By: Ibukun Keyamo
Ninety-four percent of marketers say personalization efforts drive direct sales increases, according to HubSpot’s State of Marketing research. That figure points to a measurable commercial shift now reshaping how major retailers approach their digital storefronts, and few companies are more central to that shift than Inference Beauty, the Swiss B2B beauty technology company founded by Estella Benz. Formerly known as Skin Match Technology, the company rebranded to Inference Beauty in 2025 as its platform expanded well beyond its original scope. Benz built Inference Beauty to solve a problem she identified at the core of beauty ecommerce: without structured product and ingredient intelligence, even the largest and best-curated retail assortments are difficult for shoppers to navigate with confidence. What she built in response is increasingly defining how forward-thinking beauty retailers approach personalization at scale.
How Inference Beauty Is Addressing Beauty Retail’s Personalization Gap
Beauty is one of the more complex product categories to sell online. Skin type, hair condition, fragrance preferences, ingredient sensitivities, and undertone all determine whether a product will work for a specific shopper. Those variables are straightforward for a trained store associate to assess in person and nearly impossible for a standard product listing page to address. The result has historically been purchase uncertainty, with shoppers defaulting to familiar brands, abandoning carts, or purchasing products that turn out to be a poor fit.
According to McKinsey’s research on scaling gen AI in beauty retail, gen AI-powered hyperpersonalization can improve beauty retail conversion rates by up to 40 percent. Yet most beauty ecommerce environments still lack the infrastructure to deliver this level of matching at scale, not because the will is absent, but because the underlying product and ingredient data is not structured well enough to power it. Estella Benz founded Inference Beauty specifically to close this infrastructure gap, building a platform that sits between a retailer’s product catalogue and its digital customer experience.
The Inference Beauty Platform and How It Works
The Inference Beauty platform is built on a proprietary database of more than 150,000 beauty products and 60,000 standardized cosmetic ingredients, organized by source, function, effect, and utility. The platform’s solution suite covers seven core capabilities: AI Skin Analysis for Skincare Personalization, AI Hair Analysis for Haircare Recommendations, AI Fragrance Finder with Olfactory Matching, AI Foundation Shade Matching Across Brands, an Ingredient Intelligence and Transparency Engine, Beauty Product Data Enrichment and Catalog Structuring, and a PDP Personalization and Recommendation Engine. The Inference Beauty engine enables retailers to deliver cross-brand product recommendations tailored to individual shoppers throughout the online journey. The platform draws on signals from more than 3 million beauty-interested consumer profiles per month, improving recommendation accuracy across skin type, fragrance preferences, and ingredient sensitivities over time.
“Retailers carry extraordinary product assortments, but without the right data infrastructure, those assortments are difficult for shoppers to navigate with confidence,” said Estella Benz, Founder and CEO of Inference Beauty. “The missing layer is structured product and ingredient intelligence. Once you have it, the quality of every recommendation, filter, and search result improves significantly.”
The commercial impact reported by Inference Beauty clients reflects measurable shifts in performance. In documented case studies, retailers using the platform have seen improvements in conversion rates and average basket value, along with modest increases in products added per basket and user sign-up rates, contributing to the development of first-party data and supporting more refined personalization over time.
Inference Beauty currently serves more than 100 retailers and brand integrations across the European Union, the United States, Canada, Australia, and the United Arab Emirates. The company is an alumnus of the Beauty Tech Atelier L’Oréal Accelerator and a winner of the ForwardBeauty Challenge by Douglas, two well-regarded recognition programs within the beauty technology sector.
Estella Benz on Ingredient Intelligence as a Growth Driver
Beyond diagnostics and product matching, Estella Benz has identified ingredient transparency as one of the most commercially significant opportunities available to beauty retailers today. Consumer interest in ingredient knowledge is now measurable in purchase behavior, with ingredient transparency data from Cosmetics Business showing 72 percent of shoppers expect detailed ingredient explanations when making beauty purchases online. That expectation is being reinforced by regulation, with new INCI Glossary standardization requirements under EU Commission Implementing Decision 2025/1175 taking mandatory effect in July 2026, and Canada’s SOR/2024-63 framework introducing parallel requirements for online sales.
Inference Beauty’s Ingredient Intelligence and Transparency Engine translates complex INCI terminology into clear, consumer-friendly insights while making that data actionable for product search, filtering, and personalized recommendations. The company’s ingredient database spans 60,000 standardized cosmetic ingredients, each categorized by source, function, and effect, and is among the more comprehensive ingredient databases designed for beauty retail applications.
“Ingredient transparency has moved from a brand differentiator to a baseline expectation,” said Benz. “Our platform translates complex ingredient terminology into clear consumer-facing insights while making that data actionable for personalized product discovery. That combination is what modern beauty retail requires, and it is what Inference Beauty is built to deliver.”
What the Market Data Says About AI Personalization in Beauty Retail
The commercial case for AI personalization tools in beauty retail is strengthening. According to a Future Market Insights forecast, the global AI beauty personalization platforms market is projected to reach 2.3 billion USD in 2026 and grow to 16.4 billion USD by 2036 at a compound annual growth rate of 21.7 percent. Case study data from across the industry show AI-powered beauty advisors consistently improving conversion rates and average order values at major retailers, with the scale of gains varying by platform, category, and deployment approach.
Retailers who have adopted structured AI recommendation infrastructure, including those integrating platforms such as Inference Beauty, are seeing tangible results across conversion, basket size, and multi-brand engagement. As Estella Benz puts it: “Retailers who deploy structured AI diagnostics see measurable improvements across every metric that matters. The data supports it, and the clients we serve are experiencing it directly.”
