SEO.co

SEO.co
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Enterprise SEO for people who own the number, not the theory. Technical debt, content architecture, internal linking, crawl budget, and what genuinely changes when answer engines and AI summaries sit between your pages and your buyer. Each episode picks one narrow problem — a migration that tanked traffic, a template quietly competing with itself, a content library nobody can navigate — and works it all the way through, including the parts that are inconvenient to admit. It's aimed at in-house SEO leads and agency practitioners working on sites big enough that a change has consequences. Five or six minutes, one problem, no keyword-density folklore. Topics include site migrations that lose traffic, template and cannibalisation problems, internal linking at scale, crawl budget and index bloat, entity and schema work, content pruning, answer-engine visibility, and diagnosing a ranking drop without guessing. Produced by SEO.co, AI-assisted enterprise SEO. Full details, services and further reading at https://seo.co

  1. 1d ago

    Where AEO and SEO Overlap and How to Rank in Both

    Most marketing teams treat Answer Engine Optimization and Search Engine Optimization as separate budget lines with separate playbooks. The data tells a different story. This episode of the SEO.co podcast unpacks the surprisingly large overlap between classical search rankings and AI citation behavior — and shows why collapsing the two into one coherent program is not just more efficient, but more effective. The discussion draws on the full breakdown of where AEO and SEO overlap and how to rank in both to lay out a clear, sequenced strategy. Here's what the episode covers: AI Overviews pull from existing rankings. Ahrefs data shows ~76% of pages cited in Google's AI Overviews already rank in the organic top ten — meaning classical SEO remains the delivery mechanism even for Google's newest AI surfaces. Featured snippets still matter, just differently. 99.6% of featured snippet holders already rank in the top ten, and 68% of AI Overviews cite the featured snippet source — the position-zero playbook is still paying dividends. Off-Google engines behave very differently. ChatGPT shows ~32% domain overlap with Google's top ten but only ~10% URL overlap, meaning brand presence transfers far more reliably than individual page selection — a critical distinction for AEO planning. Perplexity, by contrast, most closely mirrors traditional rankings. Four signals earn double duty across both channels: crawlability and render fidelity, consistent entity resolution across platforms, topically relevant link authority, and deep content clusters — all of which influence both traditional SEO and AI-era visibility. Schema markup is not the AEO lever many assume. Google's own guidance confirms structured data is not required for AI Overviews; schema markup remains valuable for rich results and entity disambiguation, but it doesn't drive LLM citation selection. Sequencing the unified program matters. The episode walks through the right order of operations: technical audit first (redirects, orphan pages, canonicals), then entity and schema consistency, then consolidating cannibalized content, then rewriting page openings to lead with direct answers, then earning off-site mentions from authoritative reference domains. The core argument is that running parallel SEO and AEO workstreams is the most common and most costly mistake in search strategy today. Teams that treat AEO as a layer added on top of a healthy SEO foundation — rather than a competing discipline — consistently outperform those that don't. If your team is still debating which channel deserves the budget, this episode reframes the question entirely. For more on how AI is reshaping the search landscape, check out the related episode The Fight for BOFU Keyword Rankings Just Got Harder. SEO.co

