AI search is reshaping how B2B companies shortlist PR and growth marketing partners — agencies that establish visibility in AI answers now lock in a structural advantage before the category catches up. This document presents what we've learned about Trevelino/Keller's market; your job is to tell us what we got right, what we got wrong, and what we missed.
Before the audit measures citation visibility in the integrated B2B PR and growth marketing space, these three signals tell us whether AI crawlers can access, extract, and trust Trevelino/Keller's content.
B2B companies increasingly shortlist PR and growth marketing agencies through AI assistants before a human conversation ever happens — the same shift that is reshaping how their own buyers discover them. In agency selection, where reputation and rankings have always driven the shortlist, AI answers are becoming the new rankings page, and early citations compound: domains that AI platforms learn to trust get cited more as that trust accumulates. Trevelino/Keller enters this shift from a position of strength in traditional rankings but with a content foundation that freshness-weighted AI citation currently works against.
This Foundation Review is the input-validation step before the audit runs. It presents three things we're validating together: the competitive landscape that shapes which head-to-head queries get constructed, the buyer personas that determine the search intent patterns we simulate, and the Layer 1 technical baseline that determines whether AI platforms can access and extract your content at all. Each section ends with the specific questions where your answer changes the audit's architecture.
The validation call is a decision-making session, not a readout. Two kinds of decisions get made: input validation — are the right competitors in the right tiers, the right buyers with the right influence levels — and engineering triage — which technical fixes start now, before query results come back. Everything you need to prepare is aggregated in the Pre-Call Checklist near the end of this document.
What this is Before we measure how AI platforms answer buyer questions about integrated B2B PR and growth marketing agencies, we need an accurate model of your market: who buys, who you compete against, what you're strong at, and what problems drive buyers to look. This document is that model. Everything in it becomes an input to the query set the audit executes.
What you need to do Read with a red pen. Every purple box is a question where your answer changes the audit — a persona reclassified, a competitor re-tiered, a capability reweighted. Corrections are the point of this exercise, not a failure of it. Bring your marks to the validation call.
How confidence badges work High means directly sourced — your site, published rankings, or a competitor's own page. Medium means inferred from category research and cross-referenced listings. Low means weakly sourced and flagged for your explicit confirmation. Lower-confidence items are exactly where your corrections matter most.
The baseline facts every query and comparison builds on. If anything here is wrong, everything downstream inherits the error.
Validate We classified Trevelino/Keller as "startup" strictly by headcount (~43 people) — but a 23-year-old firm ranked #2 in Atlanta sells like an established mid-market agency. Should the audit simulate buyers evaluating a scrappy specialist or an established regional leader? The answer sets the budget context and language of every generated query.
5 personas: 2 decision-makers, 2 evaluators, 1 influencer. Personas drive the query set — each one gets a cluster of queries phrased the way that buyer actually searches.
Critical review area These five personas determine whose search behavior the audit simulates. A wrong role, a missing buyer, or a misjudged influence level means the audit tests queries no real prospect of yours would type. This is the section where your correction has the largest downstream effect.
Data sourcing note Role, department, seniority, influence, veto power, and technical level come directly from the knowledge graph. Role descriptions, buying jobs, and query focus areas are synthesized from those fields plus category research. Because Trevelino/Keller is a services firm with no G2/Capterra review corpus, three personas (Daniel Okafor, Priya Raman, Elena Vasquez) are inferred from agency-buyer research rather than observed reviewer data — all three carry medium confidence and need your confirmation that they appear in real deal cycles.
→ When a CMO hires you, are they buying PR credibility first or pipeline contribution first? The answer flips whether her query cluster weights earned-media language or attribution language.
→ Do founders actually run the agency evaluation themselves at your startup clients, or do they delegate to a marketing lead? If delegated, we fold his cluster into the CMO's and reallocate 10–15 queries.
→ Does the demand gen director initiate HubSpot optimization engagements on her own budget? If yes, she's an evaluator (or better) for that product line, and we add automation-stage queries she'd run alone.
→ Does corporate communications ever hold the PR retainer budget directly at your clients? If yes, she's a decision-maker and her cluster gains validation-stage queries, not just evaluation ones.
→ Is franchise development an active growth vertical or legacy business? If legacy, his query cluster dilutes the audit — and Fishman PR stays a secondary competitor rather than moving up a tier.
