Zach Hofer-Shall of Forrester Research, Susan Etlinger of Altimeter Group, Nathan Gilliatt of Social Target and Shawn Rogers of Enterprise Management Associates discuss emerging trends in analyzing social data.
Chris Moody introduces the group by touching on the widely-felt skepticism regarding available tools for social media monitoring. Susan opens the discussion by talking about the need for deeper customer insight and innovation opportunities in general. Spinning the wheel dependent upon what a company’s needs are, the quality of the solutions varies. Nathan says many people confuse web analytics with social media analytics. You’re measuring traffic in both, but the data doesn’t always overlap. In this sense, there are silos within social media analysis. Falling into the trap of siloing can kill a business because you err on the side of ending up with irrelevant data. Zach admits that he doesn’t know a single company in existence that that can monitor everything in terms of social data. There are new technologies coming out regularly but two problems are presented:
- Each new product has a new end goal.
- A single kind of technology can’t serve a company across departments.
Shawn talks about the necessity of sharing data from application platforms. If you want to connect insight to strategic KPIs for a company or build that insight into work processes outside of the sales departments, there is currently a big level of frustration. Susan says this is all a symptom of the problem with social data today: there are two different markets, publishing and measurement, that are confused by both talkers and listeners. The question isn’t where data should live within in organization, but rather where it shouldn’t. The same post could have countless impacts on a company depending on its inner analyst; the CMO, the lawyer, the customer service head, and so forth. Zach thinks the public relations world has to prioritize crisis management over any kind of data. Susan argues for compassion for professionals in public relations, saying they are often lost in a data world. In many cases, public relations people hold the budget and are the ones that have to problem solve immediately, often while they are not privy to the relevant data.
Theoretically, what if an analyst has all of the time in the world? Observing information over time and switching tools during that process creates a big headache. Flow throughout a predetermined amount of time needs to be understood on a deep level and companies often don’t have the bandwidth to measure things so religiously. As if that wasn’t enough of a hurdle, engagement means different things to different people. For some brands, the time their customer spends on its website is more valuable than a purchase transaction. For others, the reverse is true.
Nathan points out that it’s a tall order for companies to standardize algorithms. Shawn feels the same way and tells us that even when a company manages the difficult task of agreeing on a definition of engagement, it’s up to the vendors and suppliers to empower their early adopters to engage. Zach describes two disparate worlds: social media strategists and community managers often don’t understand data and data people don’t often understand community and social media, yet they are all expected to co-exist in ROI harmony. Susan says a variety of approaches is more politically correct and that marrying a variety of methods can enrich a company across its departments.
The biggest issue we face now is that the analytical steps for reporting are too far apart. Setting up the analysis, measuring the data, communicating it intelligently, and then acting upon the insight in a meaningful way in a short amount of time is incredibly difficult. Simply put, what is determined from the data that becomes actionable and improves the company? The quality of insight is more important than quantity of the data from which it derives. There are two ways to solve problems in 2012: software (the actual tools to measure data) and people (the analysts). To bridge the gap, data tools need to become more intuitive to provide valuable insights and people need to think more critically.