How AI Search Is Recommending Online Dating: Monthly Trends

Executive Summary

Hinge remained the category leader in September 2026, holding a 74.6% valid recommendation coverage rate on the benchmark's primary metric. Across the two tracked months, the top of the market has held steady: Hinge led in both August 2026 (78.5%) and September 2026 (74.6%), with Bumble in second place in both months. The gap between the top two widened slightly, from 2.1 points in August to 3.0 points in September, driven by a larger decline at Bumble than at Hinge.

The most notable development this month was two significant declines. Bumble's valid recommendation coverage fell from 76.4% to 71.6%, a drop that stands out against an otherwise stable month. HER also posted a significant decline, falling from 34.1% to 27.8% — the largest single-brand movement in the category this month. No brand recorded a significant rise in coverage this month. The remaining eight tracked brands — Coffee Meets Bagel, eharmony, Grindr, Hinge, Match, OkCupid, Plenty of Fish, and Tinder — showed changes within the ordinary range of month-to-month movement.

Each monthly run begins with 800 prompt-surface observations (520 unique questions in August 2026; 525 in September 2026) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor; 794 were relevant and 6 were irrelevant in both months. The public metrics use the 716 qualified observations in August 2026 and 719 in September 2026 that survive both qualification stages.

Key Findings

Benchmark Context

The September 2026 report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set of 719 observations, up from 716 in August 2026.

Benchmark-Level Metrics

AI Recommendation Trend

Hinge Holds the Top Position as the Second Tier Tightens

Bumble and HER were the only two brands whose movement stood out from typical month-to-month variation, both declining — Bumble by 4.8 points and HER by 6.3 points. Hinge's lead over Bumble widened to 3.0 points even though Hinge's own coverage also declined, because Bumble fell further. OkCupid posted the largest gain, up 2.3 points, and Plenty of Fish rose 3.6 points, but neither move exceeded the range of ordinary fluctuation for the category.

What Changed This Month

Bumble: The Runner-Up Slips

Bumble's valid recommendation coverage fell 4.8 points from 76.4% in August 2026 to 71.6% in September 2026, a significant decline that widened the gap behind Hinge and narrowed the buffer ahead of the chasing pack.

The decline appears concentrated in recommendation placement rather than raw presence. Bumble's raw mention presence held nearly steady at 98.2% in September 2026 versus 99.2% in August 2026, a small change. The share of responses placing Bumble in the top three fell 2.6 points to 33.2%, but the sharpest signal was in first-position recommendations, which dropped from 2.2% to 0.3%.

The distinction to notice is between visibility and recommendation strength. Bumble remains one of the most widely mentioned apps in the category, but the rate at which AI systems put Bumble first fell from 16 first-place recommendations in August 2026 to just 2 in September 2026. The brand is still being discussed; it is being recommended first far less often.

Highest-priority diagnostic: Which prompt types shifted away from Bumble as a first-choice answer, and which competitor captured those first-position slots?

HER: A Significant Slide in Coverage

HER's valid recommendation coverage fell 6.3 points from 34.1% in August 2026 to 27.8% in September 2026, the largest single-brand movement in the category this month. HER's valid recommendation count dropped from 244 out of 716 qualified observations in August to 200 out of 719 in September.

The decline was driven more by breadth than by depth. HER's raw mention presence fell 4.9 points to 39.2%, while its top-three rate held essentially flat at 1.5% and its rank-one rate ticked up 0.3 points to 1.0%. In absolute terms, HER recorded 11 top-three and 7 first-place recommendations in September 2026, compared with 10 top-three and 5 first-place in August 2026, meaning the quality of its recommendations was stable while the overall volume of mention and recommendation activity narrowed.

The distinction to notice is that HER's issue in September 2026 was presence, not preference. When AI systems did recommend HER, they placed it in the top three at roughly the same rate as before. The decline came from fewer total mentions and fewer total valid recommendations.

Highest-priority diagnostic: Which prompt categories reduced their mention of HER, and what changed in the sources AI systems drew on for those answers?

OkCupid: A Modest Rise Toward the Third Spot

OkCupid recorded the largest upward movement of the month, climbing 2.3 points from 61.7% in August 2026 to 64.0% in September 2026, a move within the range of ordinary fluctuation. The rise was driven by a 4.0-point gain in raw mention presence to 81.2%, with OkCupid's valid recommendation count rising from 442 to 460.

