Competitive intelligence for AI-mediated buying decisions. Where Dodeka Digital wins, where it loses, and a prioritized three-layer execution plan — built from 150 buyer queries across ChatGPT + Claude.
Dodeka's 5.33% visibility rate is not a reflection of the agency's quality — it is a reflection of where its content lives relative to where buyers are searching.
[Mechanism] Three compounding gaps create the visibility pattern. First, the entire content library is conversion-oriented: service pages, portfolio work, and a pricing page answer 'what does Dodeka do?' but none address the discovery-stage questions buyers ask before they know which agency to consider. Second, no Comparison pages exist anywhere on the domain — Comparison is the one buying stage where Dodeka shows up (15.6% = 5/32), but only because buyers occasionally find it by accident; without Comparison pages, Dodeka is structurally excluded from the 32-query Comparison buying job.
Third, four capability categories have zero content coverage (SEO/organic, LLM visibility, email, ABM), which means buyers filtering for those capabilities route to competitors before Dodeka enters any consideration.
[Synthesis] L1 technical fixes must execute before L2 and L3 content investment because three specific findings directly undermine content ROI: the sitemap missing lastmod timestamps means new and updated pages will not receive freshness attribution from AI crawlers (all 62 L3 and 82 L2 pages are affected); the broken heading hierarchy on /growth-marketing, /website-audit, and /paid-media-audit reduces AI extractability on three of the highest-query-volume pages before any content edits are made; and stale blog content means the four existing SEO assets compete at a freshness disadvantage that blocks citation even when content is otherwise relevant.
Where Dodeka Digital appears and where it doesn't — across personas, buying jobs, and platforms.
[TL;DR] Dodeka Digital is visible in 5% of buyer queries and wins 75% of those. The primary challenge is getting visible in the first place.
Dodeka is visible in 5.33% of queries (8/150) but wins 71.4% of visible high-intent interactions — structural content gaps in the early funnel, not messaging quality, are the primary driver of low overall visibility.
| Dimension | Combined | Platform Delta |
|---|---|---|
| All Queries | 5.3% | Even |
| By Persona | ||
| Chief Financial Officer | 0% | Even |
| Co-Founder / CEO | 20% | Even |
| Head of Growth | 0% | Even |
| Director of Product Marketing | 0% | Even |
| VP of Marketing | 5.6% | Even |
| By Buying Job | ||
| Artifact Creation | 0% | Even |
| Comparison | 15.6% | Even |
| Consensus Creation | 7.7% | Even |
| Problem Identification | 0% | Even |
| Requirements Building | 0% | Even |
| Shortlisting | 0% | Even |
| Solution Exploration | 0% | Even |
| Validation | 8.3% | Even |
| Dimension | ChatGPT | Claude |
|---|---|---|
| All Queries | 5.3% | 5.3% |
| By Persona | ||
| Chief Financial Officer | 0% | 0% |
| Co-Founder / CEO | 20% | 20% |
| Head of Growth | 0% | 0% |
| Director of Product Marketing | 0% | 0% |
| VP of Marketing | 5.6% | 5.6% |
| By Buying Job | ||
| Artifact Creation | 0% | 0% |
| Comparison | 15.6% | 15.6% |
| Consensus Creation | 7.7% | 7.7% |
| Problem Identification | 0% | 0% |
| Requirements Building | 0% | 0% |
| Shortlisting | 0% | 0% |
| Solution Exploration | 0% | 0% |
| Validation | 8.3% | 8.3% |
[Data] Overall visibility: 5.33% (8/150 queries). Early-funnel visibility: 0% (0/45 queries across Problem Identification, Solution Exploration, Requirements Building). Comparison buying job: 15.6% (5/32) — highest visibility stage.
Shortlisting: 0% (0/24). Validation: 8.3% (2/24). Founder/CEO: 20% visible (6/30 queries).
Head of Growth: 0% (0/35). CFO: 0% (0/24). Role gap: 75pp (decision-makers win 75% = 6/8 visible; evaluators 0% = 0/60).
[Synthesis] Dodeka's visibility concentrates almost entirely at the Comparison stage (15.6% = 5/32) — the one buying job with a Comparison framing in the query. The complete absence of early-funnel visibility (0/45 queries) means buyers are never exposed to Dodeka while forming their consideration set, and the 0% visibility for Head of Growth (0/35 queries) and CFO (0/24 queries) leaves two of five buyer personas entirely unaddressed. The pattern points to a content library optimized for warm, brand-aware prospects rather than cold discovery-stage buyers.
