Personalized Offers for E-commerce | Bandit ML

Bandit ML concentrates on refining and automating the process of delivering the most suitable promotion to each individual customer.

The company participated in the summer 2020 cohort of the Y Combinator accelerator program. Furthermore, it secured $1.32 million in seed funding in September, with contributions from YC, Haystack Fund, Webb Investment Network, Liquid 2 Ventures, Jigsaw Ventures, Basecamp Fund, Pathbreaker Ventures, and a group of angel investors – including, according to CEO Edoardo Conti, ten present and former Uber personnel.

Conti, who established the company alongside Lionel Vital and Joseph Gilley, previously worked as a software engineer and researcher at Uber.

The core concept, as detailed in an email, is that customer preferences vary; one shopper may respond best to a $5 price reduction, while another might be more motivated by complimentary shipping, and a third may not be interested at all if they recently completed a substantial purchase. By analyzing a retailer’s sales history and website user data, Bandit ML intends to assist them in identifying the offer that will resonate most effectively with each customer.

Conti recognized the existence of other software designed to optimize discounts, but he asserted that none replicate the capabilities of Bandit ML: “readily available tools that employ machine learning in a manner comparable to industry leaders such as Uber, Amazon and Walmart.”

He further explained that Bandit ML’s technology stands out due to its support for complete automation (“certain retailers deployed their initial set of offers within 10 minutes of registration”) and its capacity to optimize for long-term performance indicators, such as purchases made over a 120-day timeframe, rather than solely focusing on immediate offer usage. Conti also noted that the technology underpinning the startup’s decision-making process is similar to the ReAgent project he contributed to while at Facebook.

Currently, Bandit ML primarily serves businesses utilizing Shopify stores, although it also accommodates other platforms, including Calii. Conti stated that the platform has facilitated the distribution of promotions totaling millions of dollars since July, with one apparel retailer experiencing a 20% increase in overall revenue.

“Our goal is to begin with a continuously active incentive system for all online businesses, and ultimately develop practical, ready-to-use machine learning tools that enable smaller online retailers to effectively compete with large corporations like Walmart and Amazon,” he stated.