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How DemandJump is analyzing content to discover social influencers

by Brennan Walker, on July 5, 2016

In this week’s video Tyler explains how we’re going about identifying relevant social influencers for content.


In a McKinsey study focused on the impact of social influencers they found that social recommendations had an impact on 26% of sales across the board. From that 26%, ⅔ of the purchases were directly from social while the other ⅓ influenced a purchase at some point along the decision making process.  

More so, this study found that between two product groups there was very low overlap in influencers (15% at maximum).  Therefore, it is crucial to find the right influencers for each of your product or service.  

Social Influencers are playing an ever growing role in the decision making process, and using the right influencers is key.

In this video Tyler explains exactly how we’re doing social influencers, and how it can give you an edge.  

As Tyler explains our focus on influencers is tied to creating content.  Using a semantic content graph that is constantly refreshed paired with a network of influencers that are tweeting content allows us to see what content is best for you, and how influencers are connected to that content based on topics they are most strongly associated with.

This goes beyond just seeing what an influencers has done in the past, and actively puts them within a network to see what influencers are best for certain content.  

If you’re interested in watching more of our videos you can check out our YouTube Channel here.  

Topics:Data ScienceMarketing AnalyticsSocial Media Marketing

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