Winston-Salem, NC: Collective Bias, Inc., influencer marketing, and an Inmar company, today announced prescriptiveIQ^TM, a suite of analytic solutions using first-party shopper data along with various data science applications to provide insights that inform every step of the influencer marketing process. PrescriptiveIQ^TM determines what kind of content will perform best for campaigns when to run campaigns, and how well the brand is doing across the category – ultimately leading to more consumer purchase occasions.

“Data science is helping us address key brand and shopper challenges and create smarter, more informed influencer campaigns,” said Irving Turner, Vice President, Analytics, Inmar’s Collective Bias. “The biggest evolution in marketing is going to come from the use of new data and their application to content strategies, targeting and more. By not only offering a range of data measurements to report accurate metrics on a variety of categories, but also actionable insights from this data, marketers will be able to strategically measure the effectiveness and true impact of their campaigns.”

Looking beyond simple sales or social engagement calculations, prescriptiveIQ™ provides marketers a comprehensive data and technology stack that goes deeper to offer actionable insights, and a full funnel of measurement capabilities for strategic decision making in influencer marketing campaigns.

The offerings include:  

• Shopper Intelligence: Brands can use sales data to understand the seasonality of the brand and to time the use of influencers. Machine learning algorithms recommend both the optimal number of influencers to use and the influencers that best match their campaign.
  
   
• Context Intelligence: Through analyzing social trends data and general lifestyle indicators, brands can uncover ideas for content and tap into trending ideas to drive engagement.
  
   
• Brand Intelligence: The data can uncover basket affinities, which can identify not only the likelihood of co-purchase opportunity, but also the relative size of opportunities for segmentation and targeting.
  
   
• Loyalty/Segmentation: Using purchase data, households are segmented across an entire category to determine brand loyalty of shoppers against competitive products.