A checklist for effective SEO QA

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Engineering teams usually have a quality assurance (QA) process.

Without it, they risk releasing work that hurts the user experience and creates unforeseen technical issues – including major SEO problems.

That’s where SEO QA comes in. Adding SEO-specific checks to existing QA protocols helps teams catch and fix issues before they go live.

But this step is less common than you’d think. Too often, it’s overlooked.

This article outlines what it takes to build an effective SEO QA discipline and provides a checklist SEOs and QA engineers can use to cover their bases.

Why SEO QA gets overlooked

Unless SEO is fully integrated with engineering, SEO-specific QA often gets overlooked.

As a result, SEOs may not flag problems until a tech audit – or worse, when they show up as organic KPI declines. 

This is especially common when SEO teams sit under marketing instead of product or engineering, since they’re excluded from regular milestones and lifecycle meetings. 

That makes it harder to communicate SEO’s importance, win buy-in, and establish it as part of everyday development.

Having a QA team within engineering is also no longer a given.

In agile environments, some teams prioritize speed over fully clean rollouts.

Others rely on AI tools to automate QA or monitor for technical issues, instead of employing dedicated QA engineers.

In short, there are plenty of reasons many teams lack a well-developed SEO QA practice.

What are the benefits of SEO QA?

For SEOs to be able to proactively find and resolve issues before they go out into the world, they need two things on a regular basis:

  • Opportunities to view upcoming engineering tickets and flag any that may have potential SEO impact. (A great reason for an SEO representative to be a part of sprint planning meetings.)
  • A chance to QA any of the flagged tickets before they hit production.

This has a few key benefits for the business:

  • Minimize the chances of deploying code that hurts SEO.
  • Catch and correct errors that hit production before they register with search engines.
  • Capitalize on SEO opportunities related to engineering work that’s already slotted for development.

The last bullet is just as much of a reason to implement SEO QA as the first two. 

It’s not just about catching bugs, it’s about maximizing value while minimizing resources. 

When SEOs have a chance to see what’s coming up, it allows them to connect the dots between SEO roadmap items and upcoming engineering initiatives to find potential areas of overlap. 

In turn, the business reaps the SEO benefits of work that’s already in motion, rather than spending additional resources to achieve the same goal later. 

Best practices: The 4 Ws of SEO QA

Alright, now that we’ve established why brands need SEO QA, let’s get into the logistics.

Who should perform SEO QA?

Ensure QA is performed by:

  • A technical SEO.
  • Or an engineer equipped with clear criteria shared by an SEO.

What should they check?

Define a checklist of core, critical SEO items that should be a part of QA for any ticket flagged as having potential SEO impact.

  • Refine this checklist on an ongoing basis, tailoring it to the nuances of your web stack, so no one makes the same mistake twice.
  • Automate “always-on” checklist items as much as possible to ease the resource burden over time. 
  • Supplement your checklist with any additional, project-specific SEO considerations outlined in product requirements documentation. 
  • Always check tracking, so no data is lost if GA4 or GTM issues arise.

When should SEO QA happen?

The cadence for SEO QA should mimic the site’s development release cycle and existing engineering QA processes. 

For instance:

  • If your site deploys code on two-week sprints, SEO QA should follow the same cadence.
  • After each release, run a crawl with JavaScript enabled.
  • Sites on platforms like Shopify or WordPress may release – and QA – less often.

Where should QA happen?

Test in staging before anything goes to production. 

Some elements might need to be tested in production if they affect indexing or crawlability of content. 

  • Example: The staging site might have the robots.txt set to disallow all URLs, since you don’t want staging to get indexed.

Implement monitoring tools as a safeguard that helps catch any errors that somehow make it to production.

  • Google Search Console: Make sure your account is set up, notifications are coming through, and check for issues weekly. 
  • Third-party crawlers: Set up a weekly crawl in any SEO tool, such as Semrush, Ahrefs, or Sitebulb.
  • Dedicated SEO monitoring toolsets: If you have the budget, certain third-party tools provide real-time auditing and monitoring. 

Building an SEO QA checklist

When SEO requests development work, they write the acceptance criteria in the product requirements and review the work before release.

But not all tickets that affect SEO go through that process, which makes an SEO QA checklist essential.

The checklist can be used by any SEO or QA engineer on any release flagged for SEO impact.

It’s a comprehensive list of core items, organized by category, to ensure issues don’t reach production.

Issue categories for SEO QA

Crawling

For pages to get indexed, search engines need to access URLs, crawl the content, and use it as context. 

That’s pretty fundamental to SEO, and a big reason we start here.

Note: Crawl issues often impact large swaths of the site because changes can occur across an entire page template or subfolder.

