Last week’s post on six degrees of social media monitoring inspired a lot of great comments, especially from some of the folks at the sharp end of the stick who are working for companies like Radian6, Conversition, Trackur and others. I’m pleased that you’ve all connected with this post, because I think you all have a role to play in a much larger endgame. Radian6′s Amber Naslund posted today about connecting the dots between social media engagement and other functions/departments within companies. I think part of the disconnect she addresses–a small part, but a part–is the over-emphasis on the tactical aspects of social media (brand mentions, customer complaints, even sentiment) and not enough on what mining the social web could become. As much as I love “buzz tracking” and “trending topics”, if that is all that the tools are used for, those are the conversations you’ll be part of. Mining what Katie Morse and her colleagues have at Radian6, or what Annie Pettit has at Conversition, Andy Beal at Trackur, or Larry Levy has at Jodange, etc. to show the deeper levels of insight into future products and services possible from truly analyzing the social web will get these conversations started at higher levels within the company.
Amber talks about creating an attitudinal shift within the enterprise, but the leaders in the social media monitoring space have a bigger stake and role to play in making those shifts happen. If you all can show the strategic value of your data–not just in providing a record of the past, but by actually providing insight into the products and services customers might want to buy in the future, you’ll have the CEO herself monitoring her Twitter dashboard every day. The social web, and the newly empowered consumer it has created, will become elevated from marketing channel to part of the very theory of the firm.
Take our biggest research project, for example–my company is the sole provider of exit polling data for the major news networks during U.S. Elections and Primaries. In the short term, our data provides our clients with content–who voted and what issues were important in the decision. In the long run, however, trending all of that data and mining it over time allows us to capture and predict much more profound migrations in the electorate. You all have a similar power–and a similar charge. The trend is your friend–and really mining the migration of the character of social media discussions over time to show the tectonic shift in customer expectations will be the real key to showing everyone in the enterprise that human business has changed, and corporate attitudes have to change just to keep up. So, by all means, keep tracking the Oscars, or SXSW or a thousand other interesting, buzzworthy items (we do!) but also show us what you can do at the 50,000 foot level, where the folks who really need to hear these conversations reside. Those are conversations I’d love to have. So let’s start them here!
{ 4 comments… read them below or add one }
Thanks for a good post Tom! I think you raise a very important point here and I couldn’t agree with you more!
I gotta say, I work for a social media analytics company, so I am a bit biased here, but thought I would share my views on the subject.
We spend a lot of time building intricate search taxonomies for clients, always striving to capture an accurate view of buzz and sentiment, but really, it needs to be an ongoing process. Buzz statistics, trends and sentiment rankings are highly important and obviously valuable for brands that want to learn something about their own position in the social media space, benchmarked against their competitors – but statistics does not provide the actionable insights and real value that deep dives and human analytics can provide. Trends are important, and I think truly mining and understanding the consumer mindset is the only way to actually understand and predict coming trends – or what’s really driving engagement – and what’s causing the shift in consumer attitudes towards brands and products?
I am myself a computer scientist, but I am also a realist and do NOT believe that there is an algorithm or software application that can perform the same level of analysis as humans can today (and probably not for the next 5 to 10 years). But we need tools and algorithms to support us, and to cope with the HUGE amount of data we have available through CGM. There are many great tools out there that provide buzz monitoring (you’ve mentioned a few of them), and they all vary in different ways. The company I work for also provides tools and dashboard solutions for clients, but from my own experience working with clients, the real value lie in the analytics and bespoke reporting – something that none of these tools or applications can currently provide.
Buzz tracking software and solutions are highly important, and any brand that commits to listening should own and USE one of these solutions to listen and interact with their customers! But they also need to take it to the next level. They need to analyze and interpret what their customers are saying about them, and they need to listen to what their competitors’ customers are saying about them!
They need to listen and they need to analyze to make informed decisions and actions! Just as Amber raised in her blog post, the most difficult task is to make them understand the importance of incorporating all this knowledge and insights throughout their value chain!
(Again thanks for a great post, and sorry for the long reply, I got a bit carried away here;))
Hi Tom:
I have to agree with what @Aleksander said above.
We (MotiveQuest) have spend the last 7 years working for the biggest brand owners using SM data mining and analysis to reveal underlying human motivations, issues, drivers and competitive dynamics in everything from cellphones, to automotive, to software, food and pharma.
While brand monitoring gets all the press right now, it is the tip of the virtual iceberg. In most categories brands make up less than 20% of the relevant conversation. If you want to know what drives people, you have to listen to (and understand) the other 80%.
More here:
http://tinyurl.com/yg4ndbv
Tom O’Brien
MotiveQuest LLC
@tomob
Hi Tom -
Well you know I’m with you because we’ve talked about it.
Part of the challenge is that businesses, in many facets, are still a bit caught like deer in the headlights of social media. It’s evidenced by the fact that so many still get thrust into this industry because they’re trying to address an emerging crisis.
And the singular, myopic focus on the trappings of “brand” have taken center stage while we’ve lost brand *intent*, which is to deliver on the things that our customers need and want. The brand is built to drive and support the need, not the other way around.
So part of it is just convincing business that they NEED and WANT these insights in the first place. I want to believe they do, but we as the harbingers of data need to not just assert what we believe to be true of the business shift, but illustrate it in the terms that take *yesterday’s* view, and translate that into a vision of what the future of business on the web might look like. That’s the only way we’re going to be able to meet in the middle, and businesses have to meet the emerging social web halfway for any of this to work.
Thanks for, as always, furthering the discussion. Looking forward to our next chat in person.
Cheers,
Amber
Hi Tom,
I was looking for some articles underlining the importance of human analysis and I came upon this post. What Aleksander said is absolutely right, as well. We would be missing more than half of the information and analysis if we only looked at the ups and downs of certain social media mentions for our clients and not the “real” data; that is, the conversations themselves and how they can be analyzed from the point of view of our clients to ensure that :
1° the conversations are pertinent for our clients (ie we didn’t pick up a post just because the brand’s key word is found in an outbound link on the bottom of the page)
2° the analysis of sentiment and breakdown according to topic is useful for business decisions following our reports (ie “positive” posts are positive from the client’s point of view)
3° the data is broken down into other analyses that our clients can use to identify influencers if they wish, or discover communities talking about their brand of which they were unaware
4° most importantly : our clients are getting the information they were looking for, be it to discover consumer expectations, carry out market research, test a campaign or launch, etc
Great article, in any case Tom and (clearly) much food for thought!
Best,
Michelle @Synthesio