You could be forgiven for thinking that we are in the middle of a Big Data explosion. Everybody is talking about it. Big communication companies are seeing it as the next Big Step. WPP's recent stake in Globant is an attempt to establish some integration between all the various data sources it has in its huge and ever-growing global basket of companies.
Chiliad is an example of an organisation offering services that collect and collate. The real question is where is the value in such an enterprise. Because, for sure, there will be value.
In fact, it's early days in the big data game. The software needed to integrate analytic data (zip codes, phone numbers, credit card charges, driver licenses etc.) with unstructured data (social media, websites, CSR, email, image meta data etc.) is still in its infancy. Issues of value are still being debated. Gartner has made some interesting first steps, showing that there is substance behind the hype of Big Data. Gartner believes that "Big Data is moving beyond along the hype cycle with an increasing number of companies launching Big Data projects. Hence, while 27% of enterprises had launched a Big Data project in 2012, with another 31% intending to do so in the next two years, by 2013 30% had deployed Big Data projects, with another 34% expecting to do so in the next two years.
That's a big jump (64% in 2013 compared to 58% in 2012), and it reflects a growing confidence that Big Data can help to enhance the customer experience (54% cited this as their driving motivation), improve process efficiency (42%) and launch new products or business models (39%)".
To me there remain some big questions around this science, which has a kind of General Universal Theory of Everything ring to it.
It's the Holy Grail, isn't it - linking all data to know all things? (After all, Knowledge is Power, as Sir Francis Bacon reminded us way back in 1597).
The first question is what do you intend to do with this interconnected data? If it is sold as a cure-all customer management system it will need constant updating as we give our data out to new services. Just when we thought SnapChat was the answer, WeChat from TenCent comes winging its way across to us from China.
It is the nature of the Internet that new things will come all the time. And we'll donate our data willingly. So new data just keeps coming and the idea that this can effortlessly integrate into the existing data pool is a big ask.
Interestingly, from the perspective of the humble consumer, data is all about Small Data. It's about "Me" data. We give up certain liberties and privacies because we think it will benefit us. The more we see the benefit, the more we give.
And the opposite happens too. If apps or online services can't hold our attention we'll drop them, or let them wither.
Which creates an interesting effect. The data being held keeps changing. It keeps validating and invalidating itself. This surely creates operational hassles. Or, alternatively, suggests that the data being integrated will always be somewhat out of date. Or, worse, the data management systems will be hard to operate, particularly for brands that want fluidity of process in real time.
Which makes me think that the real value of mega-integration might not be in the companies that do the integrating. It might be in the secondary products and services. There are many valued companies who exist symbiotically with much larger data farming organisations. WalkIt uses Google maps, Instagram (and many others) benefit from the facebook sign procedure.
This is an example of Digital Symbiosis whereby smaller, often bespoke, consumer-focused offerings could provide value for customers.
Service levels to customers could be greatly enhanced if they were given open source platforms to hone and perfect their purchasing decisions. More personalized group buying and more responsive CRM could create an even more savvy consumer, utilizing the donated data of peers to make surprisingly clever decisions.
After all this is what history is telling us has already happened. The Big Data capacities of Google, Facebook and Twitter create an enhanced experience. The data serves the user with ever more involving integrated options.
There is, undoubtedly, a race for the Big Data goldmines, but surely one of the winners will be a consumer-centric platform.
As I remind my clients regularly, there are only two forms of media now. On-screen and Off-screen.
Screen based decision activation, by keypad, touch or hands free telephony is the future and the role for Big Data on screens is very clear.
Combining analytical data with unstructured data adds value to people who have declared and stored preferences. Knowing how near or far you are from what you want to buy or do next is a natural step for a generation now peering into their screens for the answers to everything.
Finally it's worth considering how businesses in general will benefit. Certainly to my mind there are obvious bear-traps. Using integrated data to create more lock-in or to push deals relentlessly will turn consumers off.
Again. We know our data is out there. But we put it out there for our own purposes. The instant a brand claims too much insider knowledge without customer benefit, I believe consumers will question the motives.
A recent article in Adage demonstrated that there is a simple distinction in the consumer mind when it comes to how companies use data. Facebook and Google are seen to "own" my data, while Amazon "uses" my data. Consumers perceive Amazon to provide such an invaluable benefit to their lives it doesn't feel as if they are giving up personal data in the traditional sense
It's a balancing act that's been played out for years. We want you to tell us what you have to offer, but we also want choice. Value comes top of the consumer "desire tree"; incessant selling resides at the bottom.
A secondary market will grow soon after big players have invested in the software to garner, integrate and organise the data.
This will be an analytics market, which itself will need sophisticated software systems to begin to re-process and find meaning.
My hunch is that this will validate previous consumer research models that have grown and adapted over time as more information has become available. But importantly it must provide feedback.
While we know a great deal about consumer behaviour and attitudes we still don't know enough about what communication actually works. It's a strange paradox that the more digital we are the less we know about what works and what doesn't.
For example, consumers may or may not see Internet advertising - we only know through click-through metrics. Even if they do click through a recent US survey found that nearly every online American adult (98%) who looks for information online finds reasons to distrust the information they find, including, citing "too many ads" and "self promotional information".
Targeting people more accurately in a way that pleases them more profitably is where the real value of Big Data lies.
Now, who is providing that service out there?