38 queries won by named competitors · 30 no clear winner · 74 no vendor mentioned
Sorted by competitive damage — competitor-winning queries first.
| ID | Query | Persona | Stage | Winner |
|---|---|---|---|---|
| ⚑ Competitor Wins — 38 queries where a named competitor captures the buyer | ||||
| dod_047 | "Top growth marketing agencies for early-stage startups with no in-house marketing team" | Co-Founder / CEO | Shortlisting | NoGood |
| dod_049 | "Our agency charges $20K and we're only Series A — who does good growth marketing for startups under $15K a month?" | Chief Financial Officer | Shortlisting | Tuff |
| dod_050 | "Growth agencies that combine brand design with performance marketing for tech startups" | Director of Product Marketing | Shortlisting | NoGood |
| dod_051 | "Which growth agencies have strong SEO and content capabilities alongside paid media for startups?" | VP of Marketing | Shortlisting | Single Grain |
| dod_054 | "Full-service growth agencies for startups spending $10-30K per month on marketing" | Chief Financial Officer | Shortlisting | NoGood |
| dod_063 | "Best full-service growth agencies to replace multiple freelancers with one cohesive team" | Co-Founder / CEO | Shortlisting | NoGood |
| dod_066 | "Startup-focused agencies that do both brand identity and growth marketing under one roof" | Director of Product Marketing | Shortlisting | NoGood |
| dod_068 | "Best growth marketing agencies in Charlotte or Atlanta area for SaaS startups" | Co-Founder / CEO | Shortlisting | NoGood |
| dod_069 | "Need to switch web and marketing agencies — looking for one team that handles both for startups" | Head of Growth | Shortlisting | NoGood |
| dod_070 | "Tuff Growth vs other boutique growth agencies — which is better for SaaS startup paid media?" | VP of Marketing | Comparison | Tuff |
Remaining competitor wins: NoGood ×10, Galactic Fed ×7, Tuff ×6, WEBITMD ×3, Single Grain ×1, Ladder ×1. 30 queries with no clear winner. 74 queries with no vendor mentioned. Full query-level data available in the analysis export.
Queries where Dodeka Digital is mentioned but a competitor is positioned more favorably.
| ID | Query | Persona | Buying Job | Winner | Dodeka Digital Position |
|---|---|---|---|---|---|
| dod_077 | "Dodeka Digital vs Tuff — both claim to be an extension of your team, which actually delivers?" | Co-Founder / CEO | Comparison | Tuff | Strong 2nd |
| dod_096 | "Dodeka Digital vs Single Grain for AI visibility optimization — who has more startup experience?" | VP of Marketing | Comparison | Single Grain | Strong 2nd |
Who’s winning when Dodeka Digital isn’t — and who controls the narrative at each buying stage.
[TL;DR] Dodeka Digital wins 4% of queries (6/150), ranks #8 in SOV — H2H record: 2W–3L across 5 competitors.
SOV rank 8 of 10 (8 mentions vs. NoGood's 36) masks a quality advantage: Dodeka beats NoGood and Galactic Fed head-to-head while losing to Tuff, WEBITMD, and Single Grain. The gap is content volume and category presence, not performance once visible — fixing the discovery layer would close the SOV gap over time.
| Company | Mentions | Share |
|---|---|---|
| NoGood | 36 | 24.5% |
| Tuff | 26 | 17.7% |
| Ladder | 19 | 12.9% |
| Single Grain | 15 | 10.2% |
| Galactic Fed | 15 | 10.2% |
| WEBITMD | 14 | 9.5% |
| Ironpaper | 8 | 5.4% |
| Dodeka Digital | 8 | 5.4% |
| Disruptive Advertising | 5 | 3.4% |
| LAIRE Digital | 1 | 0.7% |
When Dodeka Digital 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 142 queries where Dodeka Digital is completely absent:
Vendors appearing in responses not in Dodeka Digital’s defined competitive set.
[Synthesis] The H2H record (2 wins, 3 losses across 5 matchups with only 1 query per matchup) should not be read as competitive balance — it reflects extremely limited co-appearance. The meaningful number is SOV: NoGood appears in 24.5% of all responses while Dodeka appears in 5.44%, a 19pp presence gap driven by content volume and category authority, not messaging quality. Dodeka's 71.4% conditional win rate is the strongest signal in the audit — when the playing field is level, Dodeka competes well.
