Virtual Receptionist Services: AI Market Discovery Index

Benchmark Summary

Ruby led the Virtual Receptionist Services benchmark in September 2026 with valid recommendation coverage of 50.0%, down from 69.9% in July 2026. The gap to the next brand was 0.9 percentage points over Smith.ai at 49.1% in September 2026, down from 56.6% in July 2026.

The month saw broad declines across seven tracked brands, with no significant risers. The largest single-month coverage decline was AnswerConnect at 40.6% in September 2026, down 8.6 percentage points from 49.2% in August 2026. Ruby declined 7.8 percentage points to 50.0% in September 2026 from 57.8% in August 2026, and Abby Connect declined 7.2 percentage points to 21.8% in September 2026 from 29.0% in August 2026.

Since July 2026, every leader has declined in each of the two subsequent months. Ruby declined 19.9 percentage points across the series, AnswerConnect declined 22.8 points, and Abby Connect 19.1 points. PATLive, Smith.ai, and Conversational were stable within normal month-to-month variation.

The benchmark began with 800 prompt-surface observations in each month and produced 330 qualified observations in September 2026 after qualification.

Current Benchmark at a Glance

August 2026 sat between these two months, with 303 qualified observations and a recommendation-shaped answer share of 43.6%.

Qualified surface breadth counts the six canonical AI/search surface families with at least one qualified observation; these families are ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Virtual Receptionist Services

Research Scope and Qualification

The public benchmark is narrower than the raw collection universe by design.

Brand-level percentages use the qualified observations as the public denominator, not the raw collection. AI Market Discovery Methodology

Current Brand Standings

Sorted by valid recommendation coverage.

Ruby's coverage lead is real, but Smith.ai leads on first-choice preference by a wide margin despite near-equal coverage. Ruby's rank-one rate of 10.0% is roughly half of Smith.ai's 18.5%.

How to Read the Standings

Presence rate is the share of qualified observations where a brand appears anywhere in the response. Valid recommendation coverage is the share of qualified observations where a brand appears in a valid recommendation shortlist, which is the primary benchmark metric. Top-three rate is the share of observations where a brand appears among the top three recommended options. Rank-one rate is the share of observations where a brand is recommended first. Net sentiment is the positive minus negative mention balance divided by total mentions, ranging from 0 to 1.

For formulas and denominator rules, see AI Market Discovery Metric Definitions

Recommendation Coverage Movement

Seven of ten brands recorded significant two-month coverage declines, while no brand improved. PATLive, Smith.ai, and Conversational moved within normal month-to-month variation. In the most recent month, Moneypenny declined 6.9 percentage points to 10.6% in September 2026 from 17.5% in August 2026. Nexa held roughly steady in the most recent month, recording 6.4% in September 2026 versus 6.9% in August 2026, continuing its two-month decline from the July 2026 baseline of 14.0%.

Largest Decline: AnswerConnect

AnswerConnect recorded the largest two-month decline in the benchmark at 22.8 percentage points, from 63.4% to 40.6% in valid recommendation coverage between July 2026 and September 2026. The brand declined in each of the two months since July 2026. The decline was supported by drops across other metrics: presence rate fell 17.9 percentage points to 54.9% in September 2026 from 72.8% in July 2026, top-three rate fell 21.2 percentage points to 31.8% from 53.0%, and rank-one rate fell 18.1 percentage points to 14.2% from 32.3%. Net sentiment was 0.86 in September 2026, compared with 0.92 in July 2026.

Significant Declines Across the Category

Ruby declined 19.9 percentage points to 50.0% in September 2026 from 69.9% in July 2026, with top-three rate falling 16.3 percentage points to 38.2% from 54.5%. Abby Connect declined 19.1 percentage points to 21.8% from 40.9%, with presence rate falling 18.3 percentage points to 26.1% from 44.4%. Moneypenny declined 18.4 percentage points to 10.6% from 29.0%. Davinci Virtual declined 11.9 percentage points to 4.2% from 16.1%. Nexa declined 7.6 percentage points to 6.4% from 14.0%. Posh Virtual Receptionists declined 6.8 percentage points to 15.4% from 22.2%.

These declines are broad-based rather than isolated to one brand, suggesting a category-level shift rather than a single competitive loss.

Category Leader: Ruby

Ruby remained the category leader in September 2026 with valid recommendation coverage of 50.0%, down from 69.9% in July 2026. Ruby also led presence rate at 80.9% in September 2026, down from 85.0% in July 2026. The gap to Smith.ai narrowed to 0.9 percentage points from 13.3 points in July 2026, meaning Ruby's leadership position is now marginal.

Recommendation Placement Snapshot

Coverage alone does not show how prominently a brand is recommended. Among the three brands with the highest coverage in September 2026, Smith.ai had the highest rank-one rate at 18.5%, ahead of AnswerConnect at 14.2% and Ruby at 10.0%.

Smith.ai and Ruby show how close coverage can still hide different first-position rates: Ruby edged Smith.ai on coverage at 50.0% versus 49.1% in September 2026, but Smith.ai held a higher share of first-position recommendations at 18.5% versus 10.0%.

Buyer-Intent Distribution

All qualified observations in both months fell into the brand recommendation class of discovery and consideration.

The current public series measures brand recommendation discovery only; pricing, value, and multi-brand comparison questions have no qualified signal in this benchmark. This limits what the data can say about later-stage buying decisions.

Historical Measurement Record

Evidence and Source Layer

The benchmark is built from prompt-level observations that retain the query, AI/search surface, answer, brand outcome, recommendation placement, sentiment, and, where exposed, citations or attributable evidence sources. Source presence is evidence about the information environment. It is not automatically proof that the source caused the recommendation.

Scope Boundaries

This public benchmark does not measure market share, attributable sales, every possible AI response, organic-search ranking, social mention volume, or private and sponsored channels. A movement in a metric alone does not establish causality. The two-month decline pattern should not yet be treated as a confirmed trend.

About This Benchmark

The LLM Authority Index AI Market Discovery Index tracks how prominently brands appear in AI-generated recommendations across major AI and search surfaces. New measurements are added to the same evergreen report.

• AI Market Discovery Methodology
• AI Market Discovery Metric Definitions
• AI Market Discovery Research Standards
• Modeled AI Authority Value

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