We caught up with Deep.Social founder, Pavel Maurus, to discuss the future of influencer marketing and how Deep.Social is striving to become the go-to solution for analytics and influencer marketing.

Deep Social started as Marketplace with strong accent to data insights, but as founder Pavel Maurus remembers: “When we tried to sell it to both Influencers and brands we realised that market is saturated.”

It was time to find what really could make Deep.Social different from everyone else: “we tried to sell our USP – data insights – and secured the first sale within a week. So we realised that instead of keeping it to ourselves and struggling to get influencers and brands on board it’s much easier to make our former competitors stronger by providing them with our audience data insights.”

The platform is probably the most responsive to feedback we have encountered – possibly EVER – which is not just a guess on our part, it is integral part of the platform’s product: “We are committed to deliver 3 new features/improvements each month and I would say 2 out of 3 are coming from our client’s feedback.”

Reason one: Specific Audience Data

Our audience data is more accurate and up-to-date as it is based on real-time uniform sampling of likes for the last 30 days opposed to historical data of followers or one-time sampling of likes when the sample is not representative of 24 time zones, different days of the week and error margin can be more than 50% (I actually saw once 90% error margin in our competitor’s report when an american influencer with 35% audience in the US was identified as having 3% audience in the US).

Secondly, our influencer identification uses our proprietary technology TopicTensor that is very different to Google’s PageRank but at the same time similar as it shows influencers according to their relevance score for a keyword based on analysis of their posts opposed to just a unsorted list of accounts that mention a keyword in their bio. When you base influencer identification on audience data we sort them per segment size i.e. strongest influence on target group opposed to just an unsorted list of accounts falling under certain audience filters.

Reason Two: Post Analytics

Post Analytics with audience insights. They buy it to get insights into the results of their sponsored campaigns as no other company offers audience insights for sponsored campaign posts. Even TV campaign provides audience insights let alone all digital advertising but not influencer marketing until recently.

Reason three: Avoiding Data Overload

When you see 750,000 results found on Google you are not overwhelmed. You just click on as many as you want as they are the most relevant ones. The only reason why people are overwhelmed is that they have to use many tools and many metrics and lots of manual work to get to the bottom of which influencers to use.

With proper technology nobody will care that there are 100,000 influencers matching their search criteria as they will trust TopicTensor like they trust Google PageRank and use just the top results.

I actually think audience of influencers will matter less as paid social will be much more efficient thanks to changes to Instagram algorithms of displaying paid partnership’s posts.

What will matter in the future is finding the most relevant, most authentic influencers.

People who can produce genuine or even viral content that is appealing to brands’ target audiences and can be tested on influencer’s audience and if successful amplified through paid social to all users within brand’s target group.

That’s why the future belongs to influencers who have chosen their niche and produces the best content in this niche and Deep Social will make sure that they are easily identified and found! I can also provide you a glimpse into the future of influencer marketing by revealing a secret link to a visualization of TopicTensor technology.