Competitive intelligence for AI-mediated buying decisions. Where Resonate Labs wins, where it loses, and a prioritized three-layer execution plan — built from 150 buyer queries across ChatGPT + Claude + Gemini.
Resonate Labs' visibility is structurally backloaded — the brand appears only after buyers have already formed AI-assisted shortlists without it.
[Mechanism] The root cause is a three-layer compounding absence. First, 100% of early-funnel queries — spanning problem identification, solution exploration, and requirements building — return zero visibility, meaning Resonate Labs has no content positioned to answer the questions buyers ask before they know which vendors to consider. Second, the existing content inventory is concentrated on commercial and conversion pages that lack the depth, comparison framing, and technical specificity needed to earn AI citations across mid- and late-funnel query types.
Third, two capability areas central to buyer evaluation — ROI and pipeline attribution, and self-serve reporting dashboards — have thin or missing content coverage, allowing competitors to win those query clusters by default. The result is a brand that competes well in direct comparisons but only reaches buyers who already know to compare it.
[Synthesis] L1 technical fixes must execute before L2 and L3 work because the dual H1 findings on the homepage and partner page split AI crawlers' topical anchor signal, and unverified schema and canonical configuration mean new and optimized content may not be parsed or attributed correctly. Specifically, the sitemap consolidation fix ensures that /partners and /resources — the pages most relevant to late-funnel L2 optimization — are discoverable by crawlers that do not parse robots.txt, and schema verification unblocks structured extraction for the FAQ content that L3 pieces will rely on.
Where Resonate Labs appears and where it doesn't — across personas, buying jobs, and platforms.
[TL;DR] Resonate Labs is visible in 7% of buyer queries and wins 80% of those. The primary challenge is getting visible in the first place. High-intent queries run higher at 12%.
Resonate Labs' 6.7% overall visibility (10/150 queries) is entirely concentrated in Comparison and Validation stages — the brand is structurally absent from the 45 early-funnel queries where AI-mediated Shortlisting actually happens.
| Dimension | Combined |
|---|---|
| All Queries | 6.7% |
| By Persona | |
| CEO / CMO | 10.7% |
| Director of Content Strategy | 3.3% |
| Head of Digital Marketing | 0% |
| VP of Demand Generation | 3.2% |
| VP of Marketing | 15.2% |
| By Buying Job | |
| Artifact Creation | 0% |
| Comparison | 28.1% |
| Consensus Creation | 0% |
| Problem Identification | 0% |
| Requirements Building | 0% |
| Shortlisting | 0% |
| Solution Exploration | 0% |
| Validation | 4.3% |
[Data] Overall visibility: 6.7% (10/150 queries). High-intent visibility: 12.5% (10/80 high-intent queries); win rate among visible high-intent: 80% (8/10). Early-funnel invisibility: 100% across problem identification (13/13), solution exploration (16/16), requirements building (16/16) — 45/45 early-funnel queries invisible.
Shortlisting: 0% (0/25). Comparison: 28.1% (9/32), win rate 77.8% (7/9). VP of Marketing is the strongest persona: 15.2% visibility (5/33).
[Synthesis] The visibility pattern reveals a funnel that only activates at the bottom. Resonate Labs earns strong win rates in Comparison queries — where buyers are already choosing between named vendors — but is structurally absent during the stages when buyers define their problem, explore solutions, and set requirements. Because AI-mediated Shortlisting happens before any vendor contact, arriving late at the Comparison stage means competing against shortlists built without Resonate Labs on them.
The 80% conditional win rate is a signal of brand strength that cannot be leveraged until discovery-stage presence is established.
42 queries won by named competitors · 29 no clear winner · 69 no vendor mentioned
Sorted by competitive damage — competitor-winning queries first.
| ID | Query | Persona | Stage | Winner |
|---|---|---|---|---|
| ⚑ Competitor Wins — 42 queries where a named competitor captures the buyer | ||||
| rl_010 | "What are the main ways B2B teams figure out which questions their buyers ask AI during research?" | VP of Demand Generation | Problem Identification | HubSpot |
| rl_046 | "Best GEO agencies for B2B SaaS companies that need to show up in ChatGPT and Perplexity buyer research." | VP of Marketing | Shortlisting | Omniscient Digital |
| rl_047 | "Top GEO firms that produce and publish content, not just audits, for a mid-market B2B brand replacing its SEO agency." | VP of Marketing | Shortlisting | Omniscient Digital |
| rl_051 | "Shortlist of GEO partners that tie AI visibility to pipeline for a company moving budget off traditional SEO." | VP of Marketing | Shortlisting | First Page Sage |
| rl_053 | "Top AI visibility audit providers for a Series B SaaS company losing deals before sales gets involved." | VP of Demand Generation | Shortlisting | Omniscient Digital |
| rl_054 | "Is Omniscient Digital a good fit for AI search visibility, or are there better GEO-focused options for B2B SaaS?" | VP of Demand Generation | Shortlisting | Omniscient Digital |
| rl_055 | "Should we consider Graphite for GEO content, or are there agencies more focused on AI citations for mid-market B2B?" | VP of Demand Generation | Shortlisting | Graphite |
| rl_056 | "GEO vendors that report on pipeline impact for a demand gen team replacing an underperforming SEO agency." | VP of Demand Generation | Shortlisting | Scrunch AI |
| rl_057 | "Which GEO providers offer a dashboard plus recurring visibility tracking we can report on every two weeks?" | VP of Demand Generation | Shortlisting | Peec AI |
| rl_059 | "First Page Sage vs other GEO specialists — who's strongest for a B2B content team in a technical category?" | Director of Content Strategy | Shortlisting | First Page Sage |
Remaining competitor wins: Graphite ×9, Peec AI ×5, First Page Sage ×5, Omniscient Digital ×5, Genevate ×5, GenOptima ×2, Scrunch AI ×1. 29 queries with no clear winner. 69 queries with no vendor mentioned. Full query-level data available in the analysis export.