The strategic imperative is getting onto that playing field, which requires SEO/content depth, Comparison pages, and early-funnel education content that NoGood and Tuff have already published.
What AI reads and trusts in this category.
[TL;DR] Dodeka Digital had 15 unique pages cited across buyer queries, ranking #2 among all cited domains. 10 high-authority domains cite competitors but not Dodeka Digital.
dodekadigital.com ranks #2 among cited domains with 43 citation instances across 15 unique pages — existing content has real authority. The 10-query third-party gap reveals that buyers in discovery stages find directories and editorial sources before they find dodekadigital.com, signaling a need for both on-domain educational content and off-domain third-party citation presence.
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 Dodeka Digital — off-domain authority opportunities.
These domains cited competitors but did not cite Dodeka Digital pages in the queries analyzed. This reflects citation patterns in AI responses, not overall platform presence.
[Synthesis] The #2 citation rank for dodekadigital.com with 43 citation instances is a meaningful authority signal — the site's 15 cited pages are being retrieved and surfaced when queries match existing content. However, the 10-query third-party gap reveals that for a significant portion of buyer queries, external directories and editorial sources (Clutch, G2, industry publications) are providing the citations AI uses. This indicates a third-party presence gap: Dodeka needs more off-domain editorial and directory citations to capture the queries where AI reaches for external Validation rather than citing the client's own pages.
Three layers of recommendations ranked by commercial impact and implementation speed.
[TL;DR] 21 priority recommendations (plus 5 near-rebuild optimizations) targeting 144 gap queries (142 invisible, 2 positioning gaps). 5 L1 technical fixes + 2 verification checks, 8 content optimizations (L2), 6 new content initiatives (L3).
151 recommendations address all 144 gap queries in three sequenced layers: L1 technical fixes unlock freshness and extractability for everything that follows; L2 optimizations deepen 82 existing pages with buyer framing and claim specificity; L3 builds the 62 missing content pieces starting with the Comparison architecture and LLM visibility positioning.
Reading the priority numbers: Recommendations are ranked 1–21 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 |
|---|---|---|---|
| #1 | All blog content is over 365 days old | High | 1-2 weeks |
| #2 | Schema markup status cannot be verified — manual check recommended | Medium | 1-3 days |
| #12 | Case studies lack visible publication or update dates | Medium | < 1 day |
| #13 | Multiple H1 tags on key landing pages | Medium | 1-3 days |
| #14 | Sitemap lacks lastmod timestamps on all URLs | Medium | < 1 day |
Items requiring manual review before determining if action is needed.
| Priority | Finding | Impact | Timeline |
|---|---|---|---|
| #20 | Meta descriptions and OG tags cannot be verified — manual check recommended | Low | 1-3 days |
| #21 | No explicit AI crawler directives in robots.txt | 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 /pricing page displays retainer tiers but does not include a 'Total Cost of Ownership' Comparison between a full-service retainer and managing separate paid, creative, and web vendors — buyers asking dod_022 and dod_130 ('cost Comparison: one agency vs. separate vendors') cannot extract this from the current pricing page. The /pricing page does not address the 'how should a startup evaluate growth agencies?' question (dod_031) or include a 'What's Included' breakdown granular enough to be citable by AI for requirements-building queries. The homepage does not include a 'Vendor Consolidation' value proposition section — buyers asking 'best full-service agencies to replace multiple freelancers with one team' (dod_063) find a brand page, not a positioning statement on consolidation.
Queries affected: dod_002, dod_006, dod_014, dod_022, dod_031, dod_042, dod_047, dod_054, dod_063, dod_103, dod_109, dod_116, dod_125, dod_126, dod_130, dod_139, dod_147
The /services/growth-marketing page leads with 'What we do' framing rather than buyer-diagnostic framing — buyers asking 'what are the signs I need an agency?' find a service description, not an answer to their question. The /services/growth-marketing page has no attribution methodology section — buyers asking 'what attribution models do agencies use for multi-channel campaigns?' (dod_029) cannot extract a credible answer from this page. The /paid-media-audit page exists but does not explain the ROI case for the audit or answer 'how much should a startup spend before considering agency help?' (dod_009) — it is a lead-capture page, not an educational asset.
