Why is it that we tend not to say much when we’re happy with a commercial transaction, but we can’t communicate enough when we’re disappointed! Take one of my favorite industry analysts/bloggers, Josh Greenbaum, for example. In one of his recent blogs, he roasted a prominent bank as only a scorned author of his caliber could. What does this have to do with analytics? From an enterprise perspective, perhaps nothing. From a cloud perspective, however – everything.
If the bank in question were to mine their call center data, they could no doubt find references to the events described by Josh. Even if other customers logged similar complaints, it’s entirely feasible that these events would be statistically insignificant and thus non-actionable. When you take off the enterprise blinders, however, you might find that these same events look much different in the cloud.
When you run a Google search on the issue, you find the blog ranks four out of two million results – the first three hits are for the bank’s own website. Knowing Josh, this blog is likely just the tip of the iceberg. He’s no doubt tweeted and posted on Facebook about the issue as well. Like his blog, they’re no doubt subscribed to by large audiences. Worst for the bank than the number of people involved in the communications is the fact that these individuals tend to respect Josh’s opinion quite highly.
I could list other ways in which Josh is making the bank pay, however, let’s summarize the overarching challenge and segue to how cloud analytics can help resolve such issues. The combination of social networking and the ubiquitous access to information via the Internet give consumers a much stronger and immediate voice in shaping a company’s brand image. By immediate, I mean there’s virtually zero lag time for edits, courtesy reviews, print publication, and physical distribution. If companies hope to stay ahead of such public relations fiascos, they have no choice but to deploy real real-time analytics.
Real Real-Time Analytics in the Cloud
So what does real real-time analytics look like in the cloud? Well, it starts off with enterprise data, such as customer feedback from your call center. This data is further enriched with feeds from popular social networks like twitter and Facebook. Identifying the data sources, however, is just the beginning. Next, you need to convert the data into meaningful information that can be displayed in a customer service cockpit. Lastly, your customer service representatives need tools for interacting on social networks in order to diffuse such explosive situations as they unfold.
Cloud analytics won’t necessarily stop errors from occurring. However, it can help surface issues early enough to nip them in the bud. At the end of the day, Josh was asking for nothing more.
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