| ID | Query | Persona | Stage | Winner |
|---|---|---|---|---|
| rl_062 | "Which GEO services include a reporting dashboard content teams can actually use to show progress?" | Director of Content Strategy | Shortlisting | Peec AI |
| rl_064 | "For a technical team, is a platform like Peec AI enough, or do we need a GEO agency for AI visibility?" | Head of Digital Marketing | Shortlisting | Peec AI |
| rl_068 | "Top GEO agencies for a B2B company that just realized it's invisible in AI search." | CEO / CMO | Shortlisting | First Page Sage |
| rl_069 | "GEO agencies worth Shortlisting for a B2B SaaS brand — how do Graphite and GenOptima compare for our needs?" | CEO / CMO | Shortlisting | Graphite |
| rl_073 | "We're leaving our current SEO agency — Omniscient Digital vs Graphite for better B2B competitive intelligence in AI search?" | VP of Marketing | Comparison | Graphite |
| rl_074 | "First Page Sage vs Omniscient Digital — which proves ROI better for a company switching agencies?" | VP of Marketing | Comparison | Omniscient Digital |
| rl_078 | "Graphite vs Omniscient Digital — which better maps buyer queries across the funnel for demand gen teams?" | VP of Demand Generation | Comparison | Omniscient Digital |
| rl_080 | "Genevate vs GenOptima for competitive AI visibility tracking in a crowded B2B category." | VP of Demand Generation | Comparison | Genevate |
| rl_082 | "Peec AI vs hiring a GEO agency for ongoing AI visibility tracking — what's better for a lean demand gen team?" | VP of Demand Generation | Comparison | Peec AI |
| rl_083 | "Graphite vs GenOptima for buyer-query intelligence at a Series B SaaS company." | VP of Demand Generation | Comparison | Graphite |
| rl_084 | "Switching from our SEO firm — First Page Sage vs Graphite for GEO content production for a B2B content team?" | Director of Content Strategy | Comparison | Graphite |
| rl_088 | "Genevate vs Omniscient Digital for covering multiple AI engines with a single content strategy." | Director of Content Strategy | Comparison | Omniscient Digital |
| rl_089 | "Peec AI vs Scrunch AI dashboards for content teams tracking AI citations across platforms." | Director of Content Strategy | Comparison | Peec AI |
| rl_090 | "Graphite vs Genevate on the technical side of GEO — crawler accessibility and structured data for a SaaS site." | Head of Digital Marketing | Comparison | Graphite |
| rl_092 | "Scrunch AI's platform vs a GEO agency audit — which gives more actionable AI visibility dashboards for engineers?" | Head of Digital Marketing | Comparison | Scrunch AI |
| rl_093 | "First Page Sage vs Genevate on technical GEO implementation for a B2B SaaS platform." | Head of Digital Marketing | Comparison | First Page Sage |
| rl_095 | "Replacing a manual tracking spreadsheet — Peec AI vs an agency for continuous AI visibility monitoring?" | Head of Digital Marketing | Comparison | Peec AI |
| rl_096 | "Switching SEO vendors — Graphite vs First Page Sage for engineering-grade coverage across ChatGPT, Perplexity, Gemini and Claude?" | Head of Digital Marketing | Comparison | Graphite |
| rl_099 | "First Page Sage vs Genevate — which gets a B2B brand recommended by AI faster?" | CEO / CMO | Comparison | Genevate |
| rl_100 | "We're moving on from our current agency — Omniscient Digital vs Graphite for serious AI visibility results?" | CEO / CMO | Comparison | Omniscient Digital |
| rl_102 | "Replacing our SEO retainer — GenOptima vs First Page Sage on actually executing content versus just advising?" | CEO / CMO | Comparison | First Page Sage |
| rl_104 | "We're considering replacing our SEO agency with First Page Sage — does it actually deliver measurable GEO results or mostly thought leadership?" | VP of Marketing | Validation | First Page Sage |
| rl_107 | "What do clients say about Genevate's GEO results versus its PR work for a B2B brand?" | VP of Marketing | Validation | Genevate |
| rl_111 | "Switching to Graphite for GEO — what implementation problems should we expect for a Series B SaaS?" | VP of Demand Generation | Validation | Graphite |
| rl_112 | "We'd be moving off our SEO agency to First Page Sage — complaints about its GEO content quality from B2B teams?" | Director of Content Strategy | Validation | First Page Sage |
| rl_113 | "Does Genevate handle technical GEO or just earned media — gaps a content team should watch for?" | Director of Content Strategy | Validation | Genevate |
| rl_115 | "Risks of moving our content retainer from an SEO agency to Omniscient Digital for GEO." | Director of Content Strategy | Validation | Omniscient Digital |
| rl_117 | "Before we replace our SEO tooling with Graphite — has anyone validated its AI visibility data against actual ChatGPT output?" | Head of Digital Marketing | Validation | Graphite |
| rl_121 | "Moving off manual tracking to GenOptima — what should engineering worry about during implementation?" | Head of Digital Marketing | Validation | GenOptima |
| rl_122 | "Does Genevate produce ROI a CEO can defend, or is it hard to measure for a B2B brand?" | CEO / CMO | Validation | Genevate |
| rl_140 | "Draft an RFP to replace our SEO agency with a GEO firm, plus a scorecard for Omniscient Digital, Graphite, and First Page Sage on competitive AI visibility." | VP of Marketing | Artifact Creation | Graphite |
| rl_146 | "Build a Comparison matrix of Genevate and GenOptima on multi-platform AI coverage for a B2B content team." | Director of Content Strategy | Artifact Creation | GenOptima |
| rl_001 | "How are B2B companies even finding out whether AI tools like ChatGPT recommend them to buyers?" | CEO / CMO | Problem Identification | No Vendor Mentioned |
| rl_002 | "Our competitors keep coming up when prospects ask AI for recommendations and we don't — is this something companies actually fix?" | CEO / CMO | Problem Identification | No Vendor Mentioned |
| rl_003 | "Buyers seem to pick their shortlist from AI chatbots before they ever talk to sales — how are B2B teams getting ahead of that?" | CEO / CMO | Problem Identification | No Vendor Mentioned |
| rl_004 | "Is there a real business case for investing in AI search visibility or is it still too early to matter for revenue?" | CEO / CMO | Problem Identification | No Vendor Mentioned |
| rl_005 | "What's the first step to figure out how often our brand shows up in ChatGPT and Perplexity answers?" | VP of Marketing | Problem Identification | No Vendor Mentioned |
| rl_006 | "Our organic search traffic has been sliding for over a year — is AI search the reason, and what do teams do to replace that lost pipeline?" | VP of Marketing | Problem Identification | No Vendor Mentioned |
| rl_007 | "Even though we rank well on Google, AI assistants never name us when prospects ask for vendor recommendations — what's causing that?" | VP of Marketing | Problem Identification | No Vendor Mentioned |
| rl_008 | "How are demand gen teams handling the fact that buyers build shortlists in AI tools before any form fill?" | VP of Demand Generation | Problem Identification | No Vendor Mentioned |
| rl_009 | "We think we're losing pipeline to AI recommendations we can't see — how do companies even quantify that?" | VP of Demand Generation | Problem Identification | No Vendor Mentioned |
| rl_011 | "We're pulling budget out of paid search — how do teams know if AI search visibility is worth funding instead?" | VP of Demand Generation | Problem Identification | No Vendor Mentioned |
| rl_012 | "Our blog ranks fine on Google but seems invisible in AI answers — is this a known problem and how are content teams responding?" | Director of Content Strategy | Problem Identification | No Vendor Mentioned |
| rl_013 | "Why would a site that ranks well on Google not get picked up by AI crawlers and answer engines?" | Head of Digital Marketing | Problem Identification | No Vendor Mentioned |
| rl_014 | "Build vs buy for GEO — should we retrain our existing SEO content team or hire a specialized agency?" | Head of Digital Marketing | Solution Exploration | No Vendor Mentioned |