Queries affected: dod_001, dod_009, dod_015, dod_019, dod_030, dod_037
The /services/growth-marketing page states Dodeka's services but does not include a startup-budget-range positioning statement — buyers asking 'who does good growth marketing for startups under $15K/month?' (dod_049) cannot extract Dodeka's pricing tier from this page. The /services/growth-marketing page has no 'Why Dodeka vs. [Larger Agency]' section — buyers comparing Dodeka to NoGood or WEBITMD find no differentiation argument on the page. The /growth-marketing page does not include specific client ROI benchmarks (CPL reduction, ROAS improvement) that would make it citable for 'which agency delivers measurable ROI' queries (dod_046, dod_102, dod_122).
Queries affected: dod_046, dod_049, dod_060, dod_068, dod_102, dod_105, dod_117, dod_122, dod_127, dod_132, dod_134, dod_140, dod_149
The /roi-calculator page functions as a lead-capture form with a ROI estimate output — it does not explain Dodeka's attribution methodology or what inputs/assumptions drive the calculation, making it non-citable for 'how do agencies attribute ad spend to revenue?' queries (dod_029, dod_045). The /blog/marketing-analytics-tools-101 post lists tools but does not answer 'what KPIs should I require from an agency to avoid vanity metrics?' (dod_033) — the buyer question requires agency standards guidance, not a tool Comparison. The /blog/why-roi-tracking-is-essential post explains why tracking matters but does not provide CFO-facing guidance on 'what should I expect from an agency in the first 90 days?' (dod_135) or 'how to build a business case for agency spend to investors' (dod_128, dod_142).
Queries affected: dod_003, dod_004, dod_017, dod_029, dod_033, dod_045, dod_053, dod_062, dod_104, dod_110, dod_120, dod_128, dod_135, dod_142
The /services/websites page shows design work but has no CRO methodology section — buyers asking 'which agencies are best at improving landing page conversion rates for B2B SaaS?' (dod_048, dod_065) cannot determine from this page whether Dodeka does real CRO testing or just cosmetic design changes. The /services/websites page has no A/B testing process description — buyers asking 'what A/B testing and experimentation capabilities matter most?' (dod_044) find a portfolio page, not a methodology answer. The /website-audit page does not specify what payback or conversion improvement outcome clients should expect from a redesign (dod_129) — 'we spent $30K on a redesign and conversion rate didn't change' is a buyer fear this page should directly address.
Queries affected: dod_011, dod_020, dod_032, dod_044, dod_048, dod_065, dod_108, dod_118, dod_129, dod_141, dod_146
The /services/creative page has no 'When to Invest in a Startup Rebrand' section — buyers asking dod_005 ('when should a growth-stage startup invest in a professional rebrand?') find portfolio images, not a diagnostic framework. The /services/creative page does not address the 'brand agency vs. growth agency that does brand work' positioning question (dod_018) — it shows what Dodeka has created, but not why choosing Dodeka for brand work over a pure brand agency is strategically sound. Case study pages (Canvs, Balata, Copient AI) show before/after design work but include no business outcome metrics — 'must-have creative capabilities when evaluating a full-service growth agency' (dod_034) requires specific capability statements buyers can evaluate.
Queries affected: dod_005, dod_018, dod_034, dod_050, dod_066, dod_106, dod_131, dod_143
The /services/growth-marketing page has no campaign launch timeline or creative velocity benchmark — buyers asking 'our campaigns take 6 weeks to launch, is that normal?' (dod_012) cannot determine from this page what Dodeka's launch timeline actually is. The /services/growth-marketing page has no creative testing process description — buyers evaluating whether an agency does 'real' creative testing vs. gut-feel creative selection (dod_040, dod_025) find no process information. The /work/clutch and /work/copient-ai case studies contain creative work but no creative testing metrics (number of variants tested, winning variant lift, test cycle duration) — making them non-citable for dod_138 and dod_111 queries.
Queries affected: dod_012, dod_025, dod_040, dod_056, dod_111, dod_138
The /services/websites page showcases design outcomes (visual portfolio) but has no 'Is Your Website Costing You Leads?' diagnostic section — buyers asking dod_007 need specific signals to look for, not a design gallery. The /services/websites page does not address the 'separate web agency vs. integrated' positioning question (dod_021, dod_069) — it describes Dodeka's web work without explaining why integrated web + marketing is superior to a standalone web agency. The /website-audit page is a lead-capture form with no educational content explaining what a web audit reveals, what conversion problems it identifies, or what outcomes clients see after an audit — it cannot answer dod_038 or dod_052.
