RevTrax, the industry pioneer and market leader in offer management solutions, and the exclusive Offer Management Platform (OMP) provider to hundreds of multinational CPG, retail, travel, financial services and automotive brands, announced the launch of its newest product, Predictive Purchase Data (PPD). With this new product, for the first time ever, RevTrax is leveraging more than a decade of consumer behavioral data to enable broader personalization use-cases for marketers.
“PPD can support a whole breadth of personalization use cases across every consumer digital touchpoint,” said Jonathan Treiber, Chief Executive Officer of RevTrax. “We’ve taken a giant leap with this offering, unlocking the AI intelligence and behavioral signals that power our proprietary Offer Management Platform for smarter discounting and couponing. With this now unlocked from our platform, marketers in all consumer verticals can leverage these unique pricing signals for their myriad personalization or media targeting strategies.”
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In the past six months, promotional marketers have faced increasing pressure to improve profitability due to the strains brought on by the COVID-19 pandemic. One-size-fits-all marketing and discounting strategies aren’t working. Innovative brands are revolutionizing to drive more profitable sales by knowing which customers need a discount and which don’t. RevTrax’s new PPD product gives brands the ability to leverage behavioral insights to create and deliver new personalized customer experiences that do not have to focus on discounting. The product aims to increase the profitability of each conversion by empowering marketers with the insights they need to determine which customers need discounts and which don’t, thereby enabling marketers to focus on tailoring their product offerings to customers based on profitability, not just top line. There are six predictive models available that allow marketers to deliver a better personalized experience to consumers across owned and paid media:
- Price Sensitivity – Returns a score between 0-100 based on the likelihood a customer is discount sensitive.
- Retailer Preference Rank – Returns retailer name and rank of a retailer preference for a consumer.
- Retailer Preference – Returns Y/N value to determine if a consumer is likely a shopper of a specific retailer.
- Full Price Buyer – Returns Y/N value to determine if a consumer is willing to pay full price or needs a discount to purchase.
- Retailer Class of Trade Preference – Returns preferred retailer class of trade and rank for a consumer.
- Best Time to Engage – Returns the day-part that represents the best time a consumer is likely to engage.
As retail, healthcare, and financial executives have struggled with how to react to such severe changes in consumer demand, many are at a loss for successful marketing strategies. RevTrax’s new PPD gives marketers a view into a unique dimension of consumer behavior, their price and discount sensitivity at a product and category level. This adds a new understanding of each consumer’s ability or willingness to pay for a product or service. When added to the demographic and psychographic info many marketers have already, this additional ingredient can make the difference between maximizing margin and losing money for large consumer businesses.
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As consumer privacy is of paramount importance, RevTrax’s PPD is built on a data science breakthrough that enables predictive models to score consumer traffic without requiring any sensitive consumer information. This privacy-by-design framework leverages billions of attributes to inform predictive models to a high degree of accuracy.
RevTrax’s mission is to help large consumer companies maximize profit and eliminate promotional waste due to over-discounting. PPD is aimed to extend the RevTrax mission and value proposition beyond its OMP with a data set that can be leveraged separately by marketers to increase profits up to 15% across all their other non-RevTrax personalization efforts. RevTrax’s platform is used by a variety of leading brands including Dunkin’, Starbucks, Express, Kimberly-Clark, Unilever, and Sherwin-Williams.
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