How real is real-time offline advertising?

Real time advertising is a hot topic right now. Over the last few months I’ve read a growing number of articles about how advertisers will soon be able to target their customers in real-time. Of course real-time advertising is nothing new online, what’s new here is the possibility of being able to do it in our offline lives as well. Just this last week Tesco was in the news. It has been testing the use of facial recognition systems to target interactive poster advertising based on gender. It seems we’re not a million miles away from the kind of personally adapting, real-time billboards which are the staple of sci-fi movies such as Minority Report.

I was struck by this coverage because of my interest in predictive analytics. For such systems to work would require numerous different technologies to work together but predictive analytics would have to be central. It is predictive analytics that delivers the customer insight needed at the heart of this type of advertising, for it to work well.  If companies don’t know and understand their customers in an intelligent way then real-time ‘targeted’ advertising could be disastrous, triggering customer backlash that would do real harm to a business’s brand and in short order its financial position. 

So, real-time offline advertising requires a whole range of technologies to work together – facial recognition, RFID, automated content delivery over distributed networks and so on. On top of this is the need for the whole system to be based on solid customer intelligence. Where will this come from? Balanced and intelligent customer insight must be developed through the serious application of predictive analytics, which can then use relevant data to support intelligent real-time content recommendations. The predictions, propensities and recommendations derived from the analytical processes must then be governed by established business rules that take into account issues such as compliance and privacy.

Without this customer intelligence then the risk is of a scenario something like this: “I recognise you and now I am going to offer you the same thing I offered you last time…and the time before that…and the time before that.” You get the idea. And this kind of situation is already common in the online world. You click through to a company’s website, or fill a shopping basket but don’t check out, or search for a particular company on Google. You then find that ads for that company ‘stalk’ you around the internet, regardless of whether you’ve actually bought the product or not. Such online systems are rarely sufficiently ‘joined up’ to be able to track interactions through multiple channels and really understand whether it’s appropriate or necessary to advertise more to a particular customer or not.  

Now we run the risk of this scenario being lived out again in the offline world. Never mind privacy invasion. If I was responsible for the marketing of a significant consumer brand, I’d be more concerned about looking dumb and insulting my hard-won customers with irrelevant and annoying messages.

The reality is that most businesses need to focus on using the data they have about their customers already (which is often much more than they realise) in an intelligent and co-ordinated way, through their existing channels of communication, before getting too carried away with the promise of real-time personalised advertising on the Underground, at the airport or in their shop window displays.

Our significant experience from working with our own clients tells us that companies can realise a great deal of, much lower risk, opportunity delivered from data driven customer insight.  This will not only help their financial bottom line, if applied intelligently it will always improve the customer experience and brand perception. Investments made now in well-executed predictive analytics will serve businesses well when an integrated and reliable platform for personalised, real-time, offline advertising is a reality.

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