By now, most companies have pretty good controls on internal data and information. They gather sales statistics, inventory levels, and customer data, and can sometimes even draw conclusions based on these with advanced analytical tools. As a result, many of the decisions that managers make are based on internal data. But internal data contains only half of the truth. An enormous amount of data actually resides outside of the four walls of a company. One example of external data is everything that is written by customers in social media about the company.
A somewhat classic example is a tweet that was posted toward the end of 2016 by a disgruntled Tesla owner. The person was not dissatisfied with their electric car per se, but perceived a structural problem in that many Tesla owners used charging stations as parking spots despite their car being fully charged. Tesla’s CEO, Elon Musk, responded quickly and said that the problem would be solved. Six days later Tesla introduced a fee for cars that remained parked at charging stations after they were fully charged. But the fact is that Tesla could have discovered this problem even more quickly by monitoring and analyzing the stream on Twitter, where many people had previously commented on this in different ways.
The term social listening hints at the fact that one tries, in a structured way, to analyze what is being written about a certain company on social media. By following social networks like Twitter, Facebook or LinkedIn, one can get deeper insights into customers’ problems, expectations and wishes related to the company’s products and services. It is not primarily about answering customers’ questions and complaints, but instead about performing a deeper analysis in order to discover new possibilities and to understand the big picture behind all of the conversations.
Social media is not a media – The key is to listen, engage and build relationships. | David Alston, marketing entrepreneur
Social listening is used by, among others, the company Merck, which manufactures picture screens and displays for cellphones.1 As a B2B company, they lacked direct contact with end-users, which made it difficult for them to get feedback on their products. Even if they managed the demands of the cellphone manufacturers well, they wanted to better understand which characteristics of a cellphone display increased customer satisfaction. With the help of social listening, they were able to identify different keywords that people used when they described a cellphone positively. By analyzing blogs and various social media they realized that what made the greatest impression with respect to quality was the resolution of the screen. With these newly-gained insights they decided to invest more in product development that improved the display’s performance in just that way.
The company FitBit, which manufactures health bracelets, has, via social listening, discovered many alternative uses for their products that they weren’t aware of previously. For example, their health bracelet is used in clinical studies, to capture criminals, and as evidence in trials. Discoveries like these have given them both new ideas for product development and the possibility to create interest-raising press releases.
There is an abundance of tools for working with social listening, such as Talkwalker, Sentione, Falcon, and dozens more. They are often good at slightly different things, so many companies use multiple analysis tools in parallel. In practice, these tools can analyze conversations in selected social media based on specific topics, keywords, phrases, brands or industries. Based on this data one can then create a picture of the status of one’s brand, get ideas for campaigns, or improve customer experience.
A central part of social listening is so-called sentiment analysis. It involves using smart algorithms to try to discover if a general tone is positive or negative. Neutral comments are not interesting; what one wants to differentiate is posts where strong opinions are expressed. When customers are angry, upset or for that matter impressed or overwhelmed, one wants to aggregate these emotional outbursts and see if they can be tied to specific events, product launches or statements. Sentiment analysis involves discovering concerns at an early stage, before problems escalate, as well as the possibility to lap up praise and understand when and why customers are satisfied. It is about automatically extracting the essence of customers’ current frame of mind.
Social listening is not something that can be quickly applied in the event of a crisis, but rather something that is intended to be used continuously over a long period of time. In this way, one can follow historical data about how opinions about a brand change. One can discover seasonal variations, responses to product launches and other trends. Deep analysis is used to understand why the discussion looks the way it does. The sooner one discovers changes, the easier it is to directly address negative criticism, as well as quickly capitalizing on the positive. By interpreting these external signals, the possibility of making well-informed decisions and remaining one step ahead of the competition increases.
1 Roberts, P. (2018). Social listening case studies – three brands who nailed it. Downloaded 2018-10-22 from https://oursocialtimes.com/social-listening-case-studies/