Etsy AI Market Strategy Report - Make Money Online

Answer Capsule

Etsy holds meaningful presence in AI-generated recommendations across the Make Money Online category, appearing in 37.10% of qualified observations in September 2026, but converts only 25.00% of those observations into valid recommendations. The benchmark shows Etsy is present but under-recommended, with a top-three rate of 4.03% and a rank-one rate of 0.54%, placing it eighth among ten tracked brands. Its clearest win is a positive framing profile with zero negative mentions, while its clearest weakness is weak recommendation conversion relative to its presence. The clearest opportunity lies in converting its strong visibility base into recommendation credit by strengthening the evidence sources AI systems draw on when forming shortlists.

Who This Report Is For

This report is for Etsy's marketplace, growth, and brand strategy teams tracking how AI systems recommend the platform when buyers ask where to make money online.

Report Card

Executive Summary

Etsy is visible but under-recommended in the Make Money Online category. The September 2026 LLM Authority Index benchmark shows Etsy present in 138 of 372 qualified observations, a raw mention presence rate of 37.10%, yet the platform received only 93 valid recommendations, a coverage rate of 25.00%. That gap between presence and recommendation conversion is the central finding of this report.

The sentiment picture is clean. Etsy recorded 120 positive mentions, 18 neutral mentions, and zero negative mentions, producing a net sentiment score of 0.8696. No AI surface framed Etsy negatively in the qualified set. The issue is not how Etsy is described when mentioned; it is whether Etsy is chosen at all.

Etsy's strongest platform signal came from Gemini, where it reached a valid recommendation coverage of 31.58% and a top-three rate of 21.05%, its best placement performance across all tracked surfaces. Its weakest platform signal came from ChatGPT, where Etsy appeared in only 11.54% of observations and received no top-three or rank-one recommendations.

The clearest cluster gap is structural. All 372 qualified observations in September fell into the Brand Recommendation class, meaning the benchmark measured which brand AI systems recommend when buyers ask directly. Etsy's 25.00% coverage in that class shows it is frequently mentioned as context but less frequently selected as the answer.

What Etsy Is Winning

Questions This Section Answers

• What is Etsy's cleanest strength in AI-generated recommendations?
• Where did Etsy show its strongest platform-level recommendation performance?
• How has Etsy's recommendation coverage moved over the benchmark series?

Etsy's cleanest win is its framing profile. The platform recorded zero negative mentions across all tracked AI surfaces in September 2026, a distinction shared with only a few competitors in the category. When AI systems reference Etsy, they do so positively or neutrally, never as a cautionary example.

Gemini represents a narrow but meaningful recommendation pocket. On that platform, Etsy achieved a valid recommendation coverage of 31.58%, a top-three rate of 21.05%, and an average recommended rank of 3.0. This is Etsy's strongest platform-level performance and suggests the platform's evidence layer resonates with at least one major AI surface.

Etsy also showed upward momentum in the benchmark series. Valid recommendation coverage rose from 19.6% in July 2026 to 25.0% in September 2026, a gain of 5.4 points. The platform remains modestly above its July baseline despite an August spike that has since receded.

Where Etsy Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why does Etsy's recommendation conversion lag its presence?
• Which platform shows the clearest gap between Etsy's presence and its recommendation credit?
• How does Etsy's placement performance compare with competitors in the category?

The core gap is recommendation conversion. Etsy appears in 37.10% of qualified observations but is recommended in only 25.00%, meaning a substantial share of its mentions do not convert into recommendation credit. Competitors with similar or lower presence convert more effectively. Swagbucks, for example, holds a presence rate of 68.82% and a coverage rate of 50.00%, while Upwork converts 79.84% presence into 56.45% coverage.

Placement is a second gap. Etsy's top-three rate of 4.03% and rank-one rate of 0.54% place it near the bottom of the tracked field. The platform received only 15 top-three placements and 2 rank-one placements across 372 observations. When Etsy is recommended, it tends to appear lower in the shortlist rather than as the default answer.

ChatGPT is the clearest platform gap. Etsy appeared in only 6 of 52 observations on that surface, received no top-three or rank-one recommendations, and recorded zero valid recommendation credit. Copilot shows a similar pattern: Etsy was present in 21 of 48 observations but received no top-three, rank-one, or top-ten placements on that surface.

Biggest Opportunity

Questions This Section Answers

• What is the clearest opportunity for Etsy in AI recommendations?
• Why is Copilot the most direct target for converting presence into recommendation credit?

The clearest opportunity is converting Etsy's existing presence into recommendation credit on the surfaces where it is currently mentioned but not selected. Copilot is the most direct target: Etsy appeared in 43.75% of Copilot observations but received no ranked recommendations at all. That presence without conversion suggests AI systems recognize Etsy as relevant context but do not yet treat it as a shortlist answer. Strengthening the owned answer layer and citation architecture around Etsy's selling and earning use cases could shift those mentions from contextual references into valid recommendations.

Competitive Landscape

Questions This Section Answers

• Which brands lead the Make Money Online category in recommendation-stage positions?
• Where does Etsy rank among the tracked field, and how do its placement metrics compare?