| rl_015 | "What actually makes content get cited by LLMs — is it schema markup, page structure, or just domain authority?" | Head of Digital Marketing | Solution Exploration | No Vendor Mentioned |
| rl_016 | "How different are the ranking factors across ChatGPT, Perplexity, Gemini and Claude — can one approach cover all of them?" | Head of Digital Marketing | Solution Exploration | No Vendor Mentioned |
| rl_017 | "What methods exist for measuring brand mentions and citations inside AI-generated answers at scale?" | Head of Digital Marketing | Solution Exploration | No Clear Winner |
| rl_018 | "We already run technical SEO in-house — what's genuinely different about optimizing a site for AI crawlers?" | Head of Digital Marketing | Solution Exploration | No Vendor Mentioned |
| rl_019 | "What kind of content earns AI citations, and how is it different from the SEO content we already produce?" | Director of Content Strategy | Solution Exploration | No Vendor Mentioned |
| rl_020 | "How do you tell the difference between agencies that really understand GEO and SEO shops that just rebranded?" | Director of Content Strategy | Solution Exploration | No Vendor Mentioned |
| rl_021 | "We've poured budget into SEO blogging with declining returns — what's the alternative content approach for AI search?" | Director of Content Strategy | Solution Exploration | No Vendor Mentioned |
| rl_022 | "Do you optimize content separately for each AI platform or is there a unified way to approach generative engine optimization?" | Director of Content Strategy | Solution Exploration | No Vendor Mentioned |
| rl_023 | "What are the approaches to mapping the AI queries buyers use early in their journey, before they reach our funnel?" | VP of Demand Generation | Solution Exploration | No Vendor Mentioned |
| rl_024 | "How do companies research why competitors get recommended by AI and they don't?" | VP of Demand Generation | Solution Exploration | No Vendor Mentioned |
| rl_025 | "Is GEO something you can run as a one-off audit or does it only really work as an ongoing program?" | VP of Demand Generation | Solution Exploration | No Vendor Mentioned |
| rl_026 | "Traditional SEO isn't delivering like it used to — what does a modern content strategy built for AI search look like?" | VP of Marketing | Solution Exploration | No Vendor Mentioned |
| rl_027 | "What's the difference between an AI visibility audit and a regular SEO audit?" | VP of Marketing | Solution Exploration | No Vendor Mentioned |
| rl_028 | "Should we hire a specialized GEO agency or expect our existing marketing agency to handle AI search?" | CEO / CMO | Solution Exploration | No Vendor Mentioned |
| rl_029 | "Is generative engine optimization a real discipline worth investing in, or marketing hype right now?" | CEO / CMO | Solution Exploration | No Vendor Mentioned |
| rl_030 | "What technical requirements should we put on a GEO vendor — crawler accessibility, schema, structured data, what else?" | Head of Digital Marketing | Requirements Building | No Vendor Mentioned |
| rl_031 | "Key requirements for a GEO program that needs to cover ChatGPT, Perplexity, Gemini and Claude, not just one engine." | Head of Digital Marketing | Requirements Building | No Vendor Mentioned |
| rl_032 | "What should an AI visibility measurement methodology include to be credible — query volume, platform coverage, sampling?" | Head of Digital Marketing | Requirements Building | No Vendor Mentioned |
| rl_033 | "Must-have vs nice-to-have: do we need a live dashboard for AI visibility or are periodic reports enough for a B2B SaaS team?" | Head of Digital Marketing | Requirements Building | No Vendor Mentioned |
| rl_034 | "What questions should I ask GEO vendors about how they track visibility changes over time?" | Head of Digital Marketing | Requirements Building | No Vendor Mentioned |
| rl_035 | "What should we require from a GEO partner on content execution — do they write and publish, or just advise?" | Director of Content Strategy | Requirements Building | No Vendor Mentioned |
| rl_036 | "How do I vet whether a GEO agency has a real methodology versus our old SEO firm's repackaged tactics — what proof should I ask for?" | Director of Content Strategy | Requirements Building | No Vendor Mentioned |
| rl_037 | "Evaluation criteria for a GEO vendor's buyer-query research — how do they decide which AI queries actually matter?" | Director of Content Strategy | Requirements Building | No Vendor Mentioned |
| rl_038 | "We're replacing our SEO content retainer — what should be in scope for a GEO content program instead?" | Director of Content Strategy | Requirements Building | No Vendor Mentioned |
| rl_039 | "Criteria for choosing a GEO partner for a B2B SaaS company — what separates a useful audit from a vanity report?" | VP of Marketing | Requirements Building | No Vendor Mentioned |
| rl_040 | "We're switching marketing agencies — what reporting should I require from a GEO vendor to prove the work connects to pipeline?" | VP of Marketing | Requirements Building | No Vendor Mentioned |
| rl_041 | "We already track SEO rankings — what should competitive AI-visibility tracking requirements look like against named competitors?" | VP of Marketing | Requirements Building | No Vendor Mentioned |
| rl_042 | "How should a GEO vendor map queries to buyer personas and funnel stages — what does good look like?" | VP of Demand Generation | Requirements Building | No Vendor Mentioned |
| rl_043 | "We want bi-weekly visibility tracking — what should I ask vendors about recurring audit cadence and trend reporting?" | VP of Demand Generation | Requirements Building | No Vendor Mentioned |
| rl_044 | "Must-have metrics for tying AI visibility to demand gen outcomes — what should be written into the contract?" | VP of Demand Generation | Requirements Building | No Vendor Mentioned |
| rl_045 | "What credentials or proof points actually signal that a GEO firm knows what it's doing for a B2B brand?" | CEO / CMO | Requirements Building | No Vendor Mentioned |
| rl_048 | "Which GEO agencies are best for tracking how we compare to competitors in AI-generated recommendations?" | VP of Marketing | Shortlisting | No Clear Winner |
| rl_049 | "Most credible GEO specialists for a B2B company that's been burned by SEO agencies overpromising." | VP of Marketing | Shortlisting | No Clear Winner |
| rl_050 | "GEO agencies that cover all major AI platforms for a 200-person B2B software company." | VP of Marketing | Shortlisting | No Clear Winner |
| rl_052 | "Best GEO firms for mapping the AI queries our buyers ask early in the funnel — B2B demand gen focus." | VP of Demand Generation | Shortlisting | No Clear Winner |
| rl_058 | "Best GEO agencies for content teams that need help getting our existing articles cited by AI engines." | Director of Content Strategy | Shortlisting | No Clear Winner |
| rl_060 | "GEO firms that handle both the technical crawler setup and the content rewrite for AI visibility." | Director of Content Strategy | Shortlisting | No Clear Winner |
| rl_061 | "Top GEO content partners for covering Perplexity and ChatGPT for a SaaS company in a crowded category." | Director of Content Strategy | Shortlisting | No Vendor Mentioned |
| rl_063 | "GEO agencies with strong technical chops — crawler accessibility, schema, structured data — for a B2B SaaS site." | Head of Digital Marketing | Shortlisting | No Clear Winner |
| rl_065 | "Best GEO providers for a high-growth SaaS that needs coverage across all four major AI assistants." | Head of Digital Marketing | Shortlisting | No Clear Winner |
| rl_066 | "We're moving off a manual tracking setup — best GEO options for a technical team, agency or a platform like Evertune?" | Head of Digital Marketing | Shortlisting | No Clear Winner |
| rl_067 | "Most reputable GEO firms for an executive team that wants a proven partner, not an experiment." | CEO / CMO | Shortlisting | No Clear Winner |
| rl_070 | "Best GEO partners for a CEO who wants AI visibility tied to revenue, switching from a generalist agency." | CEO / CMO | Shortlisting | No Clear Winner |