Queries affected: dod_007, dod_021, dod_038, dod_052, dod_058, dod_069, dod_114
Net new content addressing visibility and positioning gaps. Owner: Content Strategy. Timeline: Months.
Comparison is the buying job with the second-highest visibility rate in this audit (15.6% = 5/32 queries), meaning buyers are actively searching competitor comparisons at this stage — yet Dodeka loses all of them because no Comparison content exists anywhere on the domain. When buyers ask 'Dodeka Digital vs Tuff — which actually delivers?' (dod_077), the agency loses to Tuff on its own named query. The structural absence of Comparison pages means AI models cannot extract Comparison framing from dodekadigital.com and default to citing competitors who have published Comparison content. Building a Comparison content hub is the single highest-leverage structural investment available to Dodeka.
ChatGPT (high): Comparison queries on ChatGPT returned specific competitor names and structured Comparison framing in nearly all responses. ChatGPT surfaces pages with explicit 'vs' URL patterns and Comparison tables — Dodeka's absence from these responses is directly traceable to the missing page type. Claude (high): Claude shows high receptivity to factual, structured Comparison content with clear attributable claims. Citation-worthy passages from Comparison pages (e.g., 'Dodeka handles both website build and paid media under one retainer, unlike Tuff which subcontracts web work') are the format Claude extracts and surfaces.
Buyers searching for growth agencies increasingly require an answer to 'do you do SEO and content alongside paid?' — 13 queries in this cluster span the full buyer journey, from 'what happens to startups that rely 100% on paid?' (problem_id) to Comparison queries benchmarking competitor SEO capabilities. Dodeka has no content staking a position on organic growth, leaving Single Grain and NoGood (the two highest-SOV competitors) as the default answers. The pain point Company has no organic search presence, relying entirely on paid channels which maps directly to this cluster — buyers asking about organic invisibility risk are the same buyers Dodeka needs to reach, and Dodeka itself is organically invisible in those conversations.
ChatGPT (high): ChatGPT consistently cited agencies with published SEO methodology pages and case studies showing organic traffic results. Single Grain's content depth on SEO for SaaS is the pattern Dodeka needs to match — structured service pages with extractable claims. Claude (medium): Claude surfaced agencies with factual, citation-worthy organic growth content. A pillar post with specific data points (e.g., 'client X grew from 0 to 15K organic monthly visits in 9 months') would generate extractable passages Claude can cite in agency recommendation queries.
Dodeka is running a GEO visibility audit business yet is invisible in every query about AI search visibility optimization — this is a fundamental credibility gap that undermines the agency's core positioning. Single Grain wins the direct head-to-head (dod_096) and No Clear Winner outcomes dominate Shortlisting queries, meaning Dodeka is failing at the exact buying journey stage that is most relevant to its own service. Buyers searching 'which marketing agencies help startups show up in AI search results?' are Dodeka's ideal clients — and Dodeka does not appear in the answer. The commercial impact is compounding: each lost LLM & AI Search Visibility Optimization query not only represents a prospect lost, but damages the agency's credibility in a category it claims to lead.
ChatGPT (high): ChatGPT surfaces Single Grain on LLM visibility queries because Single Grain has published accessible content on AI search optimization. A dedicated GEO service page with structured how-it-works sections would match the format ChatGPT is already citing from competitors. Claude (high): Claude shows high receptivity to well-sourced, factual content on AI search mechanisms. An audit methodology page or guide with specific diagnostic criteria would generate the citation-worthy passages Claude needs to recommend Dodeka for LLM visibility queries.
Marketing automation capability is a qualifier question for many B2B startup buyers selecting a growth agency — 'do they handle HubSpot setup or do I need a separate RevOps partner?' is a common vetting query. Dodeka's silence on this topic means buyers routing these questions to AI will never encounter the agency as an option. Head of Growth is the primary persona for this cluster, and with Head of Growth showing 0% visibility overall (0/35 queries), this represents a significant evaluator-stage blind spot that blocks deals downstream.