Missing personas? These roles sometimes appear in integrated agency deals — do they show up in yours? Marketing Operations / RevOps lead (if the HubSpot CRM cleanup conversation starts with whoever administers the instance day to day), Chief Revenue Officer / Chief Growth Officer (if your 3Gen revenue-attribution pitch lands with the revenue org rather than marketing), and PE or VC operating partner (if investors select agencies for portfolio companies — your competitor Arketi is itself PE-backed, so that motion exists in your market). Who else shows up in your deals?
5 primary + 4 secondary competitors identified across Atlanta agencies, national B2B tech firms, and vertical specialists.
Why tiers matter Tier assignments determine the head-to-head matchups the audit tests: with 5 primary competitors at 6–8 queries each, roughly 30–40 queries run direct differentiation like "Trevelino/Keller vs Jackson Spalding" or "best B2B tech PR firm in Atlanta." We're less certain about Alloy and Phase 3 — both carry medium confidence, and if either rarely appears in real pitches, moving them to secondary shifts 6–8 queries each back into category-awareness testing.
Validate the set Three tier questions decide where the head-to-head query budget goes. (1) Do national integrated firms like Walker Sands actually appear in your competitive pitches, or do you mostly win and lose against Atlanta agencies? A wrong tier here shifts a meaningful share of the query budget away from the rivals you actually face. (2) Are the medium-confidence primaries — Alloy and Phase 3 — genuinely in your deals, or directory neighbors? (3) Who's missing — and is anyone listed here (PAN, Merritt) an agency you never actually see?
11 buyer-level capabilities mapped: 4 strong, 6 moderate, 1 weak — these determine which capability queries the audit tests.
Get consistent trade and national press coverage that builds credibility with our buyers, not just a press release distribution service
One agency that connects press coverage, content, and lead generation into a single pipeline program instead of running PR and marketing in silos
A certified HubSpot partner that can clean up our CRM, build nurture workflows, and actually run marketing automation for us
An agency team that already knows our industry, speaks our buyers' language, and has relationships with the reporters who cover our space
Run targeted ABM campaigns against our named account list with coordinated ads, content, and outreach
Rebrand or refresh our visual identity, messaging, and design system without hiring a separate branding shop
Redesign and rebuild our website so it converts, with the agency handling design, copy, and development end to end
Produce video content — customer stories, product explainers, social clips — without us managing separate production vendors
Have a team on call that can manage a data breach, recall, or executive scandal before it damages the brand
Show me what PR and marketing spend actually contributed to pipeline and revenue, not impressions and ad-value equivalency
Plan and manage our paid search, social, and programmatic budgets alongside the organic and earned programs
Prioritization The audit tests all 11 capabilities, but competitive differentiation queries will emphasize 3. Four capabilities are rated Strong:
• Earned Media & Press Coverage
• Integrated PR + Demand Generation
• HubSpot & Marketing Automation Services
• B2B Vertical Expertise (Tech, Healthcare, Fintech, Franchising)
Which of these best represents where Trevelino/Keller wins deals? Based on pain point linkage, we propose Earned Media, Integrated PR + Demand Gen, and Vertical Expertise — each maps to two high-severity buyer pains — but you know your win/loss reality better than the data does.
Validate ratings The Video ("weak") and Website Design ("moderate") ratings derive largely from Sidestreet Media's adversarial comparison page — are they still accurate after the Marsden acquisition? If stronger, the audit under-tests capabilities you can win on; if accurate, they mark gaps a competitor is already exploiting in comparison content. Also: Paid Media is our lowest-confidence rating and needs a strength check against Walker Sands and Arketi specifically, and should Brand Identity & Creative and Website Design merge into a single Re:FRESH capability? What capabilities are we missing entirely?
9 pain points: 4 high, 5 medium severity — this buyer language is how the audit's queries will actually be phrased.
Validate pains Two checks and one probe. First, severity: is "dry franchise development pipeline" really high-severity for your book of business, or does that depend on the franchising-vertical answer from the personas section? Second, language: do these first-person quotes sound like your actual prospects, or like a different budget tier? Third, pains that sometimes drive integrated-agency evaluations but aren't in this set — clients demanding AI-answer visibility from their PR spend (increasingly the reason this category gets re-evaluated), analyst relations gaps for B2B tech clients courting Gartner/Forrester coverage, and content velocity bottlenecks where approval cycles starve the program. What's missing?
Technical and structural findings from the crawl of trevelinokeller.com — 42 pages analyzed. These are handoffs your team can act on now, before the audit measures citation visibility.
Actionable now No critical blockers — AI crawler access is fully open (GPTBot, ClaudeBot, PerplexityBot and peers all allowed), which is the single most important baseline signal. But two high-severity content-integrity issues need immediate attention: Content should complete or unpublish the lorem ipsum Instnt case study today and begin the case study/practice page refresh cadence; Marketing should 301-redirect the duplicate ABM blog post; Engineering should remove the malformed Crawl-delay directive and run the schema verification pass. All of these can start before the validation call.
