Keeping the person in personalisation

How successfully has personalisation been leveraged to deliver better experiences for people (and therefore better results for brands)?

We're all familiar with a CMS that can surface content based on previous browsing behaviour, dynamic advertising using data management platforms to determine what creative to show to whom, and eCommerce pricing that adapts to what a user is likely to be prepared to pay.

So we know this stuff exists. But, I'd suggest that - even several years since the dawning of personalisation - we remain a long way short of harnessing its full potential.

Why is this? Personalisation arrived making some weighty promises. A series of out of the box technologies boasted the capability to deliver highly tailored content to users via automation. All we had to do was build the content, install the product, and watch personalisation in action. Whilst the potential of such solutions cannot be doubted, their arrival resulted in many relegating themselves to the role of passive observers; we allowed one of the core elements of effective communication to be outsourced to algorithms.

In many cases the need for scale dictates the need for technology. There is, of course, a crucial role for algorithms, automation and machine learning within personalisation. But we must never lose sight of the importance of our role. Considered human involvement ensures that the person in personalisation is always centre stage.

The need to take advantage of machines alongside the intuition and human touch of people is something that Spotify have done with great success. Gustav Soderstrom, Chief R&D Officer at Spotify, has coined the term ‘Algotorial’, citing it as a key element within the platform’s highly successful Discover Weekly service.

Algotorial is where an algorithm meets editorial. The masses of data collected and interpreted by an algorithm is analysed and refined by curators, music experts and genre specialists. As such, as well as relying on machines to apply logic based on data, recommendations delivered to users have had the considerable benefit of a highly knowledgeable and very human contribution.

The use of an algotorial approach ensures that audiences’ needs, preferences and dislikes are thoughtfully considered. Human involvement ensures that the product benefits from inputs that are the hardest to replicate via algorithms: intuition, instinct, emotion.

Spotify’s Discover Weekly stands as a great example of how, in an age of increasing roles for algorithms and machines, it will be those brands who determine how best to combine human and artificial intelligence to generate benefit who will increasingly come out on top. Brands must avoid the temptation to rely solely on technology in the pursuit of high-quality personalisation at scale; in doing so the personal touch is preserved, and the quality of customer experience is increased.