ChatGPT (medium): ChatGPT cited agencies with accessible HubSpot expertise documentation (partner pages, case studies, methodology). A structured automation capability section would improve Dodeka's extractability for this query type. Claude (medium): Claude surfaces factual, verifiable capability claims. A page that lists specific automation services with named tools (HubSpot, Salesforce, Klaviyo) and client context would provide the structured content Claude needs.
Email nurture is a baseline expectation for many growth agency retainers — buyers who don't find a clear answer on an agency's site about email capability will default to agencies that have published this information. Dodeka's silence creates doubt: does the agency do email at all, or is it a paid-media-only shop? Head of Growth and VP of Marketing are the primary personas here, and both are evaluator/decision-maker roles with real buying authority. Six queries spanning all buying stages represent a systematic void that, unlike ABM, could be addressed with relatively limited content investment.
ChatGPT (medium): ChatGPT returned No Clear Winner for most email-related queries, indicating a content vacuum. A structured service description with clear scope and platform expertise would be surfaced. Claude (medium): Claude favors factual, well-organized capability claims. An email service section with named tools (Klaviyo, HubSpot Sequences) and example use cases would provide the extractable structure needed.
ABM (account-based marketing) is a fast-growing B2B startup marketing priority, and buyers are actively asking whether growth agencies can deliver it or whether they need a specialist. Dodeka has zero content on this topic — not thin, but entirely absent — meaning AI models have nothing to cite when ABM capability is in scope. The 'missing' coverage status across all 6 queries means Dodeka cannot even partially satisfy these buyer questions. Head of Growth and VP of Marketing drive these queries, both with buying authority. Because no competitors dominate most ABM queries (No Vendor Mentioned or No Clear Winner), this is a category where Dodeka can become the reference answer with relatively focused content investment.
ChatGPT (high): ChatGPT returned No Vendor Mentioned for most ABM queries, meaning it found no reliable agency-level content to cite. A well-structured ABM service page or guide would be surfaced with high receptivity given the current content vacuum. Claude (high): Claude shows high receptivity to educational, well-structured content on relatively underserved topics. An ABM guide with a clear 'when startups need ABM' framework would generate the citation-worthy, factual passages Claude prioritizes in recommendation responses.
All recommendations across all three layers, ranked by commercial impact × implementation speed.
All 4 blog posts were published between October and December 2024 and have not been updated since. The most recent post is from December 11, 2024 — over 15 months old at the time of analysis. No new blog content has been published since.
Our analysis method returns rendered page content as markdown text, which does not include JSON-LD schema markup, meta tags, or other HTML head elements. We cannot confirm whether appropriate schema types (Organization, LocalBusiness, Service, Article, FAQPage) are implemented.
10 of 62 L3 gaps (16.1% = 10/62) target LLM & AI Search Visibility Optimization feature queries. All 10 are routed as 'thin' or positioning gaps — dod_096 is a direct positioning loss where 'Dodeka Digital vs Single Grain for AI visibility optimization' results in Single Grain winning. The agency offers GEO/LLM visibility as a differentiating service but has produced no content establishing this claim for AI citation.
21 of 62 L3 gaps (33.9% = 21/62) trace to Comparison-intent queries that triggered an AFFINITY OVERRIDE: the buying job requires Comparison page types but none exist on dodekadigital.com — case studies, feature pages, landing pages, blogs, and a pricing page are present, but zero dedicated Comparison or 'vs' pages. Two additional positioning gaps (dod_077, dod_096) show Dodeka appearing in direct-named comparisons but losing to Tuff and Single Grain respectively.
6 of 62 L3 gaps (9.7% = 6/62) target Account-Based Marketing & ABM Campaigns feature queries, all routed with coverage status 'missing' — the most severe rating, indicating zero relevant content exists on dodekadigital.com addressing ABM capability. NoGood wins the primary Shortlisting Comparison (dod_097) and No Vendor Mentioned dominates early-funnel queries, meaning buyers aren't finding guidance on ABM from any single agency in AI responses — a first-mover opportunity exists.
The /pricing page displays retainer tiers but does not include a 'Total Cost of Ownership' Comparison between a full-service retainer and managing separate paid, creative, and web vendors — buyers asking dod_022 and dod_130 ('cost Comparison: one agency vs. separate vendors') cannot extract this from the current pricing page.
The /services/growth-marketing page leads with 'What we do' framing rather than buyer-diagnostic framing — buyers asking 'what are the signs I need an agency?' find a service description, not an answer to their question.
