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Data Services

RevTrax data services help brands personalize pricing and promotion.

Buyers Guide

Data Services Buyers Guide Take a deeper dive into our RevTrax Data Services to learn more about what you can do and how you can do it.
Read the Buyers Guide

A breakthrough in data science to predict consumer behavior

Using data science, RevTrax offers its client partners the ability to leverage insights from billions of consumer engagement data points to determine ideal pricing and promotion in a privacy-by-design framework using state-of-the-art modeling techniques.  

In the world of evolving consumer privacy, brands demand that data partners are privacy-focused.  RevTrax utilizes a predictive engine built without using any sensitive personal information or exposing any consumer private data.

RevTrax data services are based on over a decade of experience studying consumer response to offers and state of the art machine learning algorithms.  You don't need to provide any data assets to take advantage of this technology.

Want to suppress against deal-seekers who will churn?  We’ve got your covered.

RevTrax data can be used to ensure that you’re targeting full price buyers who are engaging with your brand for the right reasons and are more likely to be valuable long-term customers.


Want to improve margin and drive more sales at the same time?  Check out what Clorox did.

The Clorox Company – a leading multinational manufacturer and marketer of consumer and professional products – recently partnered with RevTrax and saw a 291% increase in units moved by leveraging this data.


Want to ensure higher conversion rates from targeted media?  We can do that.

RevTrax understands which consumers are most likely to convert and can help you create audiences that are more likely to engage and make a purchase. 


Want to drive more successful shopper campaigns?  Check.

We can help you target consumers who are most likely to shop at individual key accounts for a specific category or type of product.


Our predictive models are built on a strong foundation: 

        • 100+ million attributes observed each month
        • 2,000+ retail banners represented
        • 250k+ individual retail storefronts represented

So how does it work?

Partners can leverage a real-time API or file sync to take advantage of this offering.  Data Services include:

        • Price Sensitivity: Returns a score between 0-100 based on the likelihood a customer is discount sensitive.
        • Full Price Buyer: Returns Y/N value to determine if a consumer is willing to pay full price or needs a discount to make a purchase.
        • Retailer Preference Rank: Returns retailer name and rank of retailer preference for a consumer
        • Retailer Class of Trade Preference: Returns preferred retailer class of trade and rank for a consumer
        • Retailer Preference: Returns Y/N value to determine if a consumer is likely a shopper of a specific retailer
        • Best Time to Engage: Returns the daypart that represents the best time a consumer is likely to engage

Want to learn more? Reach out through the chatbot or go here.