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A/B testing for brick-and-mortar stores.
Key people at Prayas Analytics.
Prayas Analytics was founded in 2014 by Yash Kothari (Founder) and Pranshu Maheshwari (Founder/CTO).
Prayas Anaytics helped retailers A/B test their stores, the way eCommerce companies A/B test their websites. We did this by continuously collecting data on customer movement using existing security cameras already in a retailer's stores.
We were a Y Combinator backed company (S15) and worked with several retailers including Barneys, Payomatic, and multiple Fortune 200 retailers.
Prayas Analytics was founded in 2014 by Yash Kothari (Founder) and Pranshu Maheshwari (Founder/CTO).
Key people at Prayas Analytics.
Prayas Analytics developed a data analytics platform for brick-and-mortar retail stores, enabling retailers to perform A/B testing in physical locations similar to how eCommerce companies test website changes. Their product collects data on customer movement and behavior inside stores using existing security cameras, without requiring additional hardware. This helps retailers optimize customer experience, reduce abandonment, and improve labor efficiency. The company primarily served large retailers, including Barneys and Fortune 200 companies, aiming to bring digital-style experimentation and analytics to physical retail[1][2][4].
Founded in 2014 and backed by Y Combinator (Summer 2015), Prayas Analytics positioned itself at the intersection of retail technology and data analytics, addressing the challenge of measuring and optimizing in-store customer behavior. Their solution filled a gap in the retail ecosystem by enabling data-driven decision-making for physical stores, a sector traditionally lacking the granular analytics available online[1][2].
Prayas Analytics was founded in 2014 by Yash Kothari and Pranshu Maheshwari, both recent graduates from the University of Pennsylvania. The founders combined backgrounds in statistics, programming, and economics to create a product that could bring the power of digital analytics to physical retail environments. The idea emerged from recognizing the lack of tools for continuous, data-driven experimentation in brick-and-mortar stores, unlike the well-established A/B testing in eCommerce[1][3][5].
Early traction included acceptance into the prestigious Y Combinator accelerator program in Summer 2015, which helped them refine their product and gain access to a network of investors and retail clients. They worked with notable retailers such as Barneys and Payomatic, validating their approach and technology by deploying their analytics platform in real-world retail settings[1][2].
Prayas Analytics rode the wave of digital transformation in retail, where brick-and-mortar stores increasingly sought to leverage data analytics and experimentation to compete with eCommerce. The timing was critical as retailers faced pressure to improve in-store customer experience and operational efficiency through technology.
Market forces favoring Prayas included the growing availability of in-store cameras, advances in computer vision, and the rising expectation for data-driven decision-making in all retail channels. By enabling A/B testing in physical stores, Prayas Analytics helped bridge the gap between online and offline retail analytics, influencing how retailers approach store optimization and customer engagement[1][2][4].
Although Prayas Analytics is currently inactive, their approach highlighted a significant opportunity in retail tech: applying rigorous, data-driven experimentation to physical stores. Future trends shaping this space include enhanced computer vision, AI-driven analytics, and integration of omnichannel data to create seamless customer experiences.
If revived or succeeded by similar companies, this model could evolve to become a standard tool for retailers, helping them adapt quickly to changing consumer behaviors and competitive pressures. The concept of A/B testing in physical retail remains highly relevant as the industry continues to digitize and innovate.
Prayas Analytics exemplified how startups can translate digital best practices into traditional sectors, setting a foundation for ongoing innovation in retail analytics[1][2][4].