Upwork and Fiverr hold the strongest recommendation-stage positions in the Make Money Online category, with Upwork leading at 56.45% valid recommendation coverage and Fiverr close behind at 54.57%. Etsy sits eighth in the tracked field, behind the leaders and several mid-field brands that convert presence into recommendation credit more effectively.

Average recommended rank covers rank-eligible recommendations only.

Etsy's top-three rate of 4.03% and rank-one rate of 0.54% sit well below the category leaders. The table shows that Etsy's sentiment is competitive with the field, but its placement metrics lag most tracked brands, confirming that the gap is recommendation conversion rather than framing quality.

Prompt Evidence

Gemini / Brand Recommendation Prompt: "What is the best legit survey site?" Result: Etsy received a valid recommendation with a top-three placement, contributing to its strongest platform-level coverage on Gemini.

ChatGPT / Brand Recommendation Prompt: "What are some legit surveys for money?" Result: Etsy was mentioned but received no ranked recommendation, reflecting its pattern of presence without conversion on ChatGPT.

Google AI Overviews / Brand Recommendation Prompt: "What app pays you real money?" Result: Etsy appeared as a neutral or positive reference but did not convert into a top-three or rank-one recommendation on this surface.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map the specific prompts where Etsy is mentioned but not recommended, identifying which high-intent queries produce contextual references instead of shortlist placement.

Phase 2: Recommendation Readiness Plan Prioritize the surfaces and prompt clusters where Etsy's presence is highest but conversion is weakest, starting with Copilot and ChatGPT.

Phase 3: Owned Answer Layer Buildout Develop owned content that directly answers make-money-online prompts with Etsy as the recommended option, giving AI systems clear material to cite.

Phase 4: Citation / Authority Layer Development Strengthen the external source footprint that AI systems draw on when forming recommendations, focusing on third-party coverage that positions Etsy as a legitimate earning platform.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track Etsy's presence, recommendation coverage, placement, and sentiment monthly to measure whether the gap between visibility and recommendation credit is closing.

Why This Matters

AI-generated recommendations are becoming the shortlist moment for buyers deciding where to make money online. Etsy is part of the conversation, appearing in more than a third of qualified observations, but it is not consistently the answer. Presence alone does not put a brand on the buyer shortlist; recommendation credit does.

The next move for Etsy is targeted correction of the prompt, page, and citation layers. The platform's positive framing gives it a clean foundation. The work is converting that favorable visibility into valid recommendations and higher placement, particularly on surfaces where Etsy is already mentioned but not selected.

Core Metrics

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Etsy, the calculation is (120 × 1 + 18 × 0 + 0 × -1) / 138, producing a net sentiment score of 0.8696.

This score matters because unclassified mention counts are misleading. A raw mention total treats a positive recommendation, a neutral reference, and a cautionary mention as equal signals, which distorts any visibility analysis. Share of voice is a diagnostic metric, not a business KPI; appearing often means little if those appearances do not translate into recommendation credit. A positive recommendation, neutral reference, cautionary mention, and competitor-displaced mention are not equal in commercial value. Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, because it separates how a brand is framed from how often it is chosen.

Sentiment by Platform

Methodology

1. Report orientation: This is a benchmark-based analysis of Etsy's AI recommendation visibility in the Make Money Online category, drawn from the LLM Authority Index AI Market Discovery Index and CiteWorks Studio interpretation. It is not a client implementation case study.
2. Reporting window: Data reflects September 2026, with baseline comparisons to July 2026 where available.
3. Platforms tracked: ChatGPT, Copilot, Gemini, Perplexity, Google AI Overviews, and Google AI Mode.
4. Observation count: 372 qualified benchmark observations in September 2026, derived from 800 source prompt-surface observations.
5. Competitor universe: Amazon, Etsy, Fiverr, InboxDollars, Rover, Shopify POS, Survey Junkie, Swagbucks, TaskRabbit, and Upwork.
6. Public clusters used: All qualified observations fell into the Brand Recommendation buyer-intent class. No qualified observations fell into Pricing and Value or Multi-Brand Comparison classes.
7. Stage 0 role: Raw prompt-surface observations were collected across the surface universe, deduplicated into unique questions, filtered for relevance, and qualified into the public benchmark denominator.
8. Definition of a mention: A brand mention is any qualified observation where the brand appears in the AI response, regardless of whether it is recommended.
9. Definition of a valid recommendation: A valid recommendation is a qualified observation where the brand receives explicit recommendation credit, distinct from a neutral reference or contextual mention.
10. Limitations: Small observation counts for individual brands mean single-prompt shifts can move percentages. The public benchmark does not measure market share, sales attribution, organic-search ranking positions, or causality from metric movement alone. Source presence is evidence about the information environment, not proof that a source caused a recommendation.

See How AI Is Recommending Your Brand

The benchmark shows where Etsy wins and loses recommendation credit across AI surfaces. A company-level AI visibility audit goes deeper, mapping the specific prompts, competitors, and evidence sources shaping those outcomes. Understanding which queries produce mentions instead of recommendations is the first step toward converting visibility into shortlist placement.