Home > Method, Monitoring, Observations, Product, social, Software > Datanetis – highly scalable solution for finding influencers mathematically

Datanetis – highly scalable solution for finding influencers mathematically

  I recently noticed on LinkedIn that one of my old friend is now the CEO and founder of a new start-up company named Datanetis. I sent him an email because I was intrigue and it was also a good opportunity to catch up.  Elery Pfeffer and I worked together few years ago in a small start-up called Nester Software (later the name changed to Plataine) he was a student back then and I was thinking about moving to America. He is one of the brightest people I ever met.  Elery graduated from Tel-Aviv university in computer science and in a country with so many bright people and very few universities, it is as hard to become a student in Tel-Aviv university as it is in one of the Ivy League education institutions over here. Yet the thing that makes Elery a great friend is his strong integrity and generosity. Later he become the President of Nester, I made it to the state and we kept the friendship and mutual respect going.

Elery was kind enough to spend an hour with me over the phone and through GoToMeeting session he presented his new creation. Now, I was even more excited. Datanetis is the real thing! It is not another dot com web2.0 bubble company. The company has a real product with multiple patent pending applications describing algorithms for finding influencers, highly complex (real barriers to entry), and scalable. Datanetis is selling it to the enterprise as a hosted solution and providing new data about whom should the bushiness focus his best marketing effort on – leads to influencer on other leads. And they already have large customers around the world.

Elery view of the new marketing is revolutionary.

“The new marketing is not just about customer’s monetary value but also about the customer’s social value to the organization.”

For someone that has been working building software for the marketing automation industry over 8 years now and is familiar with multiple solutions for finding the right prospect out of many, it was an eye opener. I’m evidencing the progression from mass email campaigns through marketing to target individuals with a matching/relevant offers (data mining, behavioral pattern, collaborate filtering, recommendation engines) to finding customers that can market for you – agents.

Finding subtle connections between individual and causality.

Followers buy only in networks where influencers buy first

Quoting Harvard Business Review:

“The only path to profitability growth may lie in a company’s ability to get its loyal customers to become, in effect, its marketing department”

So who are these loyal customers?

Datanetis’s software is capable of both automatically generating social networks from low level CRM data within the customer database and to mathematically identify influencers and followers. This information could be used to increase the return on every marketing dollar spent on new product adoption(x5-x70), new customers acquisition(x12), churn prevention (x10-x30), conversion, product cross sell(x6), higher product virality, and significant cost reduction.

From Datanetis’s experience, social network marketing using influencers is comprised of two cycles. The first is the closed friends cycle, from the results it seems as if they almost decide simultaneously to follow the leader. This first wave peaks around 4-5 weeks from the beginning of the campaign. The second wave peaks around 9-10 weeks traversing through the rest of the social sphere. This may indicate that the customers are going through different decision making processes at different locations on the social network graph (influencers affinity). This knowledge offers Datanetis customers ways to fine tune their campaigns over time.

In my opinion this disruptive technology will force changing some of the operations and thinking in the marketing department going forward.

Viral marketing is not just hit and run but a multiple acts campaign.

Another interesting finding that Elery shared with me is the lack of influencers trivial characteristics. Any attempt, so far, trying to map influencers based on demographic, product adoption or any other factor distinguishing them from the population failed.

This is what Datanetis found about these individuals only after finding them using their software:

  • Social Influencers are not celebrities and resellers
  • Influencers typically
    • represent 7-15% of the total population
    • has influence in 3-5 different subject areas

Datanetis successfully executed hundreds of large scale social marketing campaigns and is globally active in Retail, Telco, Gaming, Internet, and Hospitality industries.

Here is what that Elery suggests to the marketers out there:

“Don’t focus only on turning leads into sales, focus on turning influencers into ambassadors for your company.”

The influencers phenomenon is covered vastly on the web ever since the invention of digital social networks and the social graph. From what that I read so far it seems to me that we are still in the experimental/research phase. I was excited about finding a real application with proven method for finding influencers. Maybe Datanetis will help pushing this new science forward.


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