Social Analytics and Business Intelligence

Susan Etlinger of the Altimeter Group, Shawn Rogers of Enterprise Management Associates  and John Lovett of Web Analytics Demystified discuss what’s next for social data and business intelligence. 

Social Data Analyst Panel at Big Boulder

Where Does Social Data Live Within an Organization? Where Should It?

Marketing, public relations and communications groups have a firm grip on social data, and they’re holding on tight because other parts of the business enterprise want access to the information. That’s a good (and exciting!) thing. Other departments want this data available to the decision-makers and stakeholders, which could be an indicator of the maturing of the social data environment. Social data becomes really impactful when it resides in other departments. The CFO, for instance, can make data sacred and turn it into metrics that really matter. Social data is starting to actively move into other departments such as customer support, human resources, finance, legal, risk, sales, IT services, operations, market research, etc., because stakeholders are now wanting to understand the implications of that data.

Convergence
Enterprise wants to understand the data, but they don’t know where to start and, even if they did, they don’t know how to communicate the data. Social data firms can help markets understand the social data at hand and the solutions this data can provide (or the problems they can help reveal) in context through a deep technical integration. When we look at data, what are we actually seeing? Data needs to be pervasive through a business. But then we begin to look at unstructured data like images and video — how are businesses supposed to capture and interpret this kind of rich media social data from its consumers? How long should companies hold on to any kind of social data?

We are still counting things: How many Fans/Comments/Likes/RTs? We are still focused on the volume-based metrics and asking the wrong questions about social data. There is a need to think deeply and ask what are outcomes we as businesses are trying to drive on social and work around those. And even that is not enough — you also need to know if it’s effective and energizing your communities.

Where Are The Opportunities for Business Intelligence?
Right now, analytics can determine a brand score and sentiment, but let’s start to tie solutions to better decision-making. For example, when a flight is cancelled, an airline should know that a customer is angrily tweeting about it in real time and should be able to do something about it. Currently customers take to two separate customer experience channels — tweeting about their unhappiness in real time and filing a complaint via the company’s traditional customer service channels later on when the airline can do little to improve that specific experience. There is a big value payoff when companies bring in data to operational workflows that truly drive business. Action goes beyond insight. There could be privacy issues as companies try to stitch together a customer profile based on transactional and social data, but imagine if businesses leveraged and marketed that knowledge?

Drill, Baby, Drill

A holding company for a restaurant chain, through social data platforms, noticed very serious incidences of complaints about the steak quality in a geographical region. By integrating the data of the supply chain with social data from the Twitter stream, the company was able to drill down through the data and pinpoint the problem to a distributor where six shipments of meat had been compromised. If the company had not done this, who knows how long this problem could have gone undetected or if the true issue would have been identified and corrected.

A company that supplies commercial kitchen equipment to restaurant chains was exploring ways to use social data — could a complaint about a meal at Chili’s mean something was amiss with one of their fryers? If you listen to the social signal — a customer complaint or comment — and correlate that to  a location point, can you figure out trends if equipment is having issues, etc.? The company wanted to explore this, and more and more businesses are looking for ways to decipher and decode social data. Current data sets are isolated, and so companies are not always seeing the big picture on their customer’s experiences and possible opportunities to beat out competitors. By incorporating these data streams together, they can understand what happens and how the customer experience is impacted.

Another case: Kraft was using social data to see how consumers liked the taste and flavor of a reformulated salad dressing. But social data was showing that keywords associated with the dressing were “blood” and “thumb.” Turns out, the company had also redone the way the bottled opened, and customers were getting hurt with this new design. Consumers were taking to the social channels to complain, not calling the 1-800 customer service phone number to Kraft. The company, through social data analysis, was able to discover the problem within a few months, and fix the bottle cap design.

Are We There Yet?

Business intelligence has a long way to go in using and understanding social data and its implications. We need to do a better job of understanding and educating people about what exactly these social platforms are used for, how consumers use them, and what value do companies receive by using them, in order to quantify the value to make sense to the C-suite. There is a level of ignorance about the power of these social channels, and some work in better understanding their capabilities, as well as limitations, is needed for the metrics to be more meaningful and insightful.

Industry leaders have explored creating social media standards under the simple objective to better understand social media metrics: What is reach? What is an impression? Define influence. Define engagement. But debate is fierce, as every vendor for data has a different opinion about these definitions, which currently remain too vague. Departments can’t even agree on what a “customer” is defined as, as it means something different to operations than it does to marketing, thanks to differing objectives of each stakeholder. Also, as social media channels evolve, so too does the meaning of a Like or Retweet or Comment, and what that means for businesses. We will need correct ways to talk about the social data and ask scientific questions in ways that are consistent. 

Big Boulder is the world’s first social data conference. Follow along at #BigBoulder, on the blog under Big BoulderBig Boulder on Storify and on Gnip’s Facebook page.

Big Boulder: Social Media Analytics

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.


Social Media Analysts at Big Boulder

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:

  1. Each new product has a new end goal.
  2. 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.

Big Boulder is the world’s first social data conference. Follow along at #BigBoulder, on the blog under Big BoulderBig Boulder on Storify and on Gnip’s Facebook page.