Signifyd Launches Its Commerce Protection Platform to Optimize Revenue Throughout the Shopping Journey

Signifyd announced the launch of its Commerce Protection Platform, an innovative retail solution that leverages its vast Commerce Network to maximize ecommerce conversion, automate customer experience and eliminate fraud and customer abuse.

The enterprise-ready platform gives retailers “found money” to overcome the twin challenges of modern retail rapidly increasing costs for top-of-funnel customer acquisition and bottom-of-funnel fulfillment. As platforms like Google, Facebook and Amazon drive up digital ad prices and customer expectations, merchants need to recapture lost revenue opportunities in the middle segment of the shopper journey checkout and payments flows.

“The Commerce Protection Platform is built for retail in the 2020s,” Signifyd CEO Raj Ramanand said in announcing the product. “The enterprise market has been looking for a complete solution that will not only automate the customer experience needs of today, but will also identify and capitalize on missed conversion potential in their checkout flows.”

Recommended AI News: 4 Tech Industry Predictions for the Edge Computing Focused New Year

The platform will be formally unveiled Thursday at Signifyd’s FLOW Forward Summit 2020, a virtual conference featuring a half-day of learning from some of retail’s preeminent thought leaders.

The Commerce Protection Platform was designed in consultation with Signifyd customers, including Customer Advisory Board members Samsung, TUMI, Rite Aid, Crown & Caliber, Stance and Boardriders.

By harnessing artificial intelligence, the platform automates online order flows, instantaneously sorts fraudulent orders from legitimate ones, triages abuse chargebacks stemming from customer disputes and future-proofs the enterprise against rapidly evolving payments compliance issues. It also includes a financial guarantee backing the platform’s decisions.

Anthony Milano, vice president of Boardriders and a member of Signifyd’s Customer Advisory Board, said Signifyd’s solutions helped boost the company’s approval rate by 25 percentage points to more than 99%. It also accelerated fulfillment across the board.

Recommended AI News: First RPA Center of Excellence to Bring Hundreds of New Jobs to Mississippi Delta

Signifyd’s Commerce Network spanning over 10,000 merchants globally ensures prior knowledge of more than 97% of online shoppers. That network data powers the platform, which delivers an average revenue lift of 4% to 6% (often more in merchants with legacy technology). It also drives win rates that are 50% to 60% higher than industry averages for shopper-abuse chargebacks.

Retailers have increasingly instituted innovative customer experience improvements to compete with the likes of Amazon. Programs that allow consumers to buy, pick up and return anywhere, for instance, have made customers’ lives easier, but also opened up retailers to increased fraud.

Retailers are also seeing a rise in abusive shopper behavior illegitimate claims that ordered products never arrived or that items received from merchants were not as described online. Such claims spur their own chargebacks. These trends will ensure that abuse will become a bigger problem than payment fraud in coming years.

The Commerce Protection Platform comprises three distinct solutions Revenue Protection, Abuse Prevention and Payments Compliance that together remove the stress of managing fraud, abuse and payment regulation and thereby free retail professionals to focus on vital business initiatives and strategies.

At the core of the platform are three product modules the Agent Console, the Decision Center and Insights Reporting that power the solutions and provide valuable insights to retail leaders.

And while the platform’s revenue lift and consumer-abuse-chargeback recovery rates are impressive, the real win is the way the Commerce Protection Platform protects the customer experience and preserves customer lifetime value.

Recommended AI News: Skills to Master Before your First Data Science Interview