Thursday, May 19, 2011

Corporate Knowledge Management Applied to Online Customer Engagement

There’s certainly no shortage of stories regarding customer engagement and social media interactivity by many businesses on the Internet, especially when responding to negative feedback and proactively shaping the amplified, echo-chamber public dialogue that follows.

PR and marketing staff may be tuned to trending commentary through "social listening" tools, search engine alerts and direct monitoring of inbound call center or emailed sentiment. However, especially with businesses that sell quite sophisticated or complex goods and services, it can be really difficult to find and assign – quickly - the right SMEs to evaluate and help respond to quickly growing community sentiment or complaints. SMEs who not only explicitly understand the product, but who also may have valuable, tacit understanding of the intersecting contexts – i.e. how the product's being used, the nature of the user community, and perhaps some knowledge of implicit product use guidelines (that don't show up in the instruction manual).

How can this be addressed? On the one hand, the situation calls for some kind of "expertise management" capability, where SMEs around the company are routinely, digitally profiled via categorized knowledge, and this information is available real-time via search or faceted navigation. Or maybe Hal knows, down in the IT Department – so just call him.

On the other hand, it's only a sharp and informed social Tweeter that can separate the bottom-line concerns and issues from the noise and opinion, and classify the conversation for the organization in a way that enables the most effective response and applied corporate intellect. In other words, to engage the public community in the most contextually relevant and accurate way – thereby shortening the "hype cycle", diluting the angst, solving the right problem.

So the customer relationship Tweeter or Blogger needs to quickly package and convey the right query to the most appropriate SME, to help elicit the best response. Implementation of a few knowledge management concepts can help. For example, within your company, perhaps information is being "semantically tagged" - identified with additional contextual value by pre-defined taxonomies of terms associated via file metadata or a content tagging index. As the information gets tagged (not only documents, but expertise profiles, conversations, multimedia), it would probably be very useful to enable tagging not only according to pre-defined corporate taxonomies, but also in free-form (i.e. building an organic folksonomy). As well, tagging should be encouraged for "dialogue instances" – i.e. blog entries and comments, bulletin board entries, intranet or wiki page updates, etc.

For the Tweeter searching for internal SMEs, this may result in a much closer match between the external issue topic and the internal expertise, because the lexicon is more semantically accurate or inclusive. A search within the standard corporate repository for "customer software release X defects" might turn up testing parameters or results from the software development lifecycle (keying off the standard terms "software", "release" and "defects"), but a search for "the stupid XX page loses my address when I hit the recalculate button" (per the complainant) might just turn up some salient internal dialogue and references among developers about this particular "feature" (or similar ones), keying off the user-supplied tags "recalculate", "button", "address" and "XX page". Maybe even "stupid", as a signal emanating from a commonly problematic area.

The unstructured dialogue instances are also bound to be easier to interpret and verify (since real experts are involved), as to whether the issue smells like a widespread problem, or it's a short-lived, one-time issue. As well, additional material may be identified that’s easy to consume and understand by customers, adding up to support for an online customer and community engagement process that's more helpful and credible.

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