  2. 4d ago

    The Fight for BOFU Keyword Rankings Just Got Harder

    Bottom-of-funnel search has always been valuable, but the competitive dynamics shifted dramatically in 2025–2026. AI-powered tools like ChatGPT, Perplexity, and Google's AI Overviews have absorbed informational queries at scale, stripping the top of the traditional funnel and funneling every serious buyer — and every competing brand — into the same narrow band of commercial and transactional SERPs. This episode of SEO.co digs into why that transformation happened so quickly, and what a modern BOFU strategy actually looks like. For a deeper read alongside the episode, the full breakdown of why BOFU keyword rankings just got harder is available on the SEO.co blog. Here's what the episode covers: The economics behind the shift: Comparison and alternative keywords were already converting at over 8% while informational content barely registered — AI search simply collapsed the supply side that propped up the old funnel model. SERP feature capture as the new baseline: Ranking in position one on a commercial query is no longer enough. Product packs, FAQ modules, review carousels, and AI Overviews stack above traditional blue links — and each feature has distinct structural requirements. Solid schema markup is now table stakes for appearing in both Google features and AI-generated citations. Why comparison and alternative pages are the content type of the moment: "Best alternatives to," "X vs. Y," and use-case-specific queries are where buyers resolve shortlists — exactly the phase that AI chatbots don't intercept. Credible pages name competitors honestly, show real pricing, and include a decision rubric rather than a feature-grid sales pitch. Third-party review platforms as a ranking and AI-citation channel: G2, Capterra, and Trustpilot are now tightly coupled to LLM shortlist generation. Brands invisible on these directories are far less likely to appear in AI-generated vendor recommendations, regardless of how well their own site performs. A strong competitor analysis should map which review platforms dominate in your category. Measurement has to change: Optimizing for total organic sessions will pull teams back toward informational content by default. BOFU strategy demands metrics tied to fewer, higher-intent visits — not aggregate traffic volume. AI SEO and on-page SEO are now the same discipline: The structured markup that earns a Google feature also increases the likelihood that an LLM cites the same passage. Teams treating these as separate workstreams are duplicating effort and leaving coverage gaps. If the way your team currently reports on SEO performance still celebrates total organic sessions, this episode is a useful prompt to recalibrate around what actually drives pipeline in the current search landscape. For more on how AI is reshaping organic strategy, the episode AI Cut Your Organic Traffic — and That's Actually Good News is a strong companion listen. SEO.co

  3. 6d ago

    AI Cut Your Organic Traffic — and That's Actually Good News

    Organic traffic is down. Way down, for a lot of teams. But when you cross-reference those session counts with pipeline data, demo requests, and revenue per visit, a different story emerges — one that the SEO.co team explores in depth in the companion article on why AI-reduced organic traffic may actually be good news. This episode breaks down what the data really shows, what's quietly leaving the funnel, and why the visitors who remain are far more valuable than the metrics suggest. Here's what the episode covers: The funnel has compressed, not collapsed. AI answer engines have absorbed informational queries — the "what is" and "how does" searches that rarely converted anyway. The clicks that remain skew heavily toward buyers who already understand the category. The click-through rate data is striking. Research across nearly 70,000 searches found that AI Overviews cut standard result clicks roughly in half. But branded keywords in the same datasets saw click-through rates rise by nearly 19% — because those queries happen after a buyer has already done their research. AI-referred visitors behave differently. Session durations from AI referrers average nearly twice those of standard organic visitors, and conversion rates from AI sources on B2B SaaS sites run as high as five times the Google organic baseline — a ratio that reframes what "good traffic" looks like. Three metrics replace "visits" as the executive dashboard. Qualified session rate (bottom-of-funnel URLs as a share of total organic), assisted conversions weighted to AI first-touch, and AI-referral revenue per visit — each maps cleanly to figures finance already tracks. Content strategy has to shift downward. With top-of-funnel noise filtered out by AI, a content strategy built around pricing pages, comparison content, and demo pathways now carries the load that glossary posts and explainers used to share. Bottom-of-funnel pages need to work harder. Attribution models built for a pre-AI world actively mislead. Last-click attribution misses the research journey happening in ChatGPT, Perplexity, and Claude before a buyer ever types a URL. A 90-day window with AI referral as a first-touch signal is the minimum viable fix. The episode draws on data from Pew Research Center, SparkToro, Similarweb, and Amsive, alongside SEO.co's own client benchmarks tracked through 2026. For teams navigating the broader implications of AI and SEO, the numbers here offer a concrete starting point for making the case internally that traffic volume and pipeline health are no longer the same conversation. For more on capturing visibility in AI-generated answers, check out the episode How to Get Your Company Recommended by ChatGPT. SEO.co

