Social Soup Debuts Machine Learning Platform For Influencer Matching

Social Soup Debuts Machine Learning Platform For Influencer Matching
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Influence consultancy Social Soup has developed a platform that utilises machine learning to drive stronger brand and influencer partnerships.

Social Soup’s Alignment Algorithm has been built around customisable metrics, allowing a brand to partner with an influencer that is more closely aligned to their brand, their products and their marketing objectives.

The development of the platform has been based on the concept of Augmented Intelligence, a combination of human review and machine learning to allow consultants to become faster and smarter at assessment and decision making.

Combining human assessment that in turn drives machine learning, the platform is coupled with AWS (Amazon Web Services) image recognition software, enabling Social Soup consultants to advise better matches to a brief more quickly.

Brands will be able to narrow their search on a range of customisable settings, including content aesthetics, influence typology, brand archetypes and values plus the traditional performance metrics.

Social Soup’s head of strategy Lee Schofield said the Alignment Algorithm applied science to the art of influence management.

“There are thousands of influencers that brands can choose from and who they select has a significant impact on the outcome of a campaign or partnership,” Schofield said.

“With the selection of the influencer community currently based predominantly on human judgement or a basic influencer database, the ROI will be impacted as the influencer in question may not match the look, feel, values or goals of the brand.

“This platform removes the guesswork, driving better selection, stronger collaboration between the brand and influencer and ultimately a greater ROI.”

The platform has been developed in partnership with leaders in the machine learning field in Australia and will be rolled out to clients over the coming week.

As with most algorithms, it will be a continuous process of learning, adjustment and improvement as the platform reviews more and more content, performs more searches and learns more about the brands’ needs. Ultimately, Social Soup hopes to apply AI to enable the platform to automatically suggest further criteria that might meet the brand’s needs.

Social Soup founder and CEO Sharyn Smith [feature image] welcomed the new technology.

“Brands are redirecting more and more of their marketing dollars to influence marketing. At the same time the influencer community continues to grow.

“With this comes opportunity but also risks. The ability to find the right influence partner becomes more difficult, the growth in fake performance metrics from some influencers, through bots and other techniques, has also grown distorting the true influence that person may have.”

“It simply isn’t feasible to leave this critical research and analysis to the human consultant alone. By giving our team the power of AI and machine learning we can strengthen their impact and provide our client partners with greater accuracy, alignment and outcomes.”

 

 

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