How AI Search Is Recommending Chatbots: Monthly Trends

Executive Summary

Intercom is now the category leader in AI search recommendations, holding valid recommendation coverage of 67.4% in October 2026. The race at the top has tightened: Tidio sits second at 61.2%, a gap of 6.2 points, while Zendesk Chat holds third at 44.0%. Intercom's 67.4% coverage is more than three times the fourth-placed LiveChat (Text S.A. (formerly LiveChat Software S.A.)) position at 27.3%.

Intercom is also the strongest riser across the full series on an absolute-points basis among brands not affected by the tracking split, with coverage up 16.6 points from 50.8% in July 2026 to 67.4% in October 2026, a gain that also held up against the prior month (up 9.0 points from 58.4% in September 2026). Tidio follows closely, up 17.3 points from 43.9% in July to 61.2% in October, extending an upward streak to three consecutive months. Both brands now sit well clear of the rest of the field.

The sharpest decliner against the baseline is Zendesk, down 50.8 points from 50.8% in July 2026 to 0.0% in October, with its coverage now reported under Zendesk Chat at 44.0%. LiveChat shows the same pattern, down 17.2 points from July to 0.0%, with its coverage appearing under the LiveChat (Text S.A. (formerly LiveChat Software S.A.)) entity at 27.3%. These are tracking-change effects rather than disappearance from AI answers.

Measured against the prior month, the category's overall pattern was mixed rather than uniformly stable: Intercom's rise to the lead was itself a significant month-over-month gain, and LiveChat (Text S.A.) also posted a significant month-over-month increase. Most of the remaining field, including Tidio and Zendesk Chat, moved within normal variation in October. Freshdesk remained the largest full-series decliner among brands unaffected by the tracking split, down 3.7 points from 23.7% in July to 20.0% in October, though that movement also stayed within normal variation.

Each monthly run begins with 800 prompt-surface observations across the benchmark's defined AI/search surface universe. Unique questions were 497 in July 2026, 575 in August, 551 in September, and 553 in October 2026. All 800 observations mentioned a tracked brand or competitor in each month. Relevant prompts were 719 in July, 732 in August, 661 in September, and 648 in October; irrelevant prompts were 81, 68, 139, and 152 respectively. The public metrics use the observations that survive both qualification stages: 476 in July 2026 and 436 in October 2026, with 500 in August and 437 in September as intermediate months.

Key Findings

AI Response Inconsistency Alerts

Questions This Section Answers

• Which AI platforms gave conflicting answers about chatbot pricing and market status in October 2026?
• What are the specific factual conflicts around Intercom, Chatfuel, Drift, and ManyChat?

The benchmark detected 5 critical or high-severity factual inconsistencies in October 2026, spanning 4 AI platforms: ChatGPT, Copilot, Gemini, and Google AI Mode. Each conflict below involves a factual claim where two platforms provided incompatible answers to the same question.

Intercom

AI platforms provided conflicting information about Intercom's pricing model. When asked "What is AI chatbot for customer service?", Google AI Mode stated that Intercom Fin is priced per seat at $29/seat/mo, while Copilot stated it is priced per resolution at $0.99. These are incompatible pricing models for the same product. Google AI Mode cited IBM, Kayako, and Salesforce source pages, while Copilot cited Technova Partners, Rasa, and Axis Intelligence. Three sources on the Copilot side were flagged: a Technova Partners page describing Intercom Fin at $39/seat/month plus $0.99/resolution, a Twig page describing it at $0.99/resolution, and a Rasa page also describing it at $0.99/resolution.

AI platforms also differed on Intercom's monthly starting price. When asked "What is the best chat integration for website?", Gemini stated that Intercom starts around $39 to $74+ per month depending on volume and features, while ChatGPT stated $29/seat/month plus $0.99 per Fin outcome. Gemini cited SupportBee, HeroThemes, and Kayako, while ChatGPT referenced Intercom's own help documentation on deploying the Fin AI Agent.

Chatfuel

AI platforms provided conflicting information about Chatfuel's starting price. When asked "Is there a cheaper version of ManyChat?", ChatGPT stated Chatfuel costs approximately $49/mo annually, while Gemini stated plans start around $14.99/month to $39/month. These ranges do not overlap. ChatGPT cited ManyChat's pricing page and a SendPulse blog, while Gemini cited Setsmart, InstantDM, and ManyChat's own blog. A SendPulse source page on the ChatGPT side was flagged for the $49/mo figure, and an InstantDM page on the Gemini side was flagged for the $14.99/mo figure.

