Tested how brands surface to AI shopping agents with Muse

Olivia Moore@omooretweets

If I was a brand or retailer, AI discoverability / agentic commerce would be my top priority right now.

And, there's an extremely easy and free way to get a sense of how you "show up" to agents. 👇

First, create a dummy account on all the agent platforms (Muse, Instinct, Dots, etc.) Sign up with a fresh email that does not have context on your real identity, or even use a VPN to "go" to where your average user is!

Then, ask the agent to perform a search that you'd want your product / platform to show up in. As an example, I prompted: "find me a winter coat for SF." Watch the agent go through the evaluation process (you can literally view the browser), and at each stage ask it questions like:

- How did you identify the initial set of options for this search? What were your sources?
- Were there any failures / blocks you encountered that eliminated any options?
- What were the exact variables that your ultimate ranking or recommendation was driven by?

Follow the process all the way through to the point of purchase. You will very quickly start to get a sense of how an agent thinks, edge case issues it runs into, etc. As an example, during my winter coat search via Muse I learned the following:

- Patagonia bot blocked my agent - so Muse then went to / recommended other retailers that carried the jacket to make my purchase
- The agent first searched options from its training data, largely informed by Wirecutter-style roundups, Reddit, and enthusiast forums. Then, it looked at connected merchants via the Meta Catalog. Then, it did live browser searches. It dropped any websites with SEO spam or fake reviews
- REI was the ultimate winner as it didn't throw up any bot challenges or traffic blocks, and my agent prioritized verifiable inventory and same-day pickup (which I didn't ask it to!). It found a discount on REI vs. the original retailer so prioritized that as well