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Google Cloud and Pluto7 helped a SoCal’s Gourmet Food Market optimize their inventory assortment using omni-channel data points

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One of California’s largest supermarkets was able to gain deeper, more realistic and prediction-based insights to improve inventory assortment


The client is an American regional supermarket chain operating in Southern California. The client engaged Pluto7 for driving transformation in the item assortment processes using ML and Ai by activating their data over digital and IoT touchpoints.

Why We Chose Pluto7

Pluto7, a Google Cloud Premier Partner, specializes in deploying accelerated solutions and custom applications in smart analytics, machine learning, and AI. The client realized that we can add immense value by leveraging our knowledge of machine learning and integrating that with current Google Cloud Platform tools such as BigQuery, Natural Language, and Google Kubernetes Engine to create an integrated solution that allows them to leverage their industry experience to build a compelling, data-driven product for many SMBs and middle market customers.


Client was enthusiastic to blend advanced tools and technologies like Cloud, ML/Ai, IoT, and Pluto7’s expertise to gain deeper, more realistic and prediction-based insights into their business, especially in leveraging the ability to determine the most optimized item assortment based on customer’s predicted value, predicted future revenue by product and differentiated and substitute items.


With a completely automated process for true item assortment, the client was able to improve revenue, productivity and customer satisfaction. With Google Cloud Platform and it’s products, Pluto7 was able to scale on hundred thousands of items and get better results within a few hours.


Enable Decision Intelligence Into Every Corner Of Your Product And Operations.

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Industry Retail

Platform Demand-ml| Sales-ml| Supply-ml


  • Manual assortment limits ability to maximize revenue
  • manual assortment is not able to effectively respond to customer behavior changes
  • Shelf storage allocation not able to scale


  • Scalable item assortment process based on customer value, predicted revenue by item and differentiated items.
  • Able to use dynamic item assortment to drive marketing and inventory thus setting the stage for improved revenue and reduced costs.
  • Facilitates improved customer satisfaction by ensuring stores have customer desired products on shelf.

Products Used

  • Google Cloud Platform
  • Google Cloud Storage
  • BigQuery 
  • Data Lab / Ai Notebook
  • Tensorflow
  • Google Cloud Machine Learning Engine
  • App Engine
  • Looker