John Caddell's blog

Earlier this week, I posted on ways businesses can monitor what’s being said about them in various social media outlets. Perhaps in a challenge to myself, I promised a follow-up dealing with what businesses can do with this information. Finally, egged on by Amber and David from Radian6, here it is.

Companies are getting good at quickly responding to, and engaging in, conversations that others start about their products. For example, Amber and David quickly submitted thoughtful, interesting comments to my post. Dell is also very responsive, and so is Comcast. Your company should participate in these conversations as these companies do. You should be authentic and respectful and all that. Many social media consultants can help you do this. I am after something else.

Specifically this: it’s time to find useful, actionable patterns out of those gigabytes of chatter–Tweets, blog posts, comments–you’ve collected about your products, company, customer service from all these sources. And while these snippets may not follow a complete story format (i.e., “this happened, then this, then this”) per se, I treat them as stories and recommend using narrative sensemaking approaches to find the patterns.

For customer narratives, companies I’ve worked with have had success in finding deep customer values within these stories, using an exercise called emergent constructs. [Cynthia Kurtz's free e-book Working With Stories has been a critical resource to me.] By values I mean things customers find value in, or don’t find value in (or even find negative value in).

An example: I worked with a B2B online services company to help them determine what their customers valued/didn’t value in the industry segment the company operated in. We collected 50 or so stories from their customers, and ran the emergent constructs exercise with them to find the important customer values therein. They found that customers really liked responsive, personalized service, but didn’t like suppliers who appeared too small. They also didn’t have enough time so they valued time-savers of any kind. Plus they liked a supplier helping make them smarter, in other words extending their capability. They liked low prices, but were concerned that low price might indicate a supplier that wasn’t “industrial strength.”

These values, as you can see, aren’t straightforward to deal with. Anything the company did to enhance one value had some counter-effect. Amplifying a set of values might drive a customer segment away entirely. So they had to make hard decisions about things they were going to do and things they would do away with; customers they’d welcome, and customers they’d turn down. Once these difficult decisions were made, however, executing the plan wasn’t that difficult, and they could do it with confidence, given that they had a deep understanding of how customers really felt, grounded in the actual stories they told.

Sensemaking exercises like creating emergent constructs involve groups of people reading stories, answering questions, collaborating on meanings. Therefore, it’s difficult to do them with thousands or millions of transactions. How then do you narrow down the data? One simple way is to sample. Another way is to allow people who review the customer data to flag those that stand out in some way (perhaps using an Eureka button approach). Either way, gathering a bunch of stories and sending them through this process (see yesterday’s post for more on this) can illuminate very complex and nuanced issues for your company, products and brand, as illustrated above.

And once you have a grip on those, you’re prepared to use your existing decisionmaking processes to do something about them, and make real, vital improvements in your products and services.

Related posts:
Reading Between The Lines of Customer Stories
The Blackberry Storm/Twitter Project