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Social Listening For Predictive Insights

Social Listening For Predictive Insights

The 47th FIBEP World Media Intelligence Congress is happening at the end of the month and for this occasion, FIBEP MarComm Expert and Founder of Talkwalker shares his views on industry topics such as predictive analytics and the status of social listening.

1. Talkwalker is now able to monitor and analyse not only social media data, but also print and broadcast data. How do brands benefit from your integrated platform?

We empower brands and agencies to make data-driven decisions which result in increased productivity and profit. With Talkwalker, companies benefit from an all-in-one social data intelligence solution for all their social media monitoring, analytics and reporting needs that has the flexibility to integrate with other data systems. The fact that you can combine data pulled from social networks and online channels with data from offline channels and even TV broadcasts means that companies don’t need to worry about data integrity as all the data is from one centralized platform. This also makes the technology scalable so enterprises can use it across multiple departments.

2. What is the difference between monitoring and listening?

Monitoring is the first step of a listening program. Monitoring gets you results and counts basic stats such as buzz volume, sentiment and share of voice. With listening you take results from monitoring and dig deeper to understand the individual comments, influencers and overall themes that are driving results. Monitoring can give you some broad baseline statistics but it’s with listening that you can give these numbers more context which ultimately makes your insights more actionable.

3. How do you identify the content that matters?

There are several ways to identify the content that matters using social media analytics. The simplest way is probably to sort posts by the amount of engagement they’ve received i.e. total numbers of retweets, Facebook shares/likes, Instagram comments. But beyond this you can also see whether content has been shared or posted by key industry influencers, use theme clouds to determine the top topics linked to particular industry trends, and even determine trending topics in particular regions using geolocation. Which method you use really depends on what you’re looking for but for most industries you’ll want to use a combination.

4. Is predictive analytics the next piece of social media monitoring?

I think we are already seeing some examples of social data being used for predictive analytics. Social media analytics can give insight into purchase intent for products and advanced sentiment analysis can help to predict stock fluctuations. The key here I think is to combine social insights with other data. With so much data out there from so many different sources, companies need to intelligently integrate these different forms of data if they want to be predictive. This is of course a difficult task but if done well, the results could be very actionable.