  4. Oct 6

    How to Get Your Company Recommended by ChatGPT

    When a prospect asks ChatGPT to recommend the best vendor in your category, the answer it gives isn't an accident — it's the output of a multi-step retrieval pipeline that marketers can actually influence. This episode of the SEO.co podcast walks through the data-driven playbook behind getting your company recommended by ChatGPT, translating the underlying mechanics into concrete, measurable actions teams can take right now. Here's what the episode covers: How ChatGPT's retrieval pipeline works — query classification, sub-query expansion, retrieval, reranking, and citation selection, and why the retrieval layer (not the model itself) is the real optimization target. Bing indexing as a prerequisite — independent citation research shows the vast majority of ChatGPT citations mirror Bing's top results, meaning any page absent from Bing's index has near-zero probability of appearing in a ChatGPT answer. Auditing the gap between your Bing and Google coverage is a direct read on lost visibility. OpenAI crawler permissions — OAI-SearchBot, ChatGPT-User, and GPTBot each serve distinct functions; deliberately configuring robots.txt and monitoring server logs tells you whether your site is even eligible to surface. Third-party mention density and co-citation footprint — Reddit alone accounts for roughly 40% of ChatGPT citations. Tracking brand mentions alongside category keywords across Reddit, Stack Exchange, YouTube, and trade press isn't a vanity metric — it's a measurable signal the reranker actively uses. This is closely tied to a broader generative engine optimization strategy that treats AI visibility as its own channel. Entity resolution and structured data — ChatGPT recommends entities, not URLs. Publishing consistent Organization, Product, and Service schema with same-as links to Wikidata, LinkedIn, Crunchbase, and G2, plus a single canonical positioning statement mirrored across key pages, gives the model the corroboration it needs to cite your brand with confidence. Schema markup is the unglamorous infrastructure that makes entity resolution possible. Passage-level content structure and proxy measurement — ChatGPT retrieves at the passage level, not the page level. Leading each section with a direct 40–60 word answer, pairing it with sourced statistics, and writing comparison pages using exact "alternatives to" and "versus" phrasing maps content directly to the queries ChatGPT receives. With no native Search Console equivalent, teams can build a proxy by running a fixed set of buyer-intent prompts weekly and segmenting ChatGPT referral traffic in analytics — a channel that, in B2B contexts, already closes at 56% higher rates than Google or Bing leads. For a deeper read on the strategies discussed, explore the full source article linked above. Also worth your time: the episode What Your AEO Agency Isn't Telling You About AI Search covers the agency-side blind spots that compound many of the same visibility gaps addressed here. SEO.co

  5. Oct 3

    What Your AEO Agency Isn't Telling You About AI Search

    AI search is dominating agency pitch decks right now, but the gap between what gets sold and what actually delivers results is wider than most brands realize. This episode of SEO.co draws on the hidden truths about AEO agency AI search pitches to walk through exactly what's being glossed over — and what to demand before signing anything. The episode covers the most consequential blind spots in today's AEO sales cycle, including the real traffic numbers, a broken attribution picture, and the tactical myths that agencies aren't volunteering. Key points include: The traffic reality check: Cloudflare Radar data from May 2026 shows all AI search engines combined — ChatGPT, Gemini, Perplexity, Claude — account for just 0.29% of search referral traffic, versus Google's nearly 88%. Growth trajectory is real, but current volume is tiny, and any AEO engagement should be priced as long-horizon brand positioning, not near-term pipeline. The attribution black hole: Up to 70% of AI-influenced visits arrive with no referrer header, landing in GA4's Direct bucket alongside branded type-ins. Last-click attribution captures only around 2% of AI search's true revenue contribution — meaning most agencies are reporting on citations, not conversions. Three questions to ask any AEO vendor: What exact regex do they deploy to catch AI referrers? How do they reconcile branded search lift against AI visibility reports? And what self-reported attribution instrument lives on every conversion path? Agencies that can't answer all three are selling a monitoring dashboard, not a measurement system. What "being cited" actually means: AI citation is non-deterministic — the same prompt can return different sources for different users. Research shows 62% of AI citations don't include a brand mention, and only 15% of AI search categories have a consistent brand winner. A footnote citation and a named brand impression in the prose are not the same thing for memory or pipeline. Schema markup is not the shortcut it was sold as: A controlled Ahrefs study of nearly 1,900 pages found no meaningful uplift in AI citations after adding schema markup. AI visibility is built on genuine topical authority and structured, comparative content — accumulated over years, not sprint cycles. What a defensible AEO engagement looks like: A defined prompt set of 100–300 queries sampled weekly across at least four platforms, with citation rate and brand mention rate tracked separately, paired with a dual attribution stack combining a custom GA4 channel group and a self-reported instrument on every conversion path. For brands also thinking about how content architecture supports topical authority, the episode's discussion of structured content connects directly to the broader discipline of generative engine optimization — an area worth understanding alongside any AEO investment. If you missed the previous episode on resolving overlapping content, Fix Content Cannibalization by Consolidating Pages Safely is a practical companion on keeping your content footprint clean before scaling AI-facing optimization efforts. SEO.co