| rl_077 | "GenOptima vs a full-service GEO agency for multi-platform AI coverage at a mid-market B2B company." | VP of Marketing | Comparison | No Clear Winner |
| rl_081 | "Replacing a fixed SEO retainer — GenOptima's result-as-a-service vs a traditional GEO retainer, which is safer?" | VP of Demand Generation | Comparison | No Clear Winner |
| rl_086 | "Genevate vs a content-first GEO agency for getting technical documentation cited by AI." | Director of Content Strategy | Comparison | No Clear Winner |
| rl_087 | "Switching from First Page Sage — which GEO agency is better for hands-on content execution?" | Director of Content Strategy | Comparison | No Clear Winner |
| rl_091 | "Replacing spreadsheet tracking — Evertune vs Peec AI for multi-platform AI visibility measurement at scale?" | Head of Digital Marketing | Comparison | No Clear Winner |
| rl_094 | "Moving off our SEO reporting — GenOptima vs a self-serve analytics tool for tracking AI visibility, what does a technical lead need?" | Head of Digital Marketing | Comparison | No Clear Winner |
| rl_103 | "Common complaints about Omniscient Digital from B2B marketing teams." | VP of Marketing | Validation | No Clear Winner |
| rl_105 | "Biggest risks of hiring Graphite for GEO content at a mid-market B2B company." | VP of Marketing | Validation | No Clear Winner |
| rl_108 | "Hidden risks of GenOptima's result-as-a-service GEO pricing for a demand gen team." | VP of Demand Generation | Validation | No Clear Winner |
| rl_109 | "If we switch our demand gen content to Omniscient Digital, where does it fall short on early-funnel AI query coverage?" | VP of Demand Generation | Validation | No Clear Winner |
| rl_110 | "Limitations of Peec AI for a demand gen team that needs more than just visibility tracking." | VP of Demand Generation | Validation | No Clear Winner |
| rl_114 | "How do I avoid GEO agencies that just rebrand SEO — red flags for a content team evaluating vendors?" | Director of Content Strategy | Validation | No Vendor Mentioned |
| rl_116 | "Scrunch AI complaints — what do content teams wish they'd known before buying?" | Director of Content Strategy | Validation | No Clear Winner |
| rl_118 | "Evertune limitations for multi-platform AI tracking — what breaks at scale for a technical team?" | Head of Digital Marketing | Validation | No Clear Winner |
| rl_119 | "How credible is First Page Sage's GEO measurement methodology for a technical evaluator?" | Head of Digital Marketing | Validation | No Clear Winner |
| rl_120 | "Peec AI data quality concerns — does UI scraping miss citations a technical team would care about?" | Head of Digital Marketing | Validation | No Clear Winner |
| rl_123 | "Is GenOptima's performance-based GEO model too good to be true — what's the catch for a cautious executive?" | CEO / CMO | Validation | No Clear Winner |
| rl_124 | "Biggest reasons B2B companies leave Omniscient Digital for another GEO provider." | CEO / CMO | Validation | No Clear Winner |
| rl_125 | "What can go wrong with a GEO engagement — where do these projects fail for B2B brands?" | CEO / CMO | Validation | No Vendor Mentioned |
| rl_126 | "How do I build the business case for GEO investment to my board for a B2B SaaS company?" | CEO / CMO | Consensus Creation | No Vendor Mentioned |
| rl_127 | "What's the cost of staying invisible in AI search, and how do I frame that risk to leadership?" | CEO / CMO | Consensus Creation | No Vendor Mentioned |
| rl_128 | "How do I convince my exec team that competitors winning AI recommendations is an urgent threat?" | CEO / CMO | Consensus Creation | No Vendor Mentioned |
| rl_129 | "Justifying a switch from our SEO agency to a GEO specialist — what's the strategic argument for leadership?" | CEO / CMO | Consensus Creation | No Vendor Mentioned |
| rl_130 | "Typical ROI and payback when reallocating an SEO budget to a GEO program at a mid-market B2B company." | VP of Marketing | Consensus Creation | No Vendor Mentioned |
| rl_131 | "How to present AI visibility dashboards to a CFO who only trusts hard numbers." | VP of Marketing | Consensus Creation | No Vendor Mentioned |
| rl_132 | "Business case for reallocating SEO budget to GEO — what numbers do I need for a 200-person SaaS?" | VP of Marketing | Consensus Creation | No Vendor Mentioned |
| rl_133 | "How do I make the case for GEO when leadership thinks our existing SEO is already fine?" | VP of Marketing | Consensus Creation | No Vendor Mentioned |
| rl_134 | "Case studies of B2B SaaS companies that drove measurable pipeline from AI visibility work." | VP of Demand Generation | Consensus Creation | No Vendor Mentioned |
| rl_135 | "How do I quantify pipeline lost to AI-driven shortlists to justify a GEO budget to my CMO?" | VP of Demand Generation | Consensus Creation | No Vendor Mentioned |
| rl_136 | "What dashboard and metrics prove a GEO program is working over time for a demand gen leader reporting to the CRO?" | VP of Demand Generation | Consensus Creation | No Vendor Mentioned |
| rl_137 | "How do I justify shifting content investment from SEO toward GEO when SEO traffic is still our biggest channel?" | Director of Content Strategy | Consensus Creation | No Vendor Mentioned |
| rl_138 | "Building internal buy-in to replace our current marketing agency with a specialized GEO partner." | Director of Content Strategy | Consensus Creation | No Vendor Mentioned |
| rl_139 | "Draft an RFP for a GEO agency for a mid-market B2B SaaS company, including AI visibility auditing and measurement requirements." | VP of Marketing | Artifact Creation | No Vendor Mentioned |
| rl_141 | "Build a TCO model comparing our current SEO retainer to a 12-month GEO engagement at a 200-person B2B company, including content costs." | VP of Marketing | Artifact Creation | No Vendor Mentioned |
| rl_142 | "Create an evaluation template for GEO vendors focused on buyer-persona query mapping for a demand gen team." | VP of Demand Generation | Artifact Creation | No Vendor Mentioned |
| rl_143 | "Write a one-page business case for GEO investment I can bring to my CMO for a Series B SaaS company." | VP of Demand Generation | Artifact Creation | No Vendor Mentioned |
| rl_144 | "Draft a GEO content brief template that ensures our articles are structured to be cited by AI engines." | Director of Content Strategy | Artifact Creation | No Vendor Mentioned |
| rl_145 | "Create a list of vetting questions to ask GEO agencies to confirm a real methodology, not rebranded SEO." | Director of Content Strategy | Artifact Creation | No Vendor Mentioned |
| rl_147 | "Create a technical GEO readiness checklist for our B2B SaaS site — crawler access, schema, and structured data." | Head of Digital Marketing | Artifact Creation | No Vendor Mentioned |
| rl_148 | "Draft an executive summary justifying a GEO program, framed around competitors winning AI recommendations and lost pipeline." | CEO / CMO | Artifact Creation | No Vendor Mentioned |
| rl_149 | "Create a board-ready one-pager template for reporting our AI visibility metrics every quarter." | CEO / CMO | Artifact Creation | No Vendor Mentioned |
| rl_150 | "Build a 90-day GEO plan template showing how we'll track AI visibility improvements over time for a B2B SaaS company." | CEO / CMO | Artifact Creation | No Vendor Mentioned |
Queries where Resonate Labs is mentioned but a competitor is positioned more favorably.
| ID | Query | Persona | Buying Job | Winner | Resonate Labs Position |
|---|---|---|---|---|---|
| rl_097 | "For an executive choosing a GEO partner, how does Resonate Labs compare to Omniscient Digital on track record?" | CEO / CMO | Comparison | Omniscient Digital | Mentioned In List |
| rl_098 | "Resonate Labs vs GenOptima — does performance-based GEO pricing beat a fixed engagement for a cautious CMO?" | CEO / CMO | Comparison | GenOptima | Strong 2nd |
Who’s winning when Resonate Labs isn’t — and who controls the narrative at each buying stage.
[TL;DR] Resonate Labs wins 5.3% of queries (8/150), ranks #9 in SOV — H2H record: 9W–2L across 5 competitors.
