Let's start from the assumption that we want to help others "do what they already want to do" - for it usually results in a "thank you" or maybe, a purchase. There’s the hotel concierge, for example, who books a guest's favourite restaurant in advance of their arrival or the site that remembers your preferences and makes it easy for you to buy the same items again.
The challenge in helping someone "do what they already want to do" is that it assumes that we already "know" what that person wants to do, and for the most part, we don't. For all our effort, marketing and advertising tends to operate in a sub- optimal world of simple demographics, ratings, static CRM systems and short lived cookies.
What we do know (or can sense) is that the data holds the key. But prizing the value out of the data in a useable, simple and scalable enough form is a whole new challenge. One where increasingly digital pioneers are turning to a new genre of big data and predictive analytics companies offering machine learning and semantic analysis to help find the patterns or clusters that turn this data into gold.
It is a challenging problem - most of what people say (particularly on social networks and call centres) is captured as text, which means that computers need to interpret the meaning of the text correctly. Did they mean ‘house’ as in ‘home’, the TV showor the genre of music? Given the ambiguity of language this is an immensely difficult problem, but surprisingly a few of these companies are achieving accuracy in excess of 85%.
Assuming a machine understands the meaning correctly, the next problem is in knowing how you "as a person" value it.Simplistically soccer and the World Cup might mean everything to you but little to me. Solving this requires two maps (technically graphs) - a map of how everything in the world relates to everything else (an ontology) and second, a map of how each person values everything in that map (an individual interest fingerprint).
Understanding how each person values the things in their lives means marketers can increase performance by hundreds of percent and spend far less. For the first time, it's possible to understand a person’s core interests and affinities in detail as context changes (perfect for brand marketers) as well as quantifying what they want to do "right now" as they land on your sites (perfect for direct response).
Marketers can use this data to personalise an individual consumer’s messages, content or experiences, or they can use this data in aggregate,finding and understanding the natural (and often hidden) clusters in the data; the places where similar behaviours and tastes co-exist. These clusters can then be used in multiple ways, reducing churn or finding the right prospecting parameters.
In essence it's a new way of media planning, targeting and personalisation - providing the foresight, if you like on what consumers want to do next.
The tech titans of this world - Google, Facebook and so forth are on the path to reaching this understanding. Now the technology is available for a new wave of digital pioneers to get to this point – and make the vital leap from customer management to customer intelligence.
Helping others "do what they already want to do" is, for the first time, a real possibility.
By Jonathan Lakin, CEO of Intent HQ.
PrivSec Conferences will bring together leading speakers and experts from privacy and security to deliver compelling content via solo presentations, panel discussions, debates, roundtables and workshops.
For more information on upcoming events, visit the website.
comments powered by Disqus