9 Essentials to Measure Brand Equity in the Age of Social Media
Elizabeth (Liz) Breese, is Senior Content and Digital Strategist at Crimson Hexagon, a popular social media analytics and listening tool used by brands and agencies around the world. On this episode, Liz and I discuss 4 out of the 9 Essentials of Online Opinion Monitoring as documented in an e-book published by the Crimson Hexagon team. This e-book introduces the essential components of social data analysis and illustrates the benefits of each aspect. It explains how understanding the nuances of conversation in social media helps brands gain more insight into, and perhaps some measure of control over, how the public perceives their brand.
Liz has a PhD in sociology, which allows her to offer a fascinating perspective on the intersection of human behavior and brand opinion monitoring through the use of algorithm-based technology. Following are four of the nine essentials. You can read about all nine essentials by downloading the e-book here.
1. Social media archive
Focusing on the past, present, and future is a challenging assignment for brands, but one that can pay huge dividends. Access to unlimited historical data is vital for comprehensive opinion monitoring. In social listening, we used to talk about “big data,” which was a handy term to pack a lot of meaning into a couple of short words. Part of what “big data” meant for brands was overwhelming and scary. Now, people don’t talk about “big data” as much. Now, it’s “social data.” As an industry, we have come a long way in how data are shared, ingested, collected, stored, and indexed.
That means that brands and their creative agencies can expect more from their data and analytics providers, in terms of historical data as well as on-demand queries of both owned and earned data. Social analytics technology that limits your queries or your access to data in some way, limits the historical benchmarking and competitive analysis that brands need to do from the social media archive.
2. Filter out the noise
When measuring brand opinion online, it is necessary to filter out irrelevant data because its inclusion can minimize and obscure important trends, warnings, and opportunities. With irrelevant data removed from the data set, you can extract accurate insights from the remaining relevant data. If you are Victoria’s Secrets’ agency doing reporting on the “Pink” apparel line, you want to filter out conversations about the color pink. Or if you are Chipotle, and you want to monitor conversation about your restaurant, you want to filter out conversations about the popular spice by the same name. You need social analytics technologies that filter out the noise, keep the signal, and do both without long Boolean strings that will probably leave out some of the organic ways that people talk about a brand.
3. Get to know your audience
In addition to learning about the demographic composition of the audience, a brand should also want to learn about their audience’s interests. Insights gained from consumer affinities can inform campaign strategies, allowing a brand to determine if they are targeting the right audience and how they may build future relationships with potential partners or sponsors.
Marketers – and here Liz is referring especially to content marketers and people who are planning advertising campaigns – know that their message needs to be welcome to their audience, not received as an interruption.
With Facebook’s newsfeed algorithm, a brand can’t count on everyone who has “liked” their page to see their message. A brand needs to design and write content their audience will genuinely care about. That mindset is true across the spectrum of digital channels that can reach your audience.
Brands evaluating social listening tools to help monitor social media brand sentiment need to consider if audience analysis and influencer analysis is available, and how deep does the information go in assessing audience interests.
A brand’s audience is producing potentially millions of signals every day on social networks about what they care about. With social listening technology social media data can stand alongside traditional research methods like focus groups to measure opinions and sentiment.
4. Skip the snapshot—get the motion picture
Conducting comprehensive opinion analysis that connects the past, present, and future allows a brand to create strategies that incorporate customers’ changing opinions and needs as well as their feelings toward competitors and the industry at large. This connects back to the first “essential” about access to data in the social media archive. A brand can and should learn from past, connect to the present and understand the potential future to design advertising campaigns and content strategies that meet the needs of the brand’s audience.
Social listening technology that is robust and easy to use provides a brand the big picture as well as granular data. Seeing the change in motion, rather than just discrete snapshots along the way, empowers brands to understand the entirety of their brand’s perception and enables more effective decision making.
Liz’ response to my “one thing” question is one that (not surprisingly) is probably (at least in part) motivated by her academic pedigree. Liz wants to see the industry improve the terminology we use in the business community so that we are more specific in the use of words to reduce confusion and inefficiencies.