A strong pairwise H2H record (9 wins, 1 loss across 11 co-appearing queries) obscures a #9 SOV ranking and near-total absence from the query types that determine whether the brand makes buyer shortlists at all.
| Company | Mentions | Share |
|---|---|---|
| First Page Sage | 36 | 19.6% |
| Omniscient Digital | 30 | 16.3% |
| Peec AI | 27 | 14.7% |
| Graphite | 21 | 11.4% |
| Scrunch AI | 14 | 7.6% |
| GenOptima | 14 | 7.6% |
| Genevate | 13 | 7.1% |
| HubSpot | 10 | 5.4% |
| Resonate Labs | 10 | 5.4% |
| Evertune | 9 | 4.9% |
When Resonate Labs and a competitor both appear in the same response, who gets the recommendation? One query with multiple competitors generates a matchup against each — so H2H totals will exceed the query count.
Win = primary recommendation (cross-platform majority). Loss = competitor was. Tie = neither or third party.
For the 140 queries where Resonate Labs is completely absent:
Vendors appearing in responses not in Resonate Labs’s defined competitive set.
[Data] SOV rank: #9 (10 mentions, 5.4% share). First Page Sage leads at #1 (36 mentions, 19.6%). H2H record: 4-0 vs.
First Page Sage, 2-1 vs. Omniscient Digital, 1-0 vs. Graphite, 2-0 vs.
Genevate, 0-1 vs. GenOptima. Invisible query winners: no AI coverage takes 49.3% (69/140 invisible queries); no clear winner 20.7% (29/140).
Competitor-won invisible queries: Graphite 7.1% (10/140), Omniscient Digital 6.4% (9/140).
[Synthesis] Resonate Labs' H2H record is genuinely strong — the brand beats every named competitor it faces except GenOptima — but H2H measures only pairwise outcomes when both brands appear in the same response, which occurs in just 11 queries. Query-level win rate tells a different story: at 6.7% overall visibility (10/150 queries), the brand is nearly absent from the buyer journey. Nearly half of all invisible queries (69/140) return no vendor recommendation at all, representing the highest-leverage opportunity — these are queries where first-mover content wins by default.
What AI reads and trusts in this category.
[TL;DR] Resonate Labs had 1 unique pages cited across buyer queries, ranking #16 among all cited domains. 10 high-authority domains cite competitors but not Resonate Labs.
With only 1 unique URL cited and a #16 domain citation rank, Resonate Labs has a homepage-only citation footprint — the structural reason it loses to competitors who have built multi-page, query-aligned content libraries.
Note: Domain-level citation counts (above) tally instances per individual domain. Competitor-level counts (below) aggregate across all domains owned by a single vendor, which may include subdomains.
Non-competitor domains citing other vendors but not Resonate Labs — off-domain authority opportunities.
These domains cited competitors but did not cite Resonate Labs pages in the queries analyzed. This reflects citation patterns in AI responses, not overall platform presence.
[Data] Client unique pages cited: 1 (resonatelabs.co). Client domain rank: #16. Raw citation instances for resonatelabs.co: 20 (appearing across 10 query IDs).
Top competitor by citation instances: firstpagesage.com at 91. Arxiv.org leads all domains at 241 citation instances. Third-party gap domains with no client presence: 245 domains with ≥2 citations.
[Synthesis] The citation data reveals a structural authority gap: only 1 unique Resonate Labs URL earns citations across all 150 queries, compared to competitors with 33–91 citation instances from dedicated content pages. The homepage is carrying the entire citation burden. Resonate Labs' own methodology — building content that AI platforms cite as authoritative sources — is not yet applied to its own domain.
Third-party domains like arxiv.org (241 instances) and thedigitalelevator.com (47 instances) are filling answer space that purpose-built Resonate Labs content could occupy.
Three layers of recommendations ranked by commercial impact and implementation speed.
[TL;DR] 31 priority recommendations (plus 3 near-rebuild optimizations) targeting 142 gap queries (140 invisible, 2 positioning gaps). 1 L1 technical fixes + 5 verification checks, 20 content optimizations (L2), 5 new content initiatives (L3).
148 recommendations execute in three layers: structural fixes first to ensure content is parseable, then 82 optimizations on existing pages, then 60 new pieces targeting the ROI and dashboard capability gaps where no Resonate Labs content currently exists.
Reading the priority numbers: Recommendations are ranked 1–31 across all three layers by commercial impact × implementation speed. Within each layer, items appear in priority order. Gaps in the sequence (e.g., L1 shows 1, 2, then 12) mean higher-priority items belong to a different layer.
Configuration and infrastructure changes. Owner: Engineering / DevOps. Timeline: Days to weeks.
| Priority | Finding | Impact | Timeline |
|---|---|---|---|
| #19 | Multiple H1 headings on the homepage and partner program page | Medium | < 1 day |
Items requiring manual review before determining if action is needed.
| Priority | Finding | Impact | Timeline |
|---|---|---|---|
| #27 | Client-side rendering status cannot be confirmed from our method | Low | < 1 day |
| #28 | Inconsistent trailing-slash convention across URLs | Low | < 1 day |
| #29 | Meta descriptions and Open Graph tags cannot be assessed from rendered output | Low | < 1 day |
| #30 | Site coverage split across two sitemaps with no sitemap index | Low | < 1 day |
| #31 | Structured-data (JSON-LD schema) coverage cannot be assessed from rendered output | Low | < 1 day |
Click any row to expand full issue/fix detail.
Existing pages that need restructuring or deepening. Owner: Content Team. Timeline: Weeks.
The /resources page (the most appropriate home for evaluation frameworks) does not contain any GEO vendor evaluation templates, RFP structures, or competitive scoring frameworks — the exact artifact type this query demands. The /resources page does not position Resonate Labs as a thought leader in GEO vendor evaluation methodology — missing the authority signal needed to surface in artifact-creation queries. The /partners page does not include evaluation criteria that buyers could use to score Resonate Labs in a competitive RFP process, leaving AI engines without Resonate Labs-provided evaluation parameters.
Queries affected: rl_140
The /partners page does not explicitly name B2B SaaS as the primary client segment served, missing the matching signal for 'best GEO agencies for B2B SaaS companies.' The /partners page does not enumerate which AI platforms (ChatGPT, Perplexity, Claude, Gemini) are covered by the GEO service, the most common shortlist filter in this query type. The /partners page lacks third-party signals (case study references, named client outcomes, or credential citations) that AI engines use to assess agency credibility when generating shortlists.
Queries affected: rl_046
The /partners page contains no competitive context positioning Resonate Labs relative to named competitors (Graphite, GenOptima), giving AI engines nothing to cite when generating 'should we add X to the list' responses. The /partners page does not address the 'B2B SaaS brand' buyer context with specificity — the primary segment qualifier CEOs use when evaluating fit. The /partners page lacks a 'why add Resonate Labs to your shortlist' argument — the specific content format AI engines pull from for shortlist composition queries.
Queries affected: rl_069
The /partners page contains no competitive differentiation language contrasting Resonate Labs with broad-scope GEO agencies like Omniscient Digital — AI engines have no extractable claim to cite when generating alternative recommendations. The /partners page does not name B2B SaaS AI search visibility as a specific specialty, missing the topical match that makes it relevant to queries about GEO-focused options for B2B SaaS. The /partners page has no positioning claim establishing Resonate Labs as a specialist (vs. generalist) GEO provider — the key distinction buyers are probing in this query.
