AI case study

InstacartIn-store recommendations

Physical stores were blind—no shelf data, no basket intelligence. On-cart AI now reads every item in milliseconds, turning carts into a revenue channel.

Published

Key results

Additional Sales Lift
~1%
Incremental Sales Lift
>1%
Click-Through Rate Increase
>5%

Result highlights

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The story

Context

An online grocery platform processing $37 billion in annual transaction value and over 1.6 billion lifetime orders, expanding into physical retail where 80% of grocery sales happen but real-time store intelligence barely exists.

Challenge

Physical stores had almost no real-time intelligence: planograms were inaccurate, out-of-stock items went undetected for hours, and shrink was rising...

Solution
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Quotes

The company

Instacart logo

Instacart

instacart.com

Online grocery delivery and pickup service from local stores.

IndustryRetail
LocationSan Francisco, CA, USA
Employees5K-10K
Founded2012

The vendor

NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.

IndustryTechnology
LocationSanta Clara, California, United States
Employees10K-50K
Founded1993

Use case

Instacart's In-store recommendations is part of this use case:

Personalization
45 case studies(+175% YoY)
Proven impact?
LowModerateVery Strong
5.4Strong
1.6Lowwithin Retail
3.8Moderatewithin Product Engineering

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