Drift

AI platforms provided conflicting information about Drift's market status. When asked "Who competes with intercom?", Gemini described Drift (by Salesloft) as a current Intercom competitor designed for sales-driven B2B enterprise teams, while Copilot stated Drift is sunsetting in 2026 and may exit the market. Gemini cited Cosupport, Decagon, and Tooltester, while Copilot cited Help Scout, Zapier, and Toolchase. A Toolchase source page on the Copilot side was flagged for the statement that Drift was sunset by Salesloft in March 2026 and that Drift.com now forwards to Salesloft.

ManyChat

AI platforms provided conflicting information about ManyChat's Pro plan price. When asked "Is there a cheaper alternative to Manychat?", ChatGPT stated ManyChat Pro starts at $29/mo on an annual basis, while Google AI Mode stated the Pro plan starts around $15/month. ChatGPT cited ManyChat's pricing page, SendPulse, and Chatfuel SDK, while Google AI Mode cited a Reddit thread, ManyChat's blog, and ReplyKaro. A ReplyKaro source page on the Google AI Mode side was flagged for the $15/mo figure.

Benchmark Context

Questions This Section Answers

• What separates the raw collection universe from the qualified benchmark set used for brand-level chatbot metrics?
• How did the qualified observation base and recommendation-shaped answer share change between July and October 2026?

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

The qualified observation count eased from 476 in July 2026 to 436 in October 2026, with August at 500 and September at 437 as intermediate months. The valid recommendation shortlist share rose from 59.9% to 77.3% over the full series, meaning a substantially larger share of the October set was eligible for recommendation analysis despite the slightly smaller qualified base. The share of recommendation-shaped answers rose from 32.6% to 61.2%.

Benchmark-Level Metrics

October 2026 combined a smaller qualified base with a materially higher concentration of recommendation-shaped answers. This makes the month a stronger basis for recommendation analysis per observation, though the reduced base warrants care when comparing brand-level percentages across the full series.

AI Recommendation Trend

Questions This Section Answers

• Who leads chatbot recommendation coverage in October 2026, and by how much?
• Which chatbots rose or fell the most against the July 2026 baseline?

Intercom Overtakes Tidio as Recommendation Coverage Concentrates at the Top

Intercom and Tidio both exceeded the threshold for normal month-to-month variation across the full series, and Intercom's month-over-month move was itself significant. The category-level change reflects two large risers plus the displacement of Zendesk and LiveChat coverage into their split entities, rather than movement concentrated in a single brand.

What Changed This Month

Questions This Section Answers

• Which chatbot brands posted significant shifts in recommendation coverage this month?
• How does the Zendesk and LiveChat tracking split affect how their coverage appears in the table?

Intercom: Significant Rise to Category Leader

Intercom's valid recommendation coverage rose 16.6 points from 50.8% in July 2026 to 67.4% in October 2026, a significant gain across the full series. The month-over-month move was also significant, up 9.0 points from 58.4% in September 2026, and the brand has now risen for three consecutive months.

Supporting metrics moved alongside coverage. Raw mention presence rose 7.7 points from 78.1% in July to 85.8% in October. Top-three recommendation rate rose 17.4 points from 29.8% to 47.2%, with 206 top-three placements. Rank-one rate rose 8.4 points from 8.6% to 17.0%, with 74 first-position recommendations.

Intercom's top-three rate gain (17.4 points) outpaced its overall coverage gain (16.6 points), while its rank-one rate rose by a smaller 8.4 points. The brand gained ground across the recommendation set more broadly than it gained outright first-place rankings. Its net sentiment score held at 0.8 across both months, so the rise is about placement rather than tone.

Highest-priority diagnostic: Which surfaces and prompt families drove the top-three and rank-one improvement, and whether that placement concentration persists.

Tidio: Sustained Significant Rise Behind the New Leader

Tidio's valid recommendation coverage rose 17.3 points from 43.9% in July 2026 to 61.2% in October 2026, a significant gain across the full series. The month-over-month move was smaller, up 1.7 points from 59.5% in September, within normal variation, but the brand has now risen for three consecutive months.

Raw mention presence rose 17.7 points from 55.9% in July to 73.6% in October. Top-three rate rose 14.2 points from 22.5% to 36.7%, with 160 top-three placements. Rank-one rate rose 2.8 points from 5.9% to 8.7%, with 38 first-position recommendations.

Tidio ceded the top position to Intercom despite its own significant rise, because Intercom's month-over-month gain was larger. Tidio's top-three rate climbed by over 14 points while its rank-one rate rose more modestly, by 2.8 points, so its recommendation footprint widened largely in the second and third positions rather than at the top spot.

Highest-priority diagnostic: Which prompt families drove the presence and top-three gains, and what separates the prompts where Tidio is ranked first from those where it is not.