Queries affected: rl_054
The /partners page does not use the specific language 'AI citations' or describe the outcome of the service in terms of being cited by LLMs — the precise value proposition this query targets. The /partners page does not identify mid-market B2B as a named client segment, missing the company-size matching signal that buyers filter on in this query. The /partners page's description of the GEO service does not differentiate it from content-production agencies like Graphite in terms of AI-citation specialization.
Queries affected: rl_055
The /partners page does not explicitly state that Resonate Labs produces and publishes content (writes, edits, publishes) versus only auditing or advising — the core filter buyers apply in this query. The /partners page has no description of what a typical content engagement scope includes (articles per month, content types, publishing workflow), leaving AI engines unable to match it to 'produces and publishes content' criteria. The /partners page does not address the 'replacing SEO agency' transition context — a dominant buyer intent signal in this query that winning pages like Omniscient Digital explicitly address.
Queries affected: rl_047
The /partners page describes the partner program outcome ('scale your GEO service line') but contains no passage explaining the process by which buyer AI queries are identified and mapped — the exact question buyers are asking in this query cluster. The /partners page uses marketing prose ('research team') rather than structured, extractable methodology claims that AI engines can cite as a named process or framework. The /partners page has no Comparison between common methods (manual prompt testing, platform analytics, automated query capture) that would make it citable for an educational 'how-to-discover-buyer-AI-queries' answer.
Queries affected: rl_010
The /visibility/ page does not address the 'platform vs. agency' decision — it likely describes the audit product without explaining when a technical team needs an agency vs. a tool. The /visibility/ page does not enumerate what a GEO agency provides that platforms like Peec AI cannot (e.g., content optimization, competitive strategy, implementation support), missing the comparative positioning. The /visibility/ page is flagged as sparse in the L1 audit, limiting the extractable content available for an 'agency vs. platform' decision response.
Queries affected: rl_064
The /visibility/ page describes the audit as a product but does not explain the underlying methods B2B companies use to measure AI recommendation visibility (manual prompt testing, automated monitoring, platform analytics) — the educational content this query triggers. The /visibility/ page does not answer the 'how do companies find out' question in a format AI engines can extract for educational responses — it reads as a product page rather than a methodology reference. The /visibility/ page's sparse body (flagged in L1 audit) limits the number of educational claims available for AI extraction on this foundational query topic.
Queries affected: rl_001
The homepage does not directly address the 'is this fixable?' question with a confident, evidence-backed answer — the primary psychological need of a buyer discovering AI recommendation gaps for the first time. The homepage does not include named outcome types or improvement timelines that AI engines can extract to answer 'yes, companies fix this, here's how' — the educational reassurance format this query triggers. The homepage marketing prose ('We change it') is too terse to be cited as educational content — AI engines need fuller explanatory passages to cite as authoritative answers to 'can this be fixed' questions.
Queries affected: rl_002
The /partners page contains no description of the implementation or onboarding process for a new GEO engagement, leaving AI engines with nothing to cite when buyers research what switching to a GEO agency involves. The /partners page does not address implementation risk mitigation — a specific content format that AI engines pull from when validating competitor switching decisions. The /partners page has no Series B SaaS-specific implementation context, missing the segment anchor that makes this content relevant to the specific buyer asking the question.
Queries affected: rl_111
The /visibility/ page describes the AI visibility audit but does not explicitly name Series B SaaS companies as a target client segment, missing the persona-matching signal AI engines need for this query. The /visibility/ page does not address the 'losing deals before sales gets involved' pain point — the specific business consequence that motivates this search — leaving AI engines unable to match it to the buyer's urgency. The /visibility/ page is sparse in body content (flagged as a short conversion page in the L1 audit), limiting the number of extractable claims available for AI citation.
Queries affected: rl_053
The /visibility/ page does not address the 'just realized we're invisible in AI search' discovery moment — the specific trigger described in this query, limiting its relevance to first-discovery buyer contexts. The /visibility/ page does not include a clear first-step call to action framed around diagnosing AI invisibility, missing the 'what to do first' positioning that new-entrant buyers need. The /visibility/ page's sparse body content (flagged in L1 audit) means AI engines have limited extractable content to cite when recommending agencies for newly-aware companies.
Queries affected: rl_068
The /partners page contains no technical implementation content relevant to a Head of Digital Marketing evaluating engineering complexity of GEO tool transitions. The /partners page does not address what technical requirements a GEO agency engagement places on an engineering team, missing the Comparison signal for 'agency vs. tool' implementation queries. The /partners page has no 'what does your team need to do' framing for a Resonate Labs engagement, leaving technical evaluators with no implementation complexity picture.
Queries affected: rl_121
The /resources page does not contain multi-platform AI coverage Comparison content — the specific content format this artifact query targets — leaving AI engines with nothing to cite from Resonate Labs. The /resources page has no competitive matrix or structured Comparison framework for GEO vendors, missing the artifact authority that would make it the cited source for vendor Comparison queries. The /visibility/ page does not enumerate Resonate Labs' own multi-platform coverage in a structured, comparable format — buyers constructing Comparison matrices cannot find Resonate Labs' own specifications.
Queries affected: rl_146
The /partners page does not distinguish between PR-based GEO approaches (earned media, brand mentions) and content-based GEO (structured content optimization, citation engineering) — the key distinction buyers probe when evaluating Genevate alternatives. The /partners page has no client outcome language or testimonial-adjacent claims that AI engines can extract as evidence of GEO results quality — missing the 'what do clients say' signal. The /partners page does not address the technical vs. earned-media split in GEO methodology, leaving buyers who question PR-led approaches with no Comparison point.
Queries affected: rl_107
The homepage states the problem ('AI shapes buyer shortlists') but does not provide the 'how teams get ahead of it' educational answer that this query demands — AI engines need a named strategy, not just a problem statement. The homepage does not include a named methodology or set of strategies that B2B teams use to appear in AI-mediated shortlists before sales engagement — the specific content AI engines pull for this query type. The homepage's hero copy addresses the outcome ('we change what AI says
Queries affected: rl_003
The /partners page does not address SEO-to-GEO transition risks or how Resonate Labs manages content continuity when a team is switching from an existing agency retainer. The /partners page has no risk mitigation framing around agency transitions — the specific content type AI engines extract for 'risks of switching to X' queries. The /partners page does not establish Resonate Labs as a lower-risk alternative to larger agencies for content transitions, missing an opportunity to capture buyers raising Omniscient Digital concerns.
Queries affected: rl_115
The /partners page does not describe the content quality standards, editorial review process, or what makes Resonate Labs' content 'AI-citation-ready' versus standard SEO content — missing the quality differentiation signal. The /partners page contains no content team-specific positioning addressing how content is written, reviewed, and structured for AI citation — the specific concerns of a Director of Content Strategy. The /partners page has no 'switching from an SEO content agency' framing that would surface it during transition Validation queries.
Queries affected: rl_112
The /resources page does not establish Resonate Labs' thought leadership credentials in terms of technical B2B content optimization — the specific expertise signal this query targets. The /resources page does not include a positioning statement for content teams in technical B2B categories (e.g., DevTools, SaaS infrastructure, security), missing the audience segment match. The /resources page lacks a named methodology or framework that content teams can reference as evidence of GEO specialization — the credential AI engines extract when evaluating 'who's strongest.'
Queries affected: rl_059
Net new content addressing visibility and positioning gaps. Owner: Content Strategy. Timeline: Months.
