Beyond Chatbots: 40+ Commerce Startups Using AI To Style Shoppers, Adjust Pricing, Track Behavior, And More

Investors poured a record high of $4.9B into artificial intelligence (AI) startups in 2016, and AI is already affecting more areas of our lives than many people realize. Even retail and e-commerce companies are increasingly integrating the technology. While chatbots may be one of the more well-known use-cases for AI in commerce, there are many other startups finding alternative uses for AI in the space.

In 2017, some of the largest deals to AI commerce startups have included a $19.5M Series D to in-store visual monitoring startup Trax Image Recognition from Investec, a $16M Series A funding to location-based marketing startup Databerries from investors including Index Ventures and Mosaic Ventures, as well as a $15M Series B to natural language search startup Twiggle from Korea Investment Partners and Mizmaa Ventures.

Using CB Insights data, we created a market map showcasing the wide array of AI startups focused on retailers and e-commerce businesses, including AI-powered personal shopping apps, natural language processing and image recognition tools for shopping websites, predictive inventory allocation tools, and more.

While there are numerous other AI startups focused broadly on personalized marketing and ad targeting, we limited this market map to startups whose core focus is retail and e-commerce. Scroll down to view the graphic, category explanations, and a full company list with select investors.

Click to enlarge. This market map is not meant to be exhaustive of startups in the space. 

Category breakdown

We divided our market map into the 11 categories listed below:

Real-time product targeting – Machine learning to present online shoppers with personalized product recommendations. These companies typically update e-commerce websites in real time to present product selections best suited to the individual shopper.

Real-time pricing & incentives – Machine learning to adjust pricing, sale options, rewards, and coupons in real time to try to push hesitant shoppers toward conversion.

Natural language search – Algorithms that use natural language processing to improve search functionality in e-commerce websites.

Visual search – Image recognition platforms that help e-commerce websites let visitors search by image, instead of text, and match relevant products to specific images.

In-store visual monitoring – AI-powered software that analyzes photo and visual content of store shelves to help brands track how their products are stocked and promoted in real time.

Conversational commerce – Chat software and chatbots focused on helping shoppers make purchases in a conversational text format using natural language processing.

Predictive merchandising – Big data analysis to optimize purchasing, allocation, and product assortment across stores and e-commerce. The aim is to better predict demand in different geographies to avoid waste and prevent inventory from going out of stock.

Sizing & styling – AI-powered software to help retailers integrate improved product sizing and outfit-building tools into their websites.

Multichannel marketing – Startups using AI to create targeted marketing campaigns across desktop, mobile, email, and other digital channels. Inclusion limited to startups focused specifically on e-commerce.

Integrated online & in-store analytics – Startups that combine both digital and physical store analytics to help retailers better understand their customers.

Location-based marketing & analytics – Startups that combine digital and physical store analytics, while also integrating beacon technology to track shoppers’ locations.

Company list

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