Appriss Retail
Optimizing Retail through Actionable Intelligence

Retail CIOs have invested significant resources in building data analytics platforms to understand what happened in the enterprise and why. These systems span sales, returns, inventory movement, purchasing, and more. The purpose of these systems is to support better decisions. Simultaneously, the world of retail is changing: the demographics of the shopper, how consumers discover products and shop for them, and the ever-blurring lines between online and offline. Never has the pressure to become a real-time enterprise been as strong as it is now.

Real-time enterprises distribute business-critical information everywhere it is needed, analyze it, determine next steps, and trigger those decisions as required. Instantly. Leveraging the most up-to-date information with advanced analytics and driving decisions in real-time is the next major frontier for retail CIOs as they look to drive efficiency, efficacy, and profitability. The challenge is where to start. Is this a whole different infrastructure and investment? Or can something that already exists be leveraged?

Exception Based Reporting systems (EBR) are great starting points in this transformation. Even though most EBR systems provide a retrospective view, they often have the most recent store-level data. With the right architecture, this granular, very fresh data can be combined with sophisticated real-time analytics systems to drive decisions across the enterprise.

Appriss Retail identified this opportunity and combined two sophisticated technology solutions into one powerful platform that improves retailers’ performance. The first solution is an advanced EBR system which powers the intelligence and analytics operations in some of the largest enterprises in the world. The second is a state-of-the-art real-time decisioning system. By helping structure and flow data from the EBR system into the predictive analytics and decisioning system, Appriss Retail supports a real-time enterprise, be it to reward a high-value customer by issuing an incentive right at the point of sale, blocking fraud, or prompting an employee on what to do next. Imagine the power you place in the hands of your employees when your system identifies a consumer who may have just taken on responsibility for a multi-generational household and prompts them to offer the consumer a subscription service that saves her time and delivers her new purchases to her doorstep.

“Serving over 90 of the largest, most advanced retailers across 45 countries at over 100,000 locations gives us a ‘boots-on-the-ground’ view of the power of an intelligent and adaptive enterprise. Combining the vision of our customers with the capabilities of our data scientists, engineers, and product experts opens exciting new ways in which we are able to help our clients be more competitive,” says Krishnan Sastry, president of Appriss Retail.

The Appriss Retail platform offers an extensive analytics data store that powers three flagship products. One is the post transactional analytics platform, Secure™, a sophisticated vertical BI solution which helps identify important issues at the store level. Another is Verify^® return authorization, a real-time analytics and decisioning platform that improves the customer experience for the 99 percent of good customers making merchandise returns while mitigating fraud from the few bad actors. The third component in the portfolio is Incent™ targeted incentives which optimizes the consumer experience by offering the most profitable consumers intelligent incentives to make additional purchases from the retailer that day.

With more than 20 years of retail data science expertise, Appriss Retail’s Software-as-a-Service (SaaS) platform generates advanced analytical insights and real-time decisions that drive action throughout the organization, including operations, finance, marketing, and loss prevention. Its performance-improvement solutions yield measurable results with significant ROI among retail store, ecommerce, and inventory functions.