What we found: The Instnt case study (/instnt-case-study/) is published, linked in the page sitemap (lastmod 2025-07-17), and fully crawlable, but its entire body is lorem ipsum filler with "Headline Goes Here" section headings and placeholder image references. It has been live in this state for over a year.
Why it matters: AI crawlers index this page as real content attributed to Trevelino/Keller. A vendor-evaluation query about the firm's fintech or identity-verification work could surface a page of literal filler text, which damages credibility and wastes a case-study slot for a fintech client (Instnt) in a vertical the firm actively sells into.
Recommended fix: Either complete the Instnt case study with real narrative and results, or unpublish the page and remove it from the sitemap (301 to /resources/) until content is ready.
What we found: All 7 case studies have sitemap lastmod dates older than 365 days (oldest: Werner, Oct 2024). 10 of 16 product/landing pages are older than 180 days, including all 8 market practice pages (6 of them older than a year, e.g. Lifestyle at Sep 2024). Only the Public Relations and Growth Marketing service pages (Aug 2026) and the homepage (Apr 2026) show recent updates.
Why it matters: AI answer engines weight freshness heavily — 76.4% of ChatGPT's most-cited pages were updated within the last 30 days (ConvertMate, 2025; ChatGPT-scoped), and AI-cited content is 25.7% fresher on average across platforms than traditional organic results (Ahrefs, August 2025). Case studies are the firm's strongest proof-of-outcome content, and they are functionally invisible to freshness-weighted citation.
Recommended fix: Establish a refresh cadence: update each case study with current results and a visible "Updated" date (quarterly for the top 3), and touch each practice page at least every 90 days with new client names, rankings, or stats. Prioritize Carvana, Werner, and the Technology/Franchising practice pages.
What we found: Both /stakes-are-high-when-abm-lacks-sales-and-marketing-alignment/ (now retitled "ABM Beyond Paid Media: Building a True Account Surround Strategy", Aug 10, 2026) and /stakes-are-high-when-abm-lacks-sales-and-marketing-alignment-2/ ("Stakes Are High When ABM Lacks Sales and Marketing Alignment", Jul 30, 2026) are published and in the post sitemap, and both appear on the homepage blog feed. The "-2" slug indicates a WordPress duplicate that was published instead of replacing the original.
Why it matters: Near-duplicate posts split crawl signals and link equity for the firm's ABM topic cluster, and the "-2" slug looks like an editorial error to any reader (or AI) that lands on it. ABM is a capability the firm actively markets, so this is a visible hygiene issue on commercially relevant content.
Recommended fix: Choose the canonical post, 301-redirect the other slug to it, and remove the redirected URL from the sitemap.
What we found: Primary commercial pages lead with stylistic headings: "Hype Is Real" (Technology), "The Dollar Isn't What It Used To Be" (Financial Services), "Two Means #1" (Inside TK), "When Your CRM Needs A CRM" (homepage), "Practice Makes Perfect" (Practices). 9 of 16 product/landing pages scored 0.4 on heading hierarchy, versus 0.8+ on the blog's how-to posts.
Why it matters: LLMs use headings as passage labels when extracting and citing content. A heading like "Hype Is Real" gives an answer engine no signal that the passage describes the #1-ranked technology PR practice in the Southeast — so the passage is less likely to be retrieved. The blog demonstrates the site can do this well; the commercial pages don't.
Recommended fix: Keep the brand voice but pair it with descriptive structure: make the descriptive claim the H2 ("Atlanta's #1-Ranked Technology PR Practice") and keep the slogan as styled text, or extend headings to carry meaning ("Hype Is Real: PR for the Age of Intelligence"). Apply to the 8 practice pages, homepage, and Inside TK first.
What we found: The homepage (content depth 0.4) is a sequence of one-line taglines ("#1 Tech Agency In The Southeast", "#1 Retention") without supporting substance, and /services/ (0.4) lists service areas as pipe-delimited keywords ("Earned | Shared | Owned | Crisis") rather than explaining them. DiscoverAI (0.5) lists AI service names without describing what any service actually does. Claims like "#1 Ranked In Atlanta" appear without source or context.
Why it matters: These are the pages AI engines most reliably fetch when asked "who is Trevelino/Keller". Unsupported superlatives are exactly the kind of claim LLMs discount; a single passage stating the O'Dwyer's ranking, headcount, and practice areas in prose would be far more citable than a wall of taglines.