ROI and budget justification queries span every persona and every funnel stage from problem identification through artifact creation, representing 22 queries where decision-makers are in active spend-approval mode. When a VP of Marketing asks 'Is there a real business case for AI search visibility?' or a CEO asks 'How do I build the business case for GEO investment to my board?', Resonate Labs is entirely absent — competitors and generic third-party sources fill the vacuum. This is the single largest content gap by query volume and the highest-stakes commercial moment: buyers who cannot find ROI proof during consensus creation and requirements building never reach Shortlisting. Without dedicated, citable ROI content, Resonate Labs is structurally excluded from the conversations that unlock budget.
ChatGPT (high): ChatGPT surfaces educational/advisory responses for most ROI queries with No Vendor Mentioned winners, indicating it is actively looking for authoritative sources to cite on GEO ROI methodology — a gap Resonate Labs can fill. Claude (high): Claude returns 0 citation counts on many ROI queries (gap_status_only derivation), suggesting it has almost no source material on GEO ROI from any vendor, making early content publication especially impactful. Gemini (medium): Gemini returns higher citation counts on ROI queries (up to 14 citations on rl_011) but still shows Resonate Labs as invisible, indicating it cites third-party research and general sources rather than vendor content — requires off-domain citation strategy.
When buyers ask 'Which GEO providers offer a dashboard plus recurring visibility tracking?' or 'How do I present AI visibility dashboards to a CFO?', Resonate Labs is entirely absent and Peec AI, Scrunch AI, and Profound dominate responses. This is both a content gap and a product positioning gap: the absence of any reporting/dashboard offering means Resonate Labs cannot credibly compete in 13 Shortlisting, Comparison, and consensus-creation queries where measurement and reporting are the primary decision criterion. Buyers at the Shortlisting and Validation stage who require bi-weekly reporting cadence, dashboard access, or CFO-ready metrics will never see Resonate Labs as an option. Addressing this gap requires both new content that explains Resonate Labs' measurement methodology and transparency about how clients track and report on GEO progress.
ChatGPT (high): ChatGPT surfaces detailed platform Comparison tables for dashboard queries (e.g., rl_057 returns 10 citations) and is actively synthesizing vendor capability information — well-structured reporting methodology content would be directly citable. Claude (medium): Claude returns very low citation counts for reporting queries (often gap_status_only), suggesting limited source material available — early mover advantage for any vendor publishing detailed measurement methodology content. Gemini (high): Gemini returns high citation counts on reporting queries (up to 14 on rl_089) and already surfaces Peec AI and Scrunch AI prominently, indicating it actively cites vendor-specific capability content for this query type.
Technical evaluators (Head of Digital Marketing) and content teams researching implementation requirements ask questions like 'Why would a site that ranks well on Google not get picked up by AI crawlers?' and 'What technical requirements should we put on a GEO vendor?'. Resonate Labs is entirely absent from these responses, with Graphite and First Page Sage collecting wins on technical Comparison queries. The Head of Digital Marketing persona — which has 0% visibility and 0% win rate across all 28 queries — is almost entirely concentrated in technical and implementation-focused queries. Without substantive technical content, Resonate Labs cannot win the evaluator persona that influences shortlist decisions and often controls implementation vendor selection. The L1 audit also identified unresolved structural issues (multiple H1 tags, schema markup unverified) that compound this gap.
ChatGPT (high): ChatGPT surfaces educational technical responses with high citation counts (up to 10 on rl_030) for technical requirements queries, actively seeking authoritative technical sources — well-structured technical guides would be directly citable. Claude (medium): Claude returns gap_status_only (0 citations) on several technical queries, suggesting very limited source material available for LLM technical optimization content — strong early-mover opportunity. Gemini (high): Gemini returns consistently high citation counts on technical queries (16 on rl_030, 13 on rl_013) and already cites developers.google.com prominently (67 citations), indicating receptivity to structured technical content from credible sources.
Comparison queries are the highest-intent buying job in the taxonomy, and Resonate Labs achieves 28% visibility and 78% win rate when it appears in Comparison queries — demonstrating that when it shows up, it wins. But it shows up in only 9 of 32 Comparison queries, and the 18 L3 Comparison gaps are structurally blocked because the site has no Comparison page format. Buyers asking 'Graphite vs Omniscient Digital for competitive intelligence' or 'First Page Sage vs Graphite for content production' represent an active vendor Shortlisting decision — these are the highest-value moments in the entire buying journey. The routing override confirms this is not a depth problem but a page-type architecture problem: the content model lacks a Comparison format entirely. Creating Comparison content that inserts Resonate Labs as a superior alternative is the highest-ROI structural intervention available.
ChatGPT (high): ChatGPT generates detailed Comparison responses with explicit verdicts (e.g., 'Verdict: Omniscient Digital wins') and high citation counts (3-10 per Comparison query), indicating it actively synthesizes Comparison content and would cite well-structured Comparison pages. Claude (medium): Claude frequently returns low citation counts (gap_status_only) on Comparison queries, suggesting it may be more cautious about vendor comparisons — but also that early, authoritative Comparison content from Resonate Labs would face less competition. Gemini (high): Gemini returns the highest citation counts on Comparison queries (up to 11) and surfaces explicit winner verdicts, demonstrating strong receptivity to structured Comparison content and clear recommendation framing.
These two positioning gap queries represent the most dangerous type of AI visibility failure: Resonate Labs is present in the conversation but losing. When an executive asks 'how does Resonate Labs compare to Omniscient Digital on track record?', the AI explicitly states Resonate Labs carries higher risk due to unverifiable public proof — a credibility gap that will cost deals. The rl_098 query shows a similar pattern on pricing model, with GenOptima's performance-based model framed as more appealing for well-defined engagements. Both gaps are addressable through concrete proof-point publication: verifiable case studies, named client references, and explicit pricing/engagement model transparency would directly change how AI platforms characterize Resonate Labs in direct Comparison responses.
ChatGPT (high): ChatGPT generated the explicit 'higher risk with unverifiable public proof' characterization in rl_097 (3 citations) — it is actively evaluating evidence quality and would update its assessment when concrete proof points are available to cite. Claude (medium): Claude returns gap_status_only (0 citations) for both positioning gap queries, suggesting it lacks sufficient source material to form a view — early publication of proof points would establish the narrative before Claude forms negative impressions. Gemini (high): Gemini returns the highest citation counts for both positioning queries (10 citations each) and surfaces explicit verdicts — it is the platform most actively synthesizing competitive Comparison content and most likely to update its characterization based on new published evidence.
All recommendations across all three layers, ranked by commercial impact × implementation speed.
Resonate Labs is invisible across 18 Comparison-format queries where buyers are evaluating two named competitors against each other (e.g., 'Graphite vs Omniscient Digital', 'First Page Sage vs Genevate'). All 18 queries have buying_job='Comparison' and routing rationale includes 'AFFINITY OVERRIDE: buying_job=Comparison requires page types [Comparison] but found [landing_page]' — meaning Resonate Labs has no Comparison-format content pages to satisfy this query type.
Resonate Labs is invisible across 22 queries where buyers are actively evaluating whether GEO investment is worth funding, including ROI benchmarks, pipeline attribution, and board-ready business case content. The site lacks dedicated ROI-focused content (coverage_status='thin' for ROI Attribution & Pipeline Impact Measurement across all 22 queries), meaning AI platforms have no substantive Resonate Labs content to cite when buyers ask about measuring and justifying GEO spend.
