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How to Use POS Data for Intelligent Retail Execution [Free Guide]

One of the most basic tools CPG brands use to understand their position in the market is point-of-sale data. From the very first time a shopper put your product in their cart to the nationwide sales you may enjoy today, POS data paints a picture of when and where your products -- and your competitors’ -- are scanned for purchase.

Armed with this intel, brands can identify new shopping trends, opportunities for growth, competitive threats, and more, and use that insight to build an intelligent strategy for where and how to invest at retail.

But as CPGs build a deeper understanding of not just where and when they’re sold, but what field activities and in-store conditions are influencing those sales, they’re able to use POS data to inform their retail execution strategy as well.

From optimizing store position and display execution to improving partnerships with retail managers, CPG brands are using point-of-sale data to radically improve execution in the store to drive sales velocity.  

 

How to Use POS Data for Intelligent Retail Execution

In this eBook, we’ll outline how CPG brands can use their point-of-sale data alongside field activity data to supercharge their retail execution strategy. 

In this guide, you'll learn how to leverage your POS data to: 

  • More accurately track promotion execution
  • Respond to noncompliance faster for more effective promotions
  • Encourage retail partners to buy in to the success of your promotions
  • More effectively plan which stores your field team should visit to have the biggest impact on sales.
 

Frank Brogie

Frank Brogie is the Product Marketing Manager at Repsly. When he’s not thinking about how to position and sell Repsly’s products, Frank loves to explore Boston by bike and hunt for vintage cars through a camera lens. On weekends you can count on Frank to organize a pickup basketball game or play disc golf. An avid podcast listener, Frank recommends Philosophize This, 99% Invisible, and Radiolab.

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