Big Data is only part of the CMO’s new armoury. It’s what you do with that information next that has the biggest impact on the entire customer experience. This is no longer your grandfather’s marketing campaign story.
In order to understand customers better the data collected has to be put into context against their behaviour and then acted upon at the right time, not in real-time and there is a big difference in approach.
Real-time vs Right time
Real-time points to the various inputs and external information received (weather, social media, financial transactions), acting upon a piece of data within moments of receiving it and ignoring other situational influences. Right-time is using that information within the context and situation it was collected from and acting when the appropriate moment presents itself for maximum benefit. It’s less scattergun and more sniper rifle. The trick is still to get away from a batched customer segmentation mentality that current campaigns rely on right now. Without the analytics behind the data collected you just have more information to treat in the same way. That’s pointless.
For example Turkcell created a marketing system to send out offers immediately when customer behavior was detected that was relevant to the offer. With 24 million subscribers analyzed each day against 40,000 trigger events per second and 200+ business rules to correlate them all – locational data, situational information like current shopping habits – they were able to respond with contextual offers, both from their own company and also from retail partners nearby, that were relevant to the consumer at that time. Turkcell achieved a $15m uplift in additional revenue just by switching from traditional batch marketing to right-time methods. Rightly so they won the EMEA Gartner CRM Excellence award in 2012 for this approach.
The data in itself is meaningless, but by pairing the data with the right analysis tools marketing and the customer experience chain can respond in ways never thought possible. Speed is not the key factor, creating consumer relevance is.
And the interplay between Big Data and analytics continues into other areas like fraud detection for example. If you design a marketing campaign that involves a high level of retail transactions from the consumer base you can also tie these into more adaptive fraud strategies that will take these new patterns into account. Hundreds of potential frauds captured, correlated and investigated per day against the context they were made in. Financial losses saved, regulator satisfied, retail reputation protected. Job done.
Big Data is the bullet. Analytics the gun. The impact only happens when you decide to combine the two.
This post first appeared on IT Redux and has been lightly edited.