of the ability to deliver this kind of data to a massive degree. The question will be who can get the best qualified profiles and the most responsive permissions. It will also be about who can effectively aggregate and match the data sourced from multiple sources across multiple geographies to define profiles and data even more precisely. The battle is truly on. And of course, all these guys are thinking, if we can make this work in music just think how many other verticals we can apply it in!
The real unknown in this though is how susceptible music buyers are to this kind of relationship management. Undoubtedly there will be some sectors and some musical genres that will demonstrate much more predictability than others. Music fans’ relationships with their favourite bands and artists are not based on some rational set of statistical metrics, but on emotional, cultural and above all transient characteristics which might just mystify the best of algorithms – what we can’t yet tell is just fickle they turn out to be.