Azoma receives investment from dunnhumby ventures to accelerate its Agentic Commerce Optimization platform

Azoma, the Agentic Commerce Optimization (ACO) platform that measures and improves how AI shopping agents discover, interpret and recommend products for retailers and CPG brands, today announced an investment from dunnhumby ventures. The investment reflects a shared view that AI shopping assistants are becoming the primary route to purchase, and that retailers and consumer packaged goods brands need to measure that channel as rigorously as they measure the shelf. The new funds will accelerate Azoma's product roadmap for customers including L'Oréal, Unilever and Mars, extending its ability to connect AI Visibility to recommended actions and measuring incremental revenue.

What the investment unlocks

The investment reinforces dunnhumby's commitment to rapid innovation in AI and bringing leading-edge technologies to clients as consumer behaviours and retail ecosystems continue to evolve. dunnhumby, the pioneer of retail customer data science, analyses $600 billion in global retail sales and processes 500 million retail transactions a week, according to figures it published in August 2026. As part of the investment, through Azoma, dunnhumby will be able to extend how it supports its retailer clients optimizing for Google's Universal Commerce Protocol (UCP) and the Agentic Commerce Protocol (ACP) while providing brands with the ability to enhance discoverability and drive revenue through shopping Agents like ChatGPT, Gemini, Alexa for Shopping and Walmart Sparky.

Leo Nagdas, Head of dunnhumby ventures, has also joined Azoma as advisor to the board as part of the investment. Nagdas founded dunnhumby's Retail Innovation Network, an open innovation programme for retail technology leaders.

Continued collaboration over the coming years will bring together Azoma's expertise in Agentic Commerce Optimization with dunnhumby's deep retail and customer data science capabilities. Azoma's Digital Twin technology, which simulates AI shopper personas to sharpen tracking and optimization, is expected to become available to dunnhumby's clients over time as part of an offering still in development.

The problem we are solving

Azoma's analysis of tens of millions of AI responses in the second quarter of 2026 found that earned or social media accounts for 86.5% of the citations behind Alexa for Shopping's recommendations, and 76% of those behind Walmart Sparky's. ChatGPT draws more heavily on retailer sources, at 37.1%. The answer a shopper receives is therefore assembled largely from sources the brand does not own.

The biggest challenges facing AEO/GEO (Answer Engine Optimization / Generative Engine Optimization) tools are understanding what the right prompts to track are, and what the revenue impact from actions is. dunnhumby's trusted data and expertise will enable Azoma to provide this to customers, strengthening its position as the leading AEO/GEO tool for ecommerce.

"AI shopping assistants are rewriting the path to purchase, and today retailers and CPGs have no reliable way to connect what an agent recommends to a sale," said Leo Nagdas, Head of dunnhumby ventures. "Azoma is a leader in the emerging agentic commerce space, and the team combines real depth in AI with a practical grasp of how retail actually works. Backing companies like Azoma is how we bring emerging technology to our clients as consumer behaviours and retail ecosystems keep changing."

Max Sinclair, CEO and Co-Founder, Azoma, commented: "dunnhumby has decades of expertise helping brands and retailers leverage customer data insight." He added: "Agentic Commerce is the next frontier. dunnhumby understands this, and brands and retailers' current data blindness better than anyone. Their investment is a vote of confidence in our current solution and shared vision. In time, their data will help us demonstrate to the world's largest retailers and consumer brands the tangible value of agent-driven recommendations. Agentic commerce is a $9 trillion opportunity, and this is how we will continue to define the category."

What this means for the brands we work with

A brand can do everything right on its own site and still lose the recommendation, because most of what an agent reads sits somewhere else.

That is the problem our customers use the platform to solve. We measure how products appear across retailer shopping agents and general assistants, at brand, category and SKU level, with the prompts and citation sources behind every mention, organised around the 5 C's of Agentic Commerce we co-authored with the Digital Shelf Institute.

Four of the five decide whether an agent can find, understand and correctly describe a product. The fifth, customer acquisition, connects that to revenue, and it is the one enterprise teams are held to. We already tie discovery, rank and citation gains to SKU-level revenue. Sharpening that connection across more of the shelf is what this investment accelerates.

If you want to know how your products currently appear across AI shopping agents, get in touch.

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The announcement
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Coverage

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