omnichannel Return dollars saved:
Appriss Retail helps retailers optimize returns by improving the consumer experience and reducing risk
We’re partnering with retailers, worldwide, to provide them with knowledge for good. With the power of big data analytics, they’re making faster, better informed decisions for tackling shrink and fraud plus increasing profits while providing good service to valued customers.
Lifting store performance by increasing sales, and reducing loss with solutions that enhance customer service (including BOPIS) and consumer loyalty.
Changing the consumer experience to reflect an omnichannel journey. Optimize for buy-online-return-in-store (BORIS), click and collect, and more.
Capitalizing on foot traffic to generate new revenue and measurably improve customer loyalty through intelligent, targeted incentive campaigns.
Immediately impacting total loss by reducing consumer fraud, retail shrink and procedural errors, while fostering a positive customer experience.
Appriss Retail benefits its clients with advanced analytic solutions and artificial intelligence models that help retailers increase net sales, enhance the customer experience, reduce loss, tackle sales reducing activities (SRAs), and improve performance.
Our solutions deliver immediate and measurable results. We use data analytics not available through any other source (including your in-house analysts). We have a team of PhD and MS degreed statisticians, a statistical criminologist, and a Certified Fraud Examiner on staff.
SaaS solutions providing retail predictive analytics, exception reporting, case management, and data integration.
A data-driven solution that enhances the consumer returns experience to drive profitable sales while reducing fraud and building loyalty.
By using key information at the time of purchase or return, Incent delivers targeted, highly valued incentives that drive additional purchases within hours of a transaction, improving store performance.
A real-time, consumer-based authorization system, that uses predictive algorithms and statistical models to identify and deter fraudulent return behavior in stores, call centers, and online.