How to Get Social Media Analytics Wrong

I had a conversation with a large consumer retailer about 18 months ago now that pointed out a pretty obvious fact: There’s a big difference between understanding what happened and why it happened. This point is still largely absent from the conversation around social media. I’m not really sure why this is the case—perhaps it is simply that people who are new to the space too readily confuse initial success with mission success? Maybe a lack of experience results in near-term thinking? Or maybe the hundreds of vendors all clamoring for attention have confused the issue?

Understanding the “what”—what people who use social media are saying—is good. It makes sense as a place to start. But that doesn’t answer the real question. You really need to understand the “why”—why people are saying what they are saying. Don’t confuse the two. Make that mistake and you are going to have explain why you didn’t go through the evaluation process, implementation process, development process, and potentially a nasty one-off integration effort… not an ideal situation. Just imagine your CMO’s voice: “All this time and effort and we still don’t have a handle on the problem?” Not a fun place to be.

Let me give you an example of how this scenario might play out. Let’s say the crowd is saying something negative about your company. Just being aware that they’re saying something negative is a good first step—but knowing this isn’t the real insight you’re after. You want to know why they’re saying it and what you can do about it, and then be able to measure the effectiveness of your response. If you simply listen to what people are saying but don’t have the ability to cross-correlate and analyze the information with what you are doing to prompt the behavior, you are still flying blind. The current focus on the “what” is useful but ultimately limiting.

Understanding why people are saying something about your organization requires cross-correlating everything—including product mix, pricing changes, policy changes, marketing, corporate responsibility, and a whole host of other activities that contribute to consumers’ opinions in the first place. There is a fundamental requirement here—one that too few people are talking about—to combine external and internal information flows in the same analytics pipeline. That is where the real insight happens. However, few (if any) external services that provide social media offerings can do this. Most of the on-premise solutions cannot do this either, since they were designed as single-purpose tools.

One final thought: To understand “why” in social media, you also typically need to understand the “who” element. We’ll cover this intersection of entity analytics and big data in a future article.

What do you think? Have you run into these issues? Which strategies are most effective for revealing the motivations behind what consumers say on social media?