Big Data, Small Data, MyData – Moving from Creepy to Cool

“So I bought this jacket I’d been interested in for a while a couple of weeks ago. With next day shipping I had it quickly and was totally content with my purchase. Then, as per usual, I get back on Google. Day-by-day I noticed the sites I’m browsing advertising the same jacket I just bought. What’s up with that? Don’t they know I just bought this thing? Why would I possibly be interested in buying another?”

This was a conversation I had with a good friend of mine last week. For the purpose of this article, let’s call him James. James works in construction management, is great at his job, is in an incredible relationship and yes, he loves clothes.

But, even though he has all of those amazing things, what James doesn’t know is how the internet is monetised.

How many times have you been involved in or overheard a conversation that describes a similar scenario? If only I had a dollar for every time I had.

In fact, this is the very reason approximately 200m people have installed Adblocking technology on their devices.

The everyday citizen is becoming increasingly fed up with an advertising model that is partially, if not completely broken. This industry, as many of us well know, is driven by large, mostly anonomysed data sets that are used to profile people – at a cohort level – and sell them products the advertiser infers the cohort will be interested in. All of this is based on group of behaviours they seemingly exhibit online.

So as a for instance, I might spend an hour browsing websites I find via Google search using terms such as “core ingredients of red wine.” Google may then infer I am interested in red wine, and likely want to purchase red wine. For the next few days, I notice numerous advertisements for organic red wine by the dozen.

What’s mostly interesting here is that an inference has been made about the purpose of my search. Perhaps it’s inferred that I am a wine drinker, but am also somewhat health conscious. Therefore the offering of a well-priced bio-organic wine might increase my propensity to purchase. In some contexts this could be useful.

However, the actual purpose of my search was that I had a team quiz event coming up the following week, where the primary topic was wine. All I therefore wanted was some general information that put me in a position of slightly higher confidence so that I could perform for my team.

A huge percentage of our digital lives surround tasks where there is zero propensity to engage in a purchasing decision. This shift in behaviour, away from merely transactions to digital ‘life management’, isn’t reflected in the current advertising model.

I explained this to James. He understood, nodded and simply said, “It’s really a bit creepy isn’t it?”

Making an inference from his comment, which was later supported by further conversation, the question James was really asking became quite clear; “What else do these companies know about me?”

Like you and I, James effectively has no control over the way his data is used. Whether it be Facebook, Google, or any other product or online services he engages with, James now feels he is the product.

Is this the best model?

With $7 billion USD wasted every year on advertising only seen by non-human bots, I tend to think the propensity to find a better model is quite high.

When you combine this massive commercial incentive with the upcoming legislative incentive known as the General Data Protection Regulation (GDPR) here in Europe, the search for a new model – something that’s been underway for quite some time – is quickening. And with citizens soon to take control over their personal data, potential answers are also becoming much clearer.

What the above highlights is simple; without context, personal data isn’t at its most useful. This applies to both advertising organisations and the individuals they display their advertising to.

So how do we move from an internet driven solely by big data, to one that is driven also by small data – my data?

Or as we at Meeco put it, how do we move from creepy to cool?

Let me introduce a model Meeco’s CEO, Katryna Dow, developed to help organisations design for shared-value. This model outlines the shared journey towards a new marketplace that is genuinely human-centric.

Creepy-to-cool

As you can see in this model, in order to move from creepy to cool, the trust barrier has to be crossed.

It’s become well known that individuals who have an ability to control their data are far more likely to share it with organsiations they trust when there is a clear exchange of value. Therefore, ‘earn trust by X’ is becoming a viable business strategy through which deeper insight and personalisation for the customer can result in new products, experiences and ancillary revenues for the organisation.

In order to do this, the customer must become a participant in the value chain. By engaging the customer through a B2C + Me2B model, not only do organisations mitigate the risk of GDPR significantly, they also lay the foundation to build new products and person-centric business models.

Both in Europe and Australasia, Meeco Labs is working with leading organisations to prove the value of Me2B models. Because of this, the move from creepy to cool that you, James and I so desperately want, is getting much closer to reality.

Thank you Colin Knowles for the Mannequins Image via Flickr – Public Domain Use

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