I don’t know exactly how long it takes to read the 50 or so words attributed to me in a recent Guardian article, but I doubt that it equates to 5 minutes, probably more like 17 seconds, meaning that I still have the larger portion of my 5 minutes of fame to come. What wonders await is anyone’s guess, but in the meantime I will juxtapose those 17 seconds of written text with a note of clarification.
On enthusiastically posting a snippet of said article on Twitter (and while I sat back and basked in the adulation) an old friend and colleague and data guru @hankyjohn responded to one of my points with a contradiction. Specifically, I said:
But Loveless said he associated the idea of having a single customer view with “big, monolithic, old school, relational databases, which are horribly hard to manage and incredibly expensive”. Just collecting data on customers for its own sake is useless unless you can do something useful with it, he said: “You don’t need to understand everything about the customer, you don’t need to collect and structure everything about the customer, you just need to have a sense about them.” He said the new data management platforms do not promise a single customer view, just a general view of what that person likes and does.
To which @hankyjohn responded (quite correctly):
@alexmloveless good work. Can I disagree though? False dichotomy for me. Traditional data warehousing can coexist nicely with other stores.
There followed a brief exchange in which I heroically clarified my point. Rather than subject you to those stilted 140 character info-barks, I’ll summarise the crux of my points here.
Although I completely stand by the point illustrated in that article, it sits removed from a broader context that would have been apparent were you in the room at the time. The wider point is this: Since the days of when advertising was first invented (by the people on Mad Men) marketers and the like have endeavoured to understand their customers. Such understanding, for the vast majority of the intervening period, was derived from stuff we can learn from any detail we can collect about them (name, address, demos etc.) and performance data (what works and what doesn’t). The former data probably existed on bits of card in filing cabinets for a long time before eventually being diligently transmogrified into their digital equivalent when computers became a thing. These digital equivalents eventually required a structured form so that they could be easily accessed and queried for the purposes of selling us stuff that we don’t need. The medium for this structure was the humble database, of which for a long time there was really only one form worth talking about, the RDBMS – relational databases. Relational databases are marvellous. They impose structure on unruly data and make it easy to access, analyse and aggregate. Thus, modern marketing became used to using these things to store their customer data, which needed to be kept clean and tidy. This was how you knew who your customers were – you kept records of them in a big old RDBMS called “Customer DB” or “CRM Store” or something equally as enticing. Problem is, since there were many different sources of data, companies frequently ended up with multiple stores, often storing overlapping data sets. Quite rightly at some point marketers and IT people alike started saying things like “wouldn’t it be great if all this data was deduplicated and stored in once place” and thus was born the dreaded Single Customer View.
Roll on a decade and SCV projects that were started on the back of wishes from marketers are still incomplete and running up legacy costs of tens of millions. Meanwhile, while failing to deliver on the meagre requirements of the time, we now have all these bloody channels and social networks and mobile devices and internets-of-things and Bigness of Data. Asking IT to justbloodywell get me a dataset I can trust is trouble enough let alone incorporating twitter handles and cross device awareness. Yet marketers are still asking such things of an SCV thinking that this once-so-called magic data bullet is actually the right place for such things.
The belief is still widely held that customer data really only can live in a big ole monolithic relational data store. This comes from a lack of distinction perpetuated on both the marketers and IT people’s part. The distinction is between Master Data Management (MDM) and, well, all the other types of data. It’s a distinction between hard, indelible customer data for the purposes of hard, lofty uses, vs the sort of fuzzy profiling that proliferates across the web and haunts you with depressing display adverts for TV’s you had briefly considered buying before that whopping council tax bill came in.
Modern marketing data is not about coherent customer information, it’s about cookies and inferred data. When marketing to (or at) someone it’s more useful to know their gender than their name. A mobile geolocation is better than a postcode. A constantly evolving stream of inferred preference data is better than a mosaic classification. This is all achieved by a web of data collection technologies and services that use the humble cookie as their primary currency and couldn’t give a hoot what your name is. You could try and mash all this lovely data into your SCV but you’d end up changing your schema every two weeks and probably hit performance/scale issues pretty quickly. Plus it’ll take 6 years and countless more million quid when you could have invested in one of those mystical unicorn DMP thingies. In such a circumstance your beloved SCV data would mostly be flowing in the other direction and consequently making an anonymised cookie store the most complete view of your customer data. God forbid!
Now don’t go rushing off to Adobe or Oracle while instructing your IT team to delete that pesky SCV. You probably need it. Email comms would not be possible without it. And if you have a more tangible relationship with your customer (like, you sell stuff to them) you need a master record with accurate, non-volatile information about them that’s nicely structured, secure and private. This is Master Data Management, and only relates secondarily to marketing. And as the learned @hankjohn correctly points out, it sits happily and harmoniously in a mature data ecosystem with anarchic jonny-come-latelys like DMPs (and a bunch of other sinister data entities).
This was the thrust of my grumpy diatribe at the Guardian offices, which perhaps doesn’t come through too well in the article. I wasn’t misquoted as such, just underquoted. The moral of this story? Write more about me.