How Faire Became the Leading Wholesale Marketplace in AI Answer Engines

The Challenge

With wholesale purchasers increasingly turning to LLMs for answers, Faire wanted to make sure they were showing up for the right queries. No AEO methodology existed yet to get them there, starting this as a pilot with no defined playbook. 

Right when the effort needed a driver, internal ownership was thin with the team member responsible for organic search about to go on leave. Every foundational question was still open - which tools to trust, which metrics mattered, how to find and convince the right publishers to participate, what a sensible budget even looked like.

Measurement made it harder. AEO offers almost no clean attribution, and a single tool couldn't isolate the lift from an individual placement. The team needed a way to prove page-level impact, not just watch aggregate numbers move.

Faire brought the project to Hamster Garage for one reason: HG had the publisher relationships and outreach process to get real content placements live, and to turn each one into a learning the program could build on.

The Strategy

With no internal AEO program and no proven way to build one, Faire brought the challenge to Hamster Garage. The reasoning was simple: earning citations in AI answers is fundamentally an earned-media problem, and HG already had the publisher relationships, the outreach engine, and the affiliate expertise to get real content live and learn from it fast. Rather than run a one-off campaign, HG set out to build a repeatable system Faire could scale. The work broke into four components.

1. A repeatable placement procurement engine. HG standardized every deal into the same five steps: prospect, qualify, pitch, incentivize, and execute. Because AEO had no established playbook, a documented process would compound learnings and scale far better than scattered wins. In practice, HG sourced high-visibility pages and domains in Profound and Scrunch, qualified each for topical fit and citation influence, pitched a tailored partnership, and ran the deal through briefing, publishing, and payment.

• Positioned the outreach as distinct from a traditional affiliate deal, which lifted response rates with publishers new to AEO
• Tightened targeting by job title in Apollo to reach the right decision-makers
• Kept a single upfront incentive and a lightweight flow (incentive, draft, revisions, publish, pay) to cut publisher friction

2. Cohort-based targeting that sharpened over time. HG ran outreach in four sequential cohorts so the strategy could start with the fastest wins and widen as evidence came in. Cohort 1 optimized pages already earning citations to lift Faire's ranking in content the models trusted. Cohort 2 pursued net-new articles on high-authority domains for high-intent questions Faire was missing. Cohort 3 used a Profound gap analysis to find the domains winning citations in Faire's weakest topics, then went wide.

• Targeted 41, 40, and 64 domains across the three cohorts
• Pivoted from a broad net to topic-level targeting once per-placement lift was proven

3. Dual-tool measurement to prove lift placement by placement. Attribution is the hardest part of AEO, so HG refused to rely on one source. Profound was the source of truth for page-level lift, tracking each procured URL day over day, while Scrunch gave faster reads between Profound's roughly two-and-a-half-week refresh. Comparing the two separated real movement from platform noise.

• Built automated Profound workflows to watch every procured page
• Ran a controlled before/after test with matched time windows to isolate placement-driven lift
• Used the methodological difference between the tools to interpret discrepancies rather than be misled by them

4. An affiliate-led approach to emerging channels. This is where the program got ahead of the curve. Rather than assume more blogs were the answer, HG analyzed where AI actually pulls citations across YouTube, Reddit, Facebook, and LinkedIn. YouTube stood out, driving citation volume equal to roughly 32% of what Faire.com generates, but those citations were fragmented across a long tail of small creators rather than concentrated in a few. That reframed the opportunity: the way to win a fragmented channel is to recruit many creators at once, which is exactly what an affiliate influencer program does, and exactly where HG is strongest.

• Turned the channel analysis into the blueprint for affiliate-led influencer recruitment
• Planned to leverage existing influencer partnerships and the Faire affiliate program to scale content, rather than negotiate one placement at a time

The Results

Over the program's first months, from December 2025 to April 2026, Faire's AEO performance strengthened at every level, from individual placements to its standing across the entire category.

Placement level. Hamster Garage's long-tail placements started earning citations the pages weren't getting before. The pattern repeated across the pages HG procured, though not uniformly:

‍Table 3. Placement performance, responses and prompts cited in, before and after go-live.

The flagship page led the group, with responses up 781% after going live. Three of four early placements posted solid gains; one older home decor listicle declined over the same window. That contrast was useful. It steered the team toward optimization and net-new formats and away from what wasn't working.

To rule out seasonal noise, HG ran a controlled comparison of matched three-week windows across four placements: together they went from 2 prompts to 28, a net gain of 26. The flagship page alone appeared across 14 prompts and generated 32 citations in the target window.

These placements are not standalone wins. Each is representative of a pattern that repeated across the pages HG procured. On its own, any single page moves a small number, and that is the nature of the long-tail approach as much as its strength. The lever is cumulative: many modest, defensible gains, stacked across dozens of pages, are what compound into movement at the category level. No one placement carries the result; the combined weight of them does.

Category level. That compounding shows up in Faire's standing across the category:

Table 4. Category-level visibility across Profound and Scrunch.

What these mean:

• AI visibility: the share of relevant AI responses that mention Faire at all
• Share of voice: Faire's slice of total brand mentions in that space, always lower than visibility even for a leader
• Average position: where Faire tends to appear in a response, with 1 being first
• Top-brands presence: how often Faire shows up among the leading brands cited (Scrunch)
• Citation share: the portion of all citations that point to Faire (Scrunch)

Worth noting: these category-level gains reflect HG's placements working alongside Faire's own SEO investment over the same period, so they're best read as a combined effort. The placement-level results stand on their own, and together they make the case for long-tail partners in AEO: individually modest, collectively decisive.

Growth Summary

This case study shows that visibility in AI answer engines can be earned deliberately, not left to chance. Starting from no program at all, Hamster Garage built a repeatable placement engine, sharpened it through cohort-based targeting, and validated every result with dual-tool measurement, turning an unproven channel into a system that reliably lifts the pages it touches.

The growth showed up where it counts. A single optimized placement went from not previously cited to 32 citations in the controlled window, and reached 24 prompts and 193 responses per month by March, with its influence score climbing roughly 13x. Across the wider set, three of four early placements posted measurable gains, and a controlled test confirmed the lift with a net gain of 26 prompts. At the category level, Faire holds the top position in AI visibility, share of voice, and average position, ahead of every competitor. Those results are the proof point: long-tail placements, run as a disciplined and measurable system, are what move a brand to the top of the AI answer.