13 of 62 L3 gaps (21% = 13/62) target SEO & Content Marketing feature queries, all routed due to 'thin' coverage status across every buying stage from Problem Identification through Artifact Creation. Dodeka's site has 4 blog posts (all published October–December 2024, stale as of March 2026) and no service page or hub addressing SEO and organic content as a capability — Single Grain and NoGood dominate these queries by default.
The /services/growth-marketing page states Dodeka's services but does not include a startup-budget-range positioning statement — buyers asking 'who does good growth marketing for startups under $15K/month?' (dod_049) cannot extract Dodeka's pricing tier from this page.
The /roi-calculator page functions as a lead-capture form with a ROI estimate output — it does not explain Dodeka's attribution methodology or what inputs/assumptions drive the calculation, making it non-citable for 'how do agencies attribute ad spend to revenue?' queries (dod_029, dod_045).
The /services/websites page shows design work but has no CRO methodology section — buyers asking 'which agencies are best at improving landing page conversion rates for B2B SaaS?' (dod_048, dod_065) cannot determine from this page whether Dodeka does real CRO testing or just cosmetic design changes.
None of the 9 case study pages (/work/bridge, /work/clutch, /work/copient-ai, /work/canvs, /work/turaco, /work/balata, /work/connected-performance, /work/medality, /work/rapid-pos) display a visible publication date, last-updated date, or any temporal signal.
Three landing pages (/growth-marketing, /website-audit, /paid-media-audit) use 10+ H1 tags each instead of a single H1 with properly nested H2/H3 subheadings. For example, /growth-marketing has H1 tags for section headers like 'What you get', 'Who its for', 'Our Process', and 'Lets Talk' that should be H2s.
The sitemap.xml contains 31 URLs but none include lastmod dates, changefreq, or priority values. The sitemap is a flat urlset with loc elements only.
The /services/creative page has no 'When to Invest in a Startup Rebrand' section — buyers asking dod_005 ('when should a growth-stage startup invest in a professional rebrand?') find portfolio images, not a diagnostic framework.
The /services/growth-marketing page has no campaign launch timeline or creative velocity benchmark — buyers asking 'our campaigns take 6 weeks to launch, is that normal?' (dod_012) cannot determine from this page what Dodeka's launch timeline actually is.
6 of 62 L3 gaps (9.7% = 6/62) target Email Marketing & Nurture Campaigns feature queries across Problem Identification through Validation buying stages, all routed as 'thin' coverage. Buyers ask whether growth agencies handle email nurture as part of their retainer — Dodeka has no content answering this question. No_clear_winner dominates Shortlisting and Validation queries, indicating buyers are uncertain about which agency to choose and Dodeka is absent from the consideration.
6 of 62 L3 gaps (9.7% = 6/62) target Marketing Automation & Tech Stack Integration feature queries, all routed as 'thin' coverage status. Buyers ask whether growth agencies handle HubSpot and Salesforce setup — Dodeka has no page, blog post, or case study section that addresses this capability. Galactic Fed wins the direct Comparison query (dod_084) on marketing automation depth.
The /services/websites page showcases design outcomes (visual portfolio) but has no 'Is Your Website Costing You Leads?' diagnostic section — buyers asking dod_007 need specific signals to look for, not a design gallery.
Our analysis returns rendered markdown and cannot access HTML head elements including meta descriptions, Open Graph tags, Twitter Card tags, and canonical URLs. These signals affect how pages appear in AI-assisted search previews and social sharing.
The robots.txt file contains only a single Sitemap directive. No User-agent rules are defined for any crawler — AI or otherwise. All 7 monitored AI crawlers (GPTBot, ChatGPT-User, ClaudeBot, PerplexityBot, Google-Extended, Googlebot, Bytespider) have 'not_mentioned' status, meaning they are implicitly allowed.
All three workstreams can start this week.
[Synthesis] The 151 recommendations are sequenced in three layers that must execute in order. L1 technical fixes address the structural infrastructure that determines whether new and optimized content receives freshness credit and AI extractability signals — specifically, the sitemap lastmod fix unblocks freshness attribution for all L2 and L3 content before it's written. L2 optimizations deepen 82 existing pages that are already indexed and matched but underperform on extractable claim depth.
L3 new content builds the Comparison architecture and capability pages that address the 62 queries with zero page match — this is the largest leverage point for long-term visibility.