Social Listening 3.0

Jonathan Farb, Chief Product Officer at ListenFirst Media, gave the second “Pecha Kucha” presentation of the day on Social Listening 3.0. To review, Pecha Kucha is a Japanese presentation style that focuses on the spirit of efficiency by having the narrator speak on exactly 20 slides, each of which is shown for only 20 seconds (6 minutes and 40 seconds in total).

Jon 1

Jon started out by saying that if you were to ask everyone in the room to define social listening, you would get a large number of different answers, including:

  • Sentiment
  • Positive/negative/neutral
  • Consumer reaction
  • Social media data
  • Forums

Jonathan asserted that “we sell social listening to tap into the world’s largest focus group” to understand what they’re doing, what they are saying, what they want to buy.

Up until recently, social listening has primarily focused on computers analyzing text. In the beginning, we had forums, BBSes, message boards, and similar tools. Social Listening 2.0 was able to structure conversation and topics in a way that supported enhanced analysis capabilities, such as measuring the volume, extracting the sentiment, and performing other text processing.

Then social listening changed again by adding “clicks,” such as clicking on icons to follow, like, or Retweet. It became immediately clear that not everyone was a content author and that some users liked to click. A lot. Tracking clicks allowed us to shift from the qualitative to quantitative and to analyze what someone was saying without them actually
having to say it.

The premise of Social Listening 3.0 is that conversation is not the entire story. If you are still evaluating the value of your brand based on text only, you are under-monetizing other engagements available to you. Not taking advantage of clicks (the rest of the story) is a real problem.

After conducting research with their clients, Jonathan’s firm found that less than 50% of fans actually post content. On the other hand, 100% of social media users click, providing valuable information that can be leveraged for ad strategies. For example, of 4.58MM digital engagements, 80% of the monetizable data for The Walking Dead was not analyzed.

You can also glean more insights than when analyzing clicks than what users actually type out and apply the insights to do optimization and competitive intelligence better. For example, Tesla is one of the lowest conversed brands on the Internet, but always in the top 5% with fan engagements.

The uptake is that if you’re still using conversation analysis as the only method for moving millions of dollars around, you’re obviously not getting the full story.

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