The problem with the new dark coffee mugs in the office is that we used to have white ones. Thus, what used to be a known– the stains, has became a known unknown: a dark mug hiding the stains within. Gives me pause every time I use them- I know something’s there, I just don’t know how bad it is. Humor me for a second and see how I’m like a proverbial client in a non-customer-centric organization: I know my customers are complaining, but I don’t know exactly what they’re saying, or how much better my product could fit their needs.
Listening (née social media monitoring) used to be a means to uncover known unknowns like this– predictable sets of things known to be possible.
The future of listening was the promise of evolving to unknown unknowns– things we didn’t even know could be out there. For example, the prospect of happening upon unexpected audiences (i.e. Dads?) talking about your product being used in unintended ways (i.e. eye cream for cellulite!).
Six years of listening has turned up hundreds to thousands of those kinds of anecdotes, yet still there is no precise science to uncover unknown unknowns. We still somewhat systematically rely on a backbone of metrics such as discussion volume, sentiment, and topics. Sometimes we try to identify “influence,” although there is no agreed upon algorithm to capture “influencers.” There is also no clear winner/best of breed technology with 100% accurate sentiment mining or topics analysis.
I think it’s time for us to agree that isn’t the future of listening. Technology will not get to the point where we can algorithmically detect weak signals in real (enough) time to prevent crises or perfect product development– much more than we can today.
The future of listening will transcend technological advancements. The future of listening– the near future– is making it work in an organization. Operationalizing listening as a standard business process. The future is a flow chart that integrates people (e.g. customer service, product), process (e.g. escalation, resolution), and technology (e.g. from listening to CRM) and disseminates results to a wider group of stakeholders.
I don’t think the fundamental challenges of listening have been solved; and, don’t want to encourage stagnation. We should forever challenge ourselves to better understand the complexities of language via semantic analysis and capture and classify new types of data (e.g. check-ins, metadata), but we should go ahead and make listening part of everyone’s daily life without waiting for perfect technology and standardized metrics.
That is the future. Serve the coffee in the potentially stained mugs. People need their caffeine to function.
Photo credit: cudmore on Flickr
Interesting take on the idea, Kate. I also agree that listening will need to go far beyond just tracking mentions if we really know what is going on in the social media world.
Cheers,
Sheldon, community manager for Sysomos
Thanks, Sheldon – By the way, I’m eager to hear more about your international coverage and how you’ve created that data set, speaking of challenges in social media…
Completely agree – except to say I’d like to think this is less the future and more the way we approach our social media monitoring for clients right now. Getting the right data to the right people in the org makes the best use of that data – turns it into action
I’d like to think that too, David, but the reality of it is very few organizations have an established enough process where listening data is effectively disseminated and/or escalated at the scale of other streams of more traditional data or to the point where it informs business decisions. Glad you agree though– perhaps with more established processes, we can shift the focus back to perfecting the technology!
Hi Kate,
We’re working on the listening tool changing cultural norms at our end. This includes a structured event flow with dialogue states that touches on some of the “business verb” activity feeds I wrote about a while ago. Nice to finally put that on screen and actually click/type. Chat to you about this soon, in a couple of weeks
I agree, the algorithmic approaches can never replace our unquantifiable human sense. “What should I listen to?” is possibly an intractable question – just like it is in real-life.
Kate,
It is true that competitive advantage is not going to come from the ‘listening platforms’ but from how and what firms do with the information collected from it. In regards to this, I feel there is an important piece of puzzle you left out – analytics (it is possible you have it merged with ‘technology’ in the people-process-technology framework).
While state-of-the-art technology and tools are great, I think a firm needs to ramp up their analytic maturity to ensure they get the full benefit from their listening posts – from social channels to customer service to retail. In other words, I do believe that advanced analytics will play a key role in the future of listening.
Regards,
Ned
You are correct, Ned – huge opportunity for advanced analytics, as validated in their tie to objective outcomes and accurate capture of meaningful constructs.
That reminds me of a session I had with IBM in their Hursley Labs a year or two ago where they were showing a product that was specifically looking into why certain things DID NOT happen. In general, rule engines and the likes are trying to recognise patterns and then execute certain actions upon detection, but it’s far more interesting to try to “identify patterns that are not there” or when certain events are not following patterns.
I wonder whether we can apply the same thinking here?
You have innovation prediction thought frameworks like TRIZ where they have categorised every single problem in the world in like 40 something categories I think. Once you can reduce a problem to one of the problem domains (with accompanying solution) then it should be fairly easy to predict the next innovation in that area. Think about needles. Almost everything that you can innovate has been innovated in that area, so years ago one US firm I think stopped trying to innovate the needle and took a step back and realised that the root problem they are trying to solve is not producing needles, but injecting certain medication into someone’s body. Once you reduce the problem to that, then you can think about devices that inject medication in your body by using high pressure instead of needles.
So you think that it’s possible to come up with a certain set of “un-patterns” (don’t know any better word for this
) in certain domains and try to look especially for that?
Seems like there’s a generation of software to be had before we call it quits on listening platforms altogether. That, instead of relying on a single person to run through thousands of tweets/statuses/etc, takes advantage of the crowd to do so.
Now, operationalizing that will result in millions of sensors being added to your internal network. That’s the future of listening.
Here’s what got me thinking about this: http://smallwarsjournal.com/blog/2010/11/i-came-across-the-following/