Digital Health
InContext Solutions Launches Artificial Intelligence for Shopper Insights
Arrangement AI is a new behavioral insights prediction model for planogram arrangement, based on more than 2 million virtual store shopping trips. InContext…
Arrangement AI is a new behavioral insights prediction model for planogram arrangement, based on more than 2 million virtual store shopping trips.
InContext Solutions, the global leader in 3D simulation software for retail, is pleased to announce the official launch of Arrangement AI. The new offering utilizes machine-learning and artificial intelligence (AI) prediction models to generate fast, flexible, and scalable insights for planogram arrangement concepts.
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“There’s no denying the impact of AI in many different industries, from healthcare to education to finance, and retail is no exception,” said David Rich, InContext CEO and Chairman. “AI is already streamlining logistics, creating frictionless checkout and providing image recognition. Today, InContext adds shopper insights prediction as another triumph for machine learning technology.”
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InContext co-founder and chief research officer, Rich Scamehorn, has led InContext to become one of the world’s foremost virtual research and visualization companies, with observed behavioral data that correlates at 0.9 or higher with in-market results. Scamehorn and team have now parlayed that experience to help take shopper insights into the world of artificial intelligence.
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“InContext’s bread and butter is our 15 years of industry-leading virtual shopper research,” said Scamehorn. “With a data lake of more than two million virtual shopping trips and over one thousand online shopper surveys, we are able to create proprietary machine-learning models that can predict behavioral outcomes for planogram arrangement with 80% accuracy on average, and in 65 CPG categories in the US.”
[To share your insights with us, please write to sghosh@martechseries.com]
The post InContext Solutions Launches Artificial Intelligence for Shopper Insights appeared first on AiThority.
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