Blog
Insights on AI retail media & agentic commerce
Playbooks, product updates, and points of view on growing retail revenue with AI.
Google may have just created a billion-dollar optimization market
AI visibility struggled to attract serious budget for a simple reason: nobody funds what they can't measure. With Google's new AI Performance Insights, it's measurable now. So the money moves.
TakesThe most expensive thing in retail right now
Brands are pouring attention into a future that isn't generating revenue yet, while the surfaces actually producing revenue today get treated like settled infrastructure. A preview of my CommerceNext session with Ken Pilot and Noam Paransky.
TakesGoogle says conversational attributes are optional. History says otherwise.
Mobile-friendly, page speed, structured data: Google introduced each as optional, and each became the price of entry. Conversational attributes, its new AI-shopping feed fields, look like the next one.
TakesYou don't have an agency problem. You have an input problem.
A CMO fired three paid agencies in two years and decided you can't find a good one anymore. The real problem was upstream: the old agency edge has been commoditized, and the leverage has moved to the inputs only the brand controls.
TakesIt always turns out to be a feed
OpenAI spent a year pitching conversational shopping, then quietly rebuilt something that looks a lot like Google Merchant Center. Every platform that monetizes shopping ends up needing the same thing first: a feed.
TakesAgentic commerce is here. Is your catalog ready for it?
Shoppers are starting to delegate research and purchase decisions to AI assistants. The brands that win will be the ones whose product data those agents can actually understand.
TakesAutomation commoditized everything except your feed
Google spent five years making paid search dramatically easier to run, which is exactly why it keeps getting more expensive to win. A classic Jevons paradox: automation standardized the edge brands used to build by hand. The one input it can't commoditize is your product feed.
GuidesWhat makes a product feed agent-ready
A practical checklist for turning a standard product feed into one that AI assistants and shopping agents can confidently surface and recommend.
TakesGoogle just told the market AI content isn't the moat. Structured product data is.
Google's official guide on optimizing for AI search quietly dismissed the llms.txt-and-content-variants playbook a whole vendor category was built on. For retailers, the moat isn't AI-optimized content. It's structured, machine-readable product data.
Customers$80M in incremental revenue last month, one optimization: the feed
Four 28-day Google Ads tests across a luxury house, a US department store, a global home retailer, and an athletic-wear brand. Every lift came from one place: the Google Merchant Center feed.
ProductThe score is not the outcome
Visibility scores are useful, but they're a means, not an end. Here's how Lily Max ties product intelligence back to revenue and ROAS.
GuidesPerformance Max for large catalogs, without the guesswork
PMax can be a black box. We break down how catalog-aware product intelligence makes it work for retailers with tens of thousands of SKUs.
TakesStripe is building the rails. Your product data decides who wins on them.
A day at Stripe Sessions made one thing unmistakable: agentic commerce has moved from interesting future to build now. Stripe is building the payment rails. The brands that win on them will already have their product data structured for agents.
TakesBrands are paying for bad product data twice now
Adobe says 34% of retail product pages can't be properly read by AI, even as the AI channel converts 42% better. The cost of thin product data used to be invisible. Answer engines just made it impossible to ignore.
CustomersHow a home brand grew agentic revenue 3x in a quarter
A look at how one home-goods retailer used product intelligence to become discoverable across AI assistants, and what changed in their numbers.
CompanyBuilding Lily Max: the engine behind every Lily product
A behind-the-scenes look at the architecture that connects product data, shopper intent, and channels into one continuously-learning system.
TakesRetail media beyond the dashboard
Dashboards report the past. The next generation of retail media has to optimize toward outcomes in real time. Here's our take.