there really is nothing stopping marketers from a much wider range of businesses gaining access to powerful predictive analytics these days. “Increasingly we had been seeing demand for solutions that are automated, that are intituive and that are easier to use for marketers that don’t have PhDs in statistics and formal training in complex data mining techniques. Genius meets that demand.”
Ball estimates, for the record, that something
in the region of 85% of KXEN users don’t have PhDs or backgrounds in maths or statistics.
THE PURPOSE OF MARKETING Ball has an interesting take too on precisely what it is that marketers are ultimately trying to achieve in 2012.
“I think the goal of what marketers do is fairly
simply really: we are trying to emulate the sort of 1-2-1 insight that owners of mom and pop stores had because they saw their customers face to face every day and got to know every little thing about them.
“As marketers, we are trying to simulate this
and then respond in a timely and efficient fashion to our customers’ precise needs at any given time. That’s where data mining and predictive analytics comes in.” Big data presents the tantalising possibility of
taking a giant step towards achieving that goal outlined by Ball, but it is becoming increasingly clear to more and more marketers that big data presents as many challenges as it does opportunites. “Web-based companies have mountains of granular data,” explains Ball. “They’re very different from traditional physical businesses in that sense. They also tend to have to be very agile and have short product lifecycles. What that means is that they’re looking for tools that can give them answers very, very quickly, virtually in real-time.
“But the problem with webstream data is that it can be enormous. There is usually gargantuan quantities of buried data in there, running to countless rows and columns – and it’s very hard to know what’s useful data and what’s not so useful.”
The other problem issue highlighted by Ball is the skills gap in the industry, one that is affecting virtually every discipline within insight-driven marketing. Automated solutions like Genius help minimise the effects of that gap.
“Genius keeps marketers on the rails when it comes to modeling because all models need to be accurate and robust,” concludes Ball. “It’s not like BI where you can tell how good a model is by looking at it.” n
“As marketers, I think we are basically trying to emulate the sort of 1-2-1 insight that owners of mom and pop stores used to have because they saw their customers face to face every day and got to know every little thing about them.” John Ball, CEO, KXEN
www.dmarket.co.uk
April 2012 29
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