The movement did not extend to placement quality. OkCupid's top-three rate fell 2.9 points to 12.9% and its rank-one rate slipped 1.4 points to 2.1%, both within normal variation. The brand's average recommended rank softened slightly from 4.15 to 4.28. OkCupid is being mentioned and recommended in more answers, but not necessarily in more prominent positions.

The distinction to notice is that OkCupid's September gain was a breadth story. The brand reached more conversations, but its position within those conversations did not improve.

Highest-priority diagnostic: Which surfaces or prompt types drove OkCupid's increased mention presence, and why did that presence not translate into higher placement?

Plenty of Fish: A Presence Gain Without a Placement Breakthrough

Plenty of Fish's raw mention presence rose 5.8 points, from 33.1% in August 2026 to 38.9% in September 2026. The brand's valid recommendation coverage rose 3.6 points to 27.3%, a move within normal variation. Plenty of Fish's mention count rose from 237 to 280 while its valid recommendation count grew from 170 to 196.

The presence gain did not produce equivalent gains in recommendation quality. Plenty of Fish's top-three rate edged up to 8.6%, and its rank-one rate rose to 3.9%, both modest moves. The brand continues to appear in more conversations but holds a similar position within them, with an average recommended rank of 4.39.

The distinction to notice is that Plenty of Fish's September gain was primarily a visibility gain — more mentions across the surface set — without yet a comparable rise in top-three or first-place placements.

Highest-priority diagnostic: Which prompt categories drove Plenty of Fish's mention gain, and what would need to change for those mentions to convert into top-three recommendations?

A Narrowing Gap Between HER and Plenty of Fish

The September 2026 data shows a notable repositioning at the lower end of the category. HER held a 10.4-point coverage advantage over Plenty of Fish in August 2026 (34.1% versus 23.7%), but that gap narrowed to just 0.5 points in September 2026 (27.8% versus 27.3%). The shift came from both directions: HER declined 6.3 points while Plenty of Fish rose 3.6 points.

This convergence is a category observation about how quickly relative positions can change when one brand loses coverage and another gains it. HER's decline was significant while Plenty of Fish's rise was not, but the combined effect compressed a double-digit gap into near-parity in a single month. Both brands now sit in a cluster with Grindr and Coffee Meets Bagel between roughly 23% and 30% coverage.

The distinction to notice is that this is not a case of one brand taking share from another. HER lost coverage across its mention base while Plenty of Fish gained mention presence independently. The two trends converged by coincidence of direction rather than direct substitution.

Highest-priority diagnostic: Whether the prompts where HER lost presence are the same prompts where Plenty of Fish gained it, or whether the two movements occurred in different parts of the query landscape.

Buyer-Intent Interpretation

In September 2026, all 719 qualified observations fell into the Brand Recommendation cluster. No qualified observations were recorded for the Pricing & Value or Multi-Brand Comparison clusters in either August or September 2026. The benchmark therefore measures which apps AI systems recommend when a user asks for a recommendation, but it cannot yet answer commercial questions about price perception, subscription value, or direct head-to-head comparisons. Those questions represent a distinct and currently unmeasured layer of the AI-driven buyer journey.

Brand Opportunity Summary

The benchmark identifies where attention is warranted across the category; a company-level analysis is needed to explain why those movements occurred and what they signal for each brand's AI visibility strategy.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations capturing the query, the AI surface that answered it, the recommendation outcome, the rank of each brand mentioned, sentiment signals, and citations where the surface exposed them. Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns to explain the movements behind these aggregate figures. Presence in an AI answer is not automatically treated as proof of causation.

Methodology and Standards

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• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Interpretation Notes

• The qualified benchmark set (719 observations in September 2026) differs from the raw collection universe (800 prompts). Brand-level percentages are calculated only within the qualified set.
• Small counts matter: Bumble's rank-one rate of 0.3% represents just 2 observations out of 719, compared with 16 out of 716 in August. Such counts are valid signals but should be read with their absolute size in mind.
• These movements identify where attention is warranted. A change between two months does not by itself establish the cause of that change.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

The aggregate percentages in this report raise the questions that matter for strategy. Which high-intent prompts is a brand winning, and which is it losing? When a brand loses a recommendation, which competitor takes its place? What attributes do AI systems associate with each option, and which external sources are shaping those answers? These questions sit beneath the movement in coverage rates and cannot be answered from the aggregate data alone.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It turns the benchmark's signal into a concrete plan for where and how to improve a brand's position across the AI search landscape.

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