  6. Oct 1

    Fix Content Cannibalization by Consolidating Pages Safely

    Content cannibalization rarely looks catastrophic at first glance — but left unaddressed, it quietly splits backlink equity, destabilizes rankings, and gives AI answer engines like ChatGPT and Perplexity an easy reason to cite a competitor instead. This episode unpacks the technical consolidation protocol detailed in SEO.co's guide to fixing content cannibalization by consolidating pages safely, walking through every decision point from diagnosis to post-merge validation. Here's what the episode covers: How to spot a real conflict: Using Google Search Console's Performance report to identify two or more URLs trading positions on the same query — and why a page-three vs. page-four split with balanced impressions is a textbook cannibalization case, while a page-three vs. page-eleven split usually isn't. The three-signal confirmation test: Shared impressions across multiple URLs, position instability (the ranking URL flipping week over week), and true intent overlap — all three must be present before consolidation is warranted. When even one is missing, targeted rewriting of titles and H1s may be enough to separate the pages in Google's eyes. Picking the right winner: Why traffic is a lagging signal and how relying on it alone can lead teams to redirect a stronger page into a weaker one — causing rankings to drop rather than consolidate. Intent fit and backlink profile matter more. Choosing the right mechanism: The differences between a 301 permanent redirect, a rel=canonical tag, and a noindex directive — why they aren't interchangeable, when each applies, and why noindex passes no link equity and should be reserved for thin, unlinked pages only. The internal link rewrite that most teams skip: Why a 301 without updating every internal link pointing at the retired URL is an incomplete migration — and how thoroughly rewiring those links toward the surviving page (including nav elements, footers, and older editorial posts) directly amplifies the consolidation's impact on rankings. Why this is now a generative engine optimization problem: AI platforms tend to cite one URL per domain per topic. Sites with multiple overlapping pages on the same question are effectively forfeiting citations to competitors who maintain a single, authoritative answer — making consolidation critical far beyond traditional keyword cannibalization concerns. The episode closes with a four-to-eight-week validation framework: tracking whether the retired URL disappears from Search Console, monitoring the survivor's position stability and impression consolidation, and re-running AI prompts to confirm that attribution has shifted to the merged page. For more from the show, check out the episode Local SEO for Lawyers: How to Dominate Google Maps & the Map Pack. SEO.co

  7. Sep 29

    Local SEO for Lawyers: How to Dominate Google Maps & the Map Pack

    For lawyers, showing up on the first page of Google isn't enough — the real prize is the Map Pack, those three local listings pinned to a map that capture the lion's share of clicks from people searching for legal help right now. This episode of the SEO.co podcast walks through a practical, prioritized framework drawn from the local SEO guide for law firms — covering exactly how attorneys can climb into that top-three local ranking and stay there. Here's what the episode covers: Google Business Profile optimization: Why it's the single highest-leverage action a law firm can take — and the specific details that separate high-performing profiles from ignored ones, including category selection, business descriptions, and photos. NAP consistency and citations: How to build a citation footprint across legal directories (Avvo, Justia, FindLaw, Martindale-Hubbell) and general platforms, and why even minor formatting differences in your name, address, or phone number can quietly undermine Google's trust in your listing. Review strategy: How Google weighs quantity, quality, diversity, and recency — and how to build a simple, compliant system for generating a steady stream of honest client reviews without running afoul of bar association rules. Responding to reviews: Why replying to every review — positive and negative — functions as a public signal of professionalism that prospective clients evaluate before they ever call. Website content and location pages: The difference between genuine, community-specific location pages and duplicated content with swapped city names, and why on-page SEO fundamentals like title tags and footer NAP data matter for local relevance. Local backlinks: How sponsorships, charitable involvement, and expert media contributions earn geographically relevant links that reinforce a firm's local authority in ways generic link building cannot. The episode closes with a reminder that local SEO is not a one-time setup task — it's a compounding investment. Firms that treat it as ongoing infrastructure consistently outperform those that treat it as a box to check. For more from the show, check out SEO MCP Servers and Claude Code: Your Practical Getting-Started Guide, which explores how emerging AI tooling is reshaping the SEO workflow. SEO.co