Resonate Labs is invisible across 13 queries where buyers are actively comparing and evaluating AI visibility reporting dashboards and measurement tooling. Coverage status is 'missing' for Self-Service Reporting & Dashboards across all 13 queries — meaning the site has no substantive content on this capability — despite reporting dashboards being flagged as an 'absent' feature in the taxonomy.
The /resources page (the most appropriate home for evaluation frameworks) does not contain any GEO vendor evaluation templates, RFP structures, or competitive scoring frameworks — the exact artifact type this query demands.
Resonate Labs is mentioned but loses in 2 queries where it is explicitly named as a Comparison subject: rl_097 ('Resonate Labs vs Omniscient Digital on track record') and rl_098 ('Resonate Labs vs GenOptima — does performance-based pricing beat a fixed engagement'). In both cases AI platforms characterize Resonate Labs as higher-risk with unverifiable public proof, making track record and pricing model transparency the specific positioning weaknesses driving these losses.
Resonate Labs is invisible across 13 queries where buyers are evaluating technical GEO capabilities including crawler accessibility, schema markup, structured data, and LLM-specific optimization techniques. Coverage status is 'thin' for Technical LLM Accessibility Optimization across all 13 queries, and the feature is rated 'moderate' coverage in the taxonomy — indicating partial but insufficient treatment on existing pages.
The /partners page does not explicitly name B2B SaaS as the primary client segment served, missing the matching signal for 'best GEO agencies for B2B SaaS companies.'
The /partners page contains no competitive context positioning Resonate Labs relative to named competitors (Graphite, GenOptima), giving AI engines nothing to cite when generating 'should we add X to the list' responses.
The /partners page contains no competitive differentiation language contrasting Resonate Labs with broad-scope GEO agencies like Omniscient Digital — AI engines have no extractable claim to cite when generating alternative recommendations.
The /partners page does not use the specific language 'AI citations' or describe the outcome of the service in terms of being cited by LLMs — the precise value proposition this query targets.
The /partners page does not explicitly state that Resonate Labs produces and publishes content (writes, edits, publishes) versus only auditing or advising — the core filter buyers apply in this query.
The /partners page describes the partner program outcome ('scale your GEO service line') but contains no passage explaining the process by which buyer AI queries are identified and mapped — the exact question buyers are asking in this query cluster.
The /visibility/ page does not address the 'platform vs. agency' decision — it likely describes the audit product without explaining when a technical team needs an agency vs. a tool.
The /visibility/ page describes the audit as a product but does not explain the underlying methods B2B companies use to measure AI recommendation visibility (manual prompt testing, automated monitoring, platform analytics) — the educational content this query triggers.
The homepage does not directly address the 'is this fixable?' question with a confident, evidence-backed answer — the primary psychological need of a buyer discovering AI recommendation gaps for the first time.
The /partners page contains no description of the implementation or onboarding process for a new GEO engagement, leaving AI engines with nothing to cite when buyers research what switching to a GEO agency involves.
The /visibility/ page describes the AI visibility audit but does not explicitly name Series B SaaS companies as a target client segment, missing the persona-matching signal AI engines need for this query.
The /visibility/ page does not address the 'just realized we're invisible in AI search' discovery moment — the specific trigger described in this query, limiting its relevance to first-discovery buyer contexts.
The rendered output for the homepage (/) and the partner program page (/partners) each surfaces two H1-level headings. On the homepage these are 'Generative Engine Optimization' and 'We don't track what AI says about you. We change it.'; on /partners they are the page-title string ('Partner Program — License GEO for your B2B agency | Resonate Labs') and the hero headline ('Scale your agency's GEO service line — without staffing a research team.'). The remaining H2/H3 nesting on both pages is logical and uses descriptive noun phrases.
The /partners page contains no technical implementation content relevant to a Head of Digital Marketing evaluating engineering complexity of GEO tool transitions.
The /resources page does not contain multi-platform AI coverage Comparison content — the specific content format this artifact query targets — leaving AI engines with nothing to cite from Resonate Labs.
The /partners page does not distinguish between PR-based GEO approaches (earned media, brand mentions) and content-based GEO (structured content optimization, citation engineering) — the key distinction buyers probe when evaluating Genevate alternatives.
The homepage states the problem ('AI shapes buyer shortlists') but does not provide the 'how teams get ahead of it' educational answer that this query demands — AI engines need a named strategy, not just a problem statement.
The /partners page does not address SEO-to-GEO transition risks or how Resonate Labs manages content continuity when a team is switching from an existing agency retainer.
The /partners page does not describe the content quality standards, editorial review process, or what makes Resonate Labs' content 'AI-citation-ready' versus standard SEO content — missing the quality differentiation signal.
The /resources page does not establish Resonate Labs' thought leadership credentials in terms of technical B2B content optimization — the specific expertise signal this query targets.
Our analysis reads rendered markdown returned by an automated fetch, which executes after any client-side rendering. All five pages returned readable body content, so no rendering failure was observed. However, two conversion pages (/brief/ and /visibility/) returned very sparse body content. This is most likely thin-by-design (short conversion landing pages), but we cannot confirm from rendered output whether any content is injected client-side and therefore invisible to crawlers that do not execute JavaScript.
Page URLs use inconsistent trailing-slash conventions: /brief/ and /visibility/ end with a trailing slash, while /partners and /resources do not. This inconsistency is reflected directly in the published sitemaps.
Meta description tags and Open Graph / social-preview tags live in the HTML <head> and are not present in the rendered markdown our method analyzes. We therefore cannot confirm whether these tags exist or are well-formed on any page.
Crawlable URLs are split across two separate sitemaps declared in robots.txt: sitemap.xml lists /, /brief/, and /visibility/; sitemap-geo.xml lists /partners and /resources. Neither file references the other, and there is no parent sitemap index unifying them. Both are correctly declared as Sitemap: directives in robots.txt, so a compliant crawler reading robots.txt will still discover both.
Our fetch method returns rendered markdown rather than raw HTML, so JSON-LD schema blocks are not visible to the analysis. We could not determine whether any page carries Organization, Service, FAQPage, or Article schema. Note: the /resources and /partners pages both present clear FAQ sections in their visible content, which are strong candidates for FAQPage markup if not already present.
All three workstreams can start this week.
[Data] Total recommendations: 148. L1: 1 fix (multiple H1s) + 5 verification checks. L2: 82 content optimization recommendations targeting 82 gap queries where existing pages cover the topic but fail to earn visibility.
L3: 60 new content recommendations targeting capability voids — ROI Attribution & Pipeline Impact Measurement (thin coverage across 26 queries), Self-Service Reporting & Dashboards (missing coverage across 9 queries), Technical LLM Accessibility Optimization (thin coverage across 10+ queries).
[Synthesis] The 148 recommendations divide into a clear sequence. L1 structural work — resolving dual H1 headings and verifying crawlability, schema, and canonical configuration — must execute first because it determines whether L2 and L3 content is parseable by AI crawlers at all. L2 optimizations target 82 queries where Resonate Labs already has relevant pages but fails to earn mentions, addressing the majority of the gap at lowest cost.
L3 new content targets the 60 queries — concentrated in ROI attribution and reporting dashboards — where no competitive content currently exists.
Gap coverage note: 80 of 142 gap queries (56%) are assigned to an L2 or L3 action item. 62 gap queries remain unrouted — these may represent edge-case queries that don’t cluster neatly or fall below the LLM’s grouping threshold.