Spencer Geren, my friend and big data evangelist, made a compelling case for the incremental value created by augmenting syndicated data in Consumer Packaged Goods with social web data. In Spencer’s example, social data provides the opportunity to understand the “why” behind the sales and consumption numbers.
As background, Dion Hinchcliffe made a very good baseline case here for the value created by combining big data and social media.
While you can make the argument that this root cause level data is already available via customer surveys, focus groups and other such methods, there are key differentiators that make the pursuit of Spencer’s concept worth the investment. A few differentiators that this strategy provides include:
- Unsolicited vs solicited consumer feedback: unsolicited feedback especially peer-to-peer, gathered via social chatter is more authentic. And, by not forcing answers to specific questions, potentially leads to unexpected yet more valuable insights.
- Timeliness of insights: social data provides a source of more real-time feedback to brands compared to the typical time delay associated with syndicated data alone. Actions taken in that time compressed state can translate into significant sales and market share impact.
- Why is always more actionable than What: As Spencer noted in his piece, social data provides insights on the behaviors and real-time reactions that will drive the consumption numbers in the future.
So, as a customer service guy, I of course look at this issue through that lens. Multi-channel customer service data provides even greater value along those three elements above. Multi-channel customer service data, by definition:
- Is unsolicited
- Is timely
- Provides the insight into customer behavior
The point here is two-fold. First, marketers and market researchers should be tapping into this customer service data as a value added tool in their quest to predict future customer behaviors. Secondly, as I argued in my recent post on Salesforce.com’s blog, customer service as an enterprise function has the opportunity to use social, multi-channel and other big data sets to reinvent itself from traditional reactive processes to a proactive deliverer of customer insights.