NEW YORK — May 9, 2023 — Kasada, provider of the most effective and easiest way to defend against advanced bot attacks, today announced a strategic partnership with Signifyd, a specialist in eCommerce fraud and consumer abuse protection.

This partnership demonstrates the companies’ commitment to helping eCommerce providers deliver on their core business priorities to reduce fraud while improving the user experience. Together Kasada and Signifyd provide an impenetrable barrier against fraud. Kasada’s anti-bot platform stops automated online fraud before it happens, while Signifyd’s Commerce Protection Program protects against additional fraud forms and consumer abuse.

“Many retailers and eCommerce organizations often face the challenge of balancing fraud prevention with a seamless customer experience. But they shouldn’t have to choose between the two,” said Sam Crowther, CEO and founder of Kasada. “Our partnership with Signifyd provides companies with a holistic solution to combat fraud without introducing any friction into the buyer’s journey, resulting in lower costs and higher profit margins.”

By eliminating automated traffic, customers will experience increased conversion rates, enhanced site performance, and gain valuable analytical insights from genuine traffic. This will enable online retailers to accurately project customer purchases, anticipate profits, run more effective marketing campaigns, forecast infrastructure spend, and better plan for future demand.

Read the full release here.

Want to learn more?

  • Why CAPTCHAs Are Not the Future of Bot Detection

    I’m not a robot” tests are definitely getting harder. But does that mean more complex CAPTCHAs are the right path forward to outsmart advancing AI and adversarial technologies?

  • The New Mandate for Bot Detection – Ensuring Data Authenticity

    Can the data collected by an anti-bot system be trusted? Kasada's latest platform enhancements include securing the authenticity of web traffic data.

Beat the bots without bothering your customers — see how.