Ah, memories. I remember the late, great Eighties, early in my analyst career, when I had my first brush with what was later known as “groupware.” It was a LAN-based package, “The Coordinator,” from Action Technologies. The architecture of the software wasn’t as important as the linguistic theory on which it was built: the notion that groups cultivate intelligence by structuring their internal conversations to achieve common goals.
Essentially, the package required people to tag every e-mail they sent based on whether it constituted a discussion of possibilities, a request for clarification, or a request for action—and it tracked these threads so that everybody knew the goal-oriented status of every conversation. As you can probably guess, this was a heavy-handed way of getting people to come to agreement. Software shouldn’t dictate how people choose to interact: real-world conversation’s far too complex and convoluted for that. Most people don’t like being forced to rephrase or reconceptualize how they communicate with others. In fact, most of us users simply defaulted to sending messages that discussed open-ended possibilities, rather than engage in a fussy protocol of formal requests and offers.
But that was a long time ago, and collaboration environments have evolved to a new plateau: social networking in all its variegated splendor. All these memories came flooding back to me yesterday while chatting with Attensity, an established vendor of content analytics solutions that can automatically extract the semantics of unstructured text in social networks and other Web 2.0 environments. Attensity can even parse the meaning in the funky “social speak”—in other words, compressed, slangy, and emoticon-laden missives such as “LOL UR GR8 CU L8R”—that constitute how many of us converse in social networks. Though I’m not the biggest fan of this crypto-lingo, it’s good to know that we’re not expected to write English sentences so that they’re optimally machine-grokkable.
We were discussing Attensity’s approach for enabling what it calls the “conversation-driven enterprise.” In this vision, the enterprise implements an infrastucture that automatically monitors, analyzes, correlates, and participates in various internal and external conversations, including social networks such as Twitter and Facebook. It occurred to me that it parallels the notion of an “event-driven enterprise,” with conversations themselves being a sort of complex event that includes lower-level events such as tweets, posts, status updates, instant messages, and the like. And that reminded me of a mnemonic I use to characterize the evolution of enterprise complex event processing environments: from tickstreams (i.e., transaction events such as bids, orders, and trades) to clickstreams (i.e., interaction events such as mouse clicks and page redirects) to tweetstreams (i.e., conversation events such as tweets, re-tweets, replies, and direct messages in Twitter).
And, to close the loop on this thought, that in turn reminded me of the presentation that Natalie Petouhoff and I presented at the last Forrester Business and Technology Forum. Our core thesis was that social networks have the potential to transform customer service by enabling ongoing conversations between customers, service reps, technical support, and other parties. Your customers are spending more time—and venting more of their true feelings—in social networks, so it only makes sense to move customer-facing operations into this brave new world.
That’s exactly the sort of scenario into which some Attensity customers have deployed their solution. Later this year, Natalie and I intend to co-author a Forrester report discussing this vision, presenting case studies, and offering some practical guidance for enterprise managers.
You can learn a lot by tuning into what customers actually tell you, and not turning a deaf ear.