The $714,000 question
Here's what it costs to tell you which TV to buy: $714,000 a year just in product purchases. That's 618 different products — TVs, monitors, headphones, soundbars, running shoes, mattresses — all bought at retail price, like a normal consumer. No manufacturer samples. No sponsored placements. No review units that arrive pre-configured and hand-selected. And that $714,000 doesn't include the engineers who design the tests, the technicians who run them, the writers who interpret the data, or the facility that houses the equipment. Behind every response time chart and color gamut measurement on RTINGS.com is an actual human being making sure the numbers are right [2]. For over a decade, this model worked. RTINGS produced the most granular, standardized, comparable product testing data on the internet, and Google sent people to it. Search traffic generated ad impressions and affiliate clicks, and the revenue funded the next round of testing. It was a virtuous cycle that rewarded doing genuinely useful, rigorous work. That cycle is broken now.
What AI actually did
The problem isn't just that AI companies scraped RTINGS' data to train their models — though they did. The more immediate crisis is what happens at the search layer. When you Google "best TV for gaming 2026," the first thing you see isn't a link to RTINGS. It's an AI Overview: a generated summary that synthesizes information from multiple sources and presents it as a clean, confident answer. Below that are sponsored results and product listings. Organic search results — the actual websites that did the work — are pushed to the bottom of the page [2]. Even when RTINGS ranks first organically, fewer people click through because the AI summary already answered their question. From the consumer's perspective, this is convenient. You get a quick answer without navigating ad-heavy websites. But that convenience has a cost that most people never see.