Recommended fix: Add a citable "About" passage to the homepage and /services/ that states in complete sentences: what the firm is, the O'Dwyer's #2 Atlanta ranking (with source), the 12 national vertical rankings, headcount, and the 3Gen methodology in one 100-150 word block.
What we found: robots.txt opens with "Crawl-delay: 10" positioned before the first User-agent group. No crawler is disallowed from content (the only Disallow is a WP-Optimize plugin JSON file).
Why it matters: Googlebot and most AI crawlers (GPTBot, ClaudeBot, PerplexityBot) ignore Crawl-delay, so impact is limited — but crawlers that do honor it (e.g., some Bing-derived and secondary bots) are throttled to ~8,600 pages/day, and the directive's placement above the User-agent line makes it technically malformed. It signals unmaintained crawler configuration.
Recommended fix: Remove the Crawl-delay directive (or scope it deliberately under a specific User-agent if server load is a real concern), and keep the Yoast-managed allow-all block.
The following items could not be assessed through our analysis method (rendered markdown). We recommend your engineering team verify these manually before the validation call.
What to check: Schema markup cannot be assessed from rendered page output — JSON-LD blocks are not visible to our analysis method. The site runs WordPress with Yoast SEO, which typically emits Organization/WebPage/Article schema by default, but coverage and field population are unverified. Appropriate schema helps AI engines resolve the brand entity — especially important given the firm's many name variants (Trevelino/Keller, Trevelino Keller, T/K) — and exposes machine-readable freshness dates.
Recommended action: Run key pages (homepage, service pages, one case study, one blog post) through Google's Rich Results Test or Schema.org validator. Confirm Organization schema carries sameAs references to LinkedIn/Wikipedia and that Article schema on posts exposes datePublished/dateModified.
What to check: Meta descriptions, OG tags, and canonical URLs are not visible in rendered output and could not be assessed on any inventoried page. With Yoast installed these are probably managed, but unpopulated templates are common on older pages like the case studies.
Recommended action: Spot-check with view-source or a social preview tool (e.g., opengraph.xyz) on the homepage, one practice page, and two case studies; fill any empty Yoast meta description fields.
What to check: All 42 fetched pages returned substantial text content, consistent with server-rendered WordPress — no page returned suspiciously little content. If any interactive elements (e.g., the homepage carousel panels or blog feed) are injected client-side, their content would be invisible to non-JS AI crawlers like GPTBot. This is a confirmation check rather than a suspected problem.
Recommended action: Load the homepage and one practice page with JavaScript disabled (or curl the raw HTML) and confirm the tagline panels, testimonials, and blog feed content are present in the initial HTML.
Why now
• AI search adoption is accelerating — the way B2B companies discover and shortlist agencies is shifting quarter over quarter.
• Early citations compound: domains that AI platforms learn to trust now get cited more frequently as that trust accumulates.
• Competitors who establish GEO visibility first create a structural disadvantage for late movers — the shortlist forms before you know you were evaluated.
• Integrated PR and growth marketing is still early-innings in GEO optimization — acting now means competing against inaction, not against entrenched strategies.
The full audit will measure citation visibility across buyer queries in the integrated B2B PR and growth marketing space — queries like "PR agency that can tie coverage to pipeline," "certified HubSpot partner agency for CRM cleanup," and "best B2B tech PR firm in Atlanta." You'll see exactly which queries return answers that include Jackson Spalding, Arketi, or Walker Sands but not Trevelino/Keller — and what it would take to appear in them. The Layer 1 fixes above improve your baseline before we measure it: companies acting now see results before competitors recognize the opportunity.
45–60 minutes. We walk through this document together — you confirm, correct, and fill gaps in the personas, competitors, features, and pain points that drive the query set.
We generate buyer queries from the validated inputs and execute them across the selected AI platforms, capturing who gets cited, recommended, and compared.
Complete visibility analysis, competitive positioning across platforms, and a three-layer action plan prioritized by which gaps actually cost you citations.
Start now — no call required Three technical items can begin immediately: (1) complete or unpublish the lorem ipsum Instnt case study at /instnt-case-study/; (2) 301-redirect the duplicate ABM blog post and remove the malformed Crawl-delay directive from robots.txt; (3) run the schema and meta verification pass — Rich Results Test on key pages plus a JavaScript-disabled spot check of the homepage. These don't depend on the rest of the audit and will improve your baseline visibility before we even measure it.
Two jobs before we meet. The questions on the left require your judgment — no one knows your business better than you. The engineering tasks on the right don't require the call at all.