  8. Sep 26

    SEO MCP Servers and Claude Code: Your Practical Getting-Started Guide

    AI-assisted SEO has taken a meaningful leap forward with the Model Context Protocol, and the gap between teams using it and those waiting on the sidelines is widening fast. This episode of the SEO.co podcast walks through this practical getting-started guide to SEO MCP servers and Claude Code, translating what can feel like developer infrastructure into a clear, actionable framework for marketers and in-house SEO teams. Here's what the episode covers: What MCP actually is (and why it matters now): The Model Context Protocol, launched in late 2024, solves the long-standing "M×N integration problem" by giving every AI client and data source a shared language — meaning your AI assistant can query live keyword volumes, backlink data, and Search Console metrics in a single session instead of stitching together CSV exports. Why Claude Code is the right environment for SEO work: Unlike a standard chat interface, Claude Code is a terminal-native agent that can read from the filesystem, maintain session state, run local scripts, and call multiple MCP servers simultaneously — making it a far more capable research and technical SEO partner than a conversational AI window. The four servers worth your time: DataForSEO's open-source TypeScript server (broadest API coverage, pay-as-you-go), Ahrefs' remote MCP server (ideal if Ahrefs is already your source of truth), the community-maintained mcp-gsc for Google Search Console (free, high-value for anomaly detection and traffic analysis), and Screaming Frog v24 (the first major desktop crawler with first-party MCP integration, released May 2026). How to evaluate any server before you install it: Prefer vendor-published servers over anonymous forks, scrutinize the authentication model, and watch pay-per-call cost models carefully — the MCP registry now lists over 9,400 servers, and more tools isn't the same as better results. The most important practical rule: Start with one server, not four. Connecting too many tools at once degrades agent performance and creates confusion about which tool to call — a lesson reinforced by the fact that Cursor caps active MCP tools at forty for exactly this reason. Security and cost guardrails to set from day one: Use environment variables or OAuth rather than committing API keys to version control, and set rate limits at the server level rather than relying on prompt instructions alone. Whether your team is building out an agentic SEO workflow from scratch or looking to add live data to an existing AI research process, this episode gives you a framework grounded in what's actually shipping today — not what's theoretically possible in eighteen months. For more on the evolving relationship between AI assistants and search visibility, don't miss the related episode llms.txt in 2026: The Adoption Gap Nobody Is Talking About. SEO.co

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About

Enterprise SEO for people who own the number, not the theory. Technical debt, content architecture, internal linking, crawl budget, and what genuinely changes when answer engines and AI summaries sit between your pages and your buyer. Each episode picks one narrow problem — a migration that tanked traffic, a template quietly competing with itself, a content library nobody can navigate — and works it all the way through, including the parts that are inconvenient to admit. It's aimed at in-house SEO leads and agency practitioners working on sites big enough that a change has consequences. Five or six minutes, one problem, no keyword-density folklore. Topics include site migrations that lose traffic, template and cannibalisation problems, internal linking at scale, crawl budget and index bloat, entity and schema work, content pruning, answer-engine visibility, and diagnosing a ranking drop without guessing. Produced by SEO.co, AI-assisted enterprise SEO. Full details, services and further reading at https://seo.co

Information

  • Creator
    SEO.co
  • Years Active
    2026
  • Episodes
    16
  • Rating
    Clean
  • Copyright
    © 2026 SEO.co
  • Show Website
    SEO.co