«Relevance» has become paramount in todays› marketplace. Simple customer segmentation is no longer good enough in the online channel. People are more demanding and web savvy than that these days. So how can Big Data help generate leads?
Michael Mokhberi of Apptus at the EASDP 2013 in Amsterdam.
Customers move, change habits, etc. When a woman becomes a mother her needs change dramatically. What used to be a good match yesterday may be very well irrelevant today!
Behavioural merchandising on websites is about creating a compelling and relevant user experience.
Data points today include what people currently do, i.e. click.
But customers make choices all the time, really, hence we should also measure what the user didn’t click!
This enhances the universe of actions with a universe of non-actions. The latter can sometimes target a customer even more precisely than the actual clicks.
About 60% of all sales come from the top sellers (top 10% of the product range).
But the average margins are 40% higher for products in the long tail as opposed to top sellers.
Therefore online sellers try growing their offering in order to sell via long tail and its higher margins.
Behavioural data today is used in real time in order to improve the bottom line. Therefore it’s crucial to understand the customer’s business, needs, data, vertical, taxonomy and content.
Big data is not about the size but what you actually do with it!
Sensis, an Apptus customer, improved their profile page creation service by 400%! Directory entries live on being comprehensive and accurate.
The best way to innovate is to experiment…
Super Summary. Thanks. But I kind of wondered when I read this quote:
«Big data is not about the size but what you actually do with it!»
That is a rather interesting definition of the term. As most people understand big data, it has two components or dimensions, namely:
1 – Volume – how fast are these data being produced, AND
2 – Access / Request for Info – how many requests for data per second or minute…
So what Michael Mokhberi seems to refer to is maybe the challenge of having data that one cannot use (is it useful or just garbage)?
I believe we need to stop waiting to leverage our data.
Instead, we need to ask ourselves what can be done with those data we already have, in the format they are in right now!
Thanks Walter for sharing these insights.
===> Urs @ComMetrics
I guess it’s useless to produce high volumes of data and access/request it quickly as long as you don’t have a concept on action you will take depending on the data. Probably that’s the first thing you want to think about: what knowledge do you want to extract from the data in order to rise the relevance of your offering?
E.g. I would not have guessed that the interesting margin is in the long tail and not with the top sellers…