AI Product Assortment
Planning Solutions

By leveraging artificial intelligence for adaptable planning, your retail teams can create more profitable, optimized assortments down to individual stores.

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Woman stocking produce at a grocery store
Woman stocking produce at a grocery store

Product assortment teams typically have deep, intuitive expertise when it comes to tailoring product assortments but struggle to get a clear picture of the impact of their decisions. By leveraging AI, retail organizations can balance the art and science of assortment planning — complementing teams’ historical knowledge with data to improve learnings and decisions over time.

RevUnit partners with leading retailers to centralize data, build custom assortment planning tools and gain a full picture of how merchandising decisions are made — with custom solutions naturally integrated into planner workflows.

A custom solution to fit your needs

Every organization we work with is different in their strategy, systems, team makeup, and data needs, so there’s not one single approach to building a custom data solution. Because of that, our teams are experts in the data journey — from modeling raw data to data visualization and building products that drive action. Once we have an understanding of your needs, we’ll create a customized solution to fit. 

We won’t just build a product; we will work with your teams and systems to get the data necessary to surface actionable insights, faster.

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Case Study: Empowering Grocery Buyers

A centralized assortment tool paired with predictive analytics provides opportunity to delight consumers with unique products and stocked shelves.

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You may need this if…

  • Current planning / buying is based on instinct or internal knowledge
  • Assortment changes are slow, with little insight into performance
  • You need a source of truth for assortment decision-making
female employee stocking produce at grocery store

How we can help

We’ll work with your team to understand how your planners are making assortment decisions, then build AI logic and an interface to surface recommendations for optimization.

Embedded strategic team that will teach + do
Data mapping + modeling to get to the necessary insights
Machine learning model integrated into existing systems
Intuitive interface for users to verify matching

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Retail data services

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Case Study

Redesigning in-store processes to improve efficiency

female retail worker/manager with short hair and glasses completing tasks on a tablet.

How one of the world’s largest retailers created a scalable digital platform that’s now used each day by more than 1.5 million team members in six countries

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Understanding & implementing recommendation engines

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Businesses across all industries can use these systems to create a better experience for customers while also helping employees make more-informed decisions.

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6 Real-world ways to surface insights to frontline employees

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The best data tools may not even feel like a data tool, but instead an informative or process management tool that makes employees’ jobs easier.

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Are you looking to create change, faster, with your data?

We can help you make that happen. Let's set up a time to discuss how.

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