prescriptiveIQ™

With prescriptiveIQ™, Collective Bias is the first to integrate first–party purchase data combined with a data and technology stack that provides actionable insights that help drive brand, shopper, content, and context decisions to create better informed and more successful influencer campaigns.

Imagine if you could answer these questions for your brand:

  • What motivates shoppers to purchase?

  • How can we create awareness for your product using influencer content to increase in–store foot traffic and basket size?

  • How can we inspire new usage occasions and impact purchase cycles?

  • How can insights about how products are purchased together help shape content and strategy across retail, geographic, and demographic lines?

  • How can seasonality in purchase patterns and timely social dialogues inform the timeframes in which content is pulsed in–market to maximize viewership and engagement?

prescriptiveIQ™ applies data science to provide shopper, brand, content, and context intelligence.

With this technology and proprietary Inmar shopper data, we are now able to...

Design prescriptive content strategies based on a cohort set of proprietary data

Provide a robust post campaign suite of proven measurement tools that can determine efficacy all the way to sales impact

Utilize our machine learning algorithm that recommends both the optimal number of influencers to use and the influencers that best match your brand’s ideal consumer profiles

Design prescriptive content strategies based on a cohort set of proprietary data

Provide a robust post campaign suite of proven measurement tools that can determine efficacy all the way to sales impact

Utilize our machine learning algorithm that recommends both the optimal number of influencers to use and the influencers that best match your brand’s ideal consumer profiles

This data can also uncover product affinities like:

  • Consumer adoption trends

  • Demo & psychographics

  • Optimal in–market content duration

  • Purchase frequency alignment

  • Social platform media mix

  • Center store acceleration

  • Trip driver identification

  • Store periphery bakery, deli, produce

We also leverage sales data for the year to understand:

  • Average basket (number of items and dollars)

  • Number of products in basket

  • Multiple purchase incidence (MPI)

  • Breakout sales month-to-month

  • Compare data by name competitor or top four in the category

  • Understand the seasonality of your brand

This data allows us to determine what kind of content will perform best for campaigns, understand when to run campaigns, and understand how well the brand is doing across the category... leading to more consumer purchase occasions. At the end of the day, it allows us to yield the best results for you and your brand.

Ready to learn more?

Contact us.

Find our whitepaper

prescriptiveIQ™: Data Science Equals Better Performing Influencer Campaigns

here.