Zendesk and LiveChat: Split Tracking Continues to Reshape the Table

Zendesk's valid recommendation coverage stands at 0.0% in October 2026, down 50.8 points from 50.8% in July, with its coverage reported under Zendesk Chat at 44.0%. Zendesk Chat moved up a further 0.5 points from 43.5% in September. LiveChat stands at 0.0%, down 17.2 points from 17.2% in July, with its coverage reported under LiveChat (Text S.A. (formerly LiveChat Software S.A.)) at 27.3%, up 7.6 points from 19.7% in September.

Within the split entities, Zendesk Chat shows raw mention presence of 57.1% and a top-three rate of 28.0%, with 122 top-three placements and 48 first-position recommendations. LiveChat (Text S.A.) shows raw mention presence of 35.3%, a top-three rate of 23.2%, and a rank-one rate of 14.9%, with 65 first-position recommendations.

The underlying brands remain highly visible under their new entity names. LiveChat (Text S.A.)'s rank-one rate of 14.9% is among the highest in the category, though Intercom's 17.0% rank-one rate remains the category high. The zero readings for Zendesk and LiveChat reflect the tracking split, not an absence from AI answers.

Highest-priority diagnostic: Whether the split entities represent distinct product lines or a reclassification of coverage that previously sat under the parent names.

Freshdesk: Continued Softening Within Normal Range

Freshdesk's valid recommendation coverage eased 3.7 points from 23.7% in July 2026 to 20.0% in October 2026, within the threshold for normal variation. The month-over-month move was a gain of 1.2 points from 18.8% in September, the first upward step after two declines.

Raw mention presence fell 14.1 points from 43.7% in July to 29.6% in October. Top-three rate fell 3.2 points from 15.6% to 12.4%, with 54 top-three placements. Rank-one rate eased 0.7 points from 2.3% to 1.6%, with 7 first-position recommendations.

Freshdesk's presence rate moved by a much larger margin (14.1 points) than its coverage rate (3.7 points, within normal range), meaning the brand is being surfaced in fewer AI answers overall even as its recommendation share holds comparatively steady. Its net sentiment score held at 0.7 across both months.

Highest-priority diagnostic: Which surfaces or prompt types account for the presence loss, and which brands now appear in the prompts where Freshdesk previously held placement.

Buyer-Intent Interpretation

Questions This Section Answers

• Which buyer-intent clusters did the qualified chatbot observations actually cover?
• Why does the benchmark not yet answer which chatbots win pricing or head-to-head comparisons?

In October 2026, all 436 qualified observations fell into the Brand Recommendation cluster. There were no qualified observations in the Pricing & Value or Multi-Brand Comparison clusters across July, August, September, or October 2026. The public benchmark therefore does not yet answer which brands win pricing discussions or head-to-head comparisons. This is a meaningful gap given that the inconsistency alerts above show AI platforms giving materially different and sometimes incompatible pricing answers for Intercom, Chatfuel, and ManyChat, so the pricing question is demonstrably active in the surface universe even though it sits outside the qualified recommendation denominator.

Brand Opportunity Summary

Questions This Section Answers

• Which chatbot brands show the strongest recommendation signals, and which are lagging?
• What is the highest-priority question for each chatbot brand to investigate?

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations, including the query, surface, recommendation outcome, rank, sentiment, and citations where exposed. Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Visibility Market Discovery research program.

• AI Visibility Industry Market
• AI Visibility Industry Market Methodology
• AI Visibility Industry Market Metrics
• AI Visibility Industry Market Standards

Report-Specific Interpretation Notes

• Movement between months identifies changes worth investigating, not established causes.
• Small observation counts for brands such as Chatfuel, Landbot, and Ada mean their coverage percentages rest on a narrow base of valid recommendations from the October 2026 qualified set.
• The qualified benchmark set of 436 observations is the denominator for all brand-level percentages, not the raw collection universe of 800 prompts.
• A tracking split continued to affect how Zendesk and LiveChat are reported, with their coverage appearing under Zendesk Chat and LiveChat (Text S.A. (formerly LiveChat Software S.A.)).
• The pricing inconsistencies reported in the alerts section involve pricing and market-status claims, which sit outside the qualified recommendation denominator and are flagged separately.

Next Step

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

Beneath the aggregate percentages lie specific questions: which high-intent prompts is a brand winning or losing, which competitor appears when a brand loses placement, what attributes do AI systems associate with each option, and which external sources shape those answers? The October 2026 benchmark identifies where attention is warranted, including the unresolved pricing and market-status conflicts affecting Intercom, Chatfuel, Drift, and ManyChat, but it does not by itself explain the mechanism.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It answers the why behind the movement, including whether the split Zendesk and LiveChat entities reflect distinct products or reclassified coverage.

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