Amazon Is a Search Engine Now: What That Means for Every Store That Isn't Amazon

Product search increasingly starts on a marketplace, not a search engine

Multiple independent survey houses converge on the same direction, even where they disagree on the exact number. eMarketer puts the share of US consumers beginning product search on Amazon at roughly 61 percent. A Jungle Scout-commissioned Amazon Advertising Report puts it as high as 74 percent. Other cited surveys land in the 55 to 63 percent range. A widely cited breakdown attributes close to half of US shoppers starting on a search engine like Google, roughly 32 percent starting on Walmart.com, and a growing roughly 11 percent starting on TikTok, figures that overlap because shoppers use more than one starting point across different purchases.

The spread between 55 and 74 percent across surveys is wide enough that no single number should be repeated as settled fact. What every survey agrees on is the direction: Amazon rivals or exceeds Google as the first place a US shopper looks for a product, which was not true a decade ago and would have sounded implausible even five years ago.

This does not make Google or your own site obsolete, it adds a shelf

The reframe is not "move everything to Amazon." It is that a shopper's attention is now split across at least three distinct surfaces that did not used to compete with each other: a general search engine, a marketplace's own internal search, and increasingly a generative AI answer. Adobe's first-party analytics panel shows AI-referred traffic to US retail sites up 393 percent year over year in Q1 2026, converting 42 percent better than average traffic that same month, a channel that barely registered two years ago and is now performing.

A DTC brand competing only for Google rankings is now optimizing for one of at least three surfaces where its buyers actually start looking. The practical implication is not choosing one surface over the others. It is making sure your product data, feed and schema are structured well enough to be legible on all three at once, since the underlying data that qualifies a product for Google's product graph, GTIN, attributes, accurate pricing, is largely the same data that qualifies it to be named in an AI shopping answer.

What actually earns placement inside Amazon's own search

Amazon's own ranking system, commonly referred to by its internal name A9/A10, weighs a distinct set of signals from Google, including sales velocity, conversion rate on the listing itself, and Amazon-specific keyword relevance in the title and backend search terms, a discipline with its own specialists and its own body of practice. Being clear about scope matters here: engineering a store's own site, its Google product graph eligibility and its AI-shopping-surface visibility is a different, though related, discipline from running a dedicated Amazon marketplace listing optimization program, and a store treating them as identical work is likely to do a mediocre job of both.

The state of the multichannel evidence

Marketing content commonly cites specific figures claiming multichannel sellers earn substantially more revenue than single-channel sellers, and that owned-store-plus-marketplace sellers see meaningfully higher margins than marketplace-only sellers. Those specific percentages, as commonly repeated, trace to marketing-vendor blog content without a disclosed underlying study, and should not be treated as settled fact. The general economic logic behind them, that depending on a single sales channel concentrates both discovery risk and marketplace-toll cost in one place, is plausible and consistent with ordinary retail economics, but it deserves to be stated as reasoning, not quoted as a verified statistic.

Building for all three shelves at once

The practical takeaway is not a dramatic pivot. It is treating owned-surface visibility, being found on your own site through Google's product graph and named in AI shopping answers, and a clean, competitive presence anywhere else you sell, as complements that share the same underlying data foundation rather than as alternatives competing for the same budget. The store that gets its feed, schema and identifiers right once benefits everywhere that data is read.