Crawling and indexing
  • Robots.txt: New or removed disallows that might impact URLs you do or don’t want crawled.
    • Are crawlers blocked from the site?
    • Are there any subfolders or parameters blocked that shouldn’t be? 
    • Are images or resources like JavaScript blocked?
  • Meta robots tags: Unintended changes from index to noindex, standard to nofollow, or vice versa.
  • Canonical tags: Were canonical URLs added, removed, or changed in ways that will cause issues?
    • For example:
      • Did Page 2+ of paginated listing pages canonicalize back to Page 1? 
      • Are filtered URLs properly canonicalized based on whether you want them indexed?
  • HTTP status codes: 3{xx} (redirect), 4{xx} (not available), or 5{xx} (server) errors resulting from changes
  • URL path: Changes to existing URLs that were not previously discussed with the SEO team.
  • Redirects: Are new redirects working properly, or did something break existing redirects?
  • Internal links: Are they coded using an <a href> tag, so crawlers can identify them?

Content changes

Are all of the following still available and correct?

Content changes
  • Navigation and footer.
  • Breadcrumbs.
  • SEO titles.
  • Meta descriptions.
  • Headings and other on-page copy.
  • Internal and external links.
  • Images, videos, and other media.
  • Related and recommended items widget.
  • User-generated content (especially reviews).
  • E-E-A-T signals, including author bylines and bios.
  • Hreflang and internationalization features.
  • Structured data: Is it crawlable, parsable, accurate, and reflecting visible information on the page? (Note: Google’s Schema Markup Testing Tool won’t work on staging URLs since crawlers are (hopefully!) blocked.)

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JavaScript and CSS

You can see CSS issues because they visually impact the page. 

For JavaScript issues, you’ll need tools to understand whether crawlers can access critical content. 

Unless you’re already running a sitewide crawl with JavaScript enabled, test one or two pages from the affected template (i.e., blog, listing, product detail) using a tool like Rendering Difference Engine.

JavaScript and CSS
  • Page elements applicable to the template are available and functioning as intended, including pop-outs, filtering, sort function, and pagination.
  • Any page content that loads after a user interaction is available in HTML that search engines can crawl.
  • If the site serves source HTML, are key elements of the page different in the rendered HTML, such as:
    • Meta robots.
    • Canonicals.
    • Titles.
    • Meta descriptions.
    • Page copy.
    • Internal links.
    • External links.

Mobile

Google crawls mobile-first. So if you’re only checking on desktop, you’re skipping SEO QA.

Mobile
  • Does it look and function as it should? 
  • Are there any accessibility issues on a smaller screen? 
  • Is there consistency between the desktop and mobile versions of the site?

Tracking

If it’s not part of QA, broken tracking is a recipe for panic. 

The team will not find the issue until they see KPIs like organic traffic decline. 

Even worse, until it’s fixed, that’s historical data that you won’t get back. 

Tracking

Before launch on staging, check if:

  • All pages and templates have tracking code available.

The day after launch, verify that:

  • Internal analytics platform doesn’t show significant declines in KPIs or discrepancies with external reporting tools (e.g., GSC).

Optional: A/B testing

Not all A/B testing tools distinguish the control and variant for crawlers. 

They’re usually served one or the other version of the page randomly, which means your variant could impact SEO.

A/B testing
  • Aside from the variable, the pages should be identical to a crawler.

Refine over time

With every round of QA, engineers and SEOs will learn nuances and find new connections. 

You’ll discover that certain types of updates are more likely to cause certain types of SEO issues, certain plugins are linked to certain types of problems, etc.

Your SEO QA checklist is a living, breathing document and a place to document all of this to make SEO QA more effective – and avoid repeating mistakes – no matter who’s carrying it out. 

Start with the list below and make it your own over time.

SEO QA checklist

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Pinterest tests Top of Search ads to capture high-intent shoppers

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Pinterest is rolling out Top of Search ads, a new ad format that places brands directly in the first 10 slots of search results and Related Pins, where nearly half of user clicks occur.

Shopping on Pinterest is inherently visual, and most searches on the platform (96%) are unbranded according to Pinterest. That makes the top of search results a prime spot for discovery – and for brands to reach consumers who are open to new products.

Why we care. Pinterest’s Top of Search ads put your products in front of shoppers at the most valuable moment: when they’re actively browsing but not yet brand-committed. With nearly all searches unbranded, the format offers a powerful way to win new customers and outperform competitors. Early testing shows significant performance lifts, making it a high-return opportunity for brands looking to drive both visibility and conversions.

How it works. Top of Search ads ensure a brand’s products are featured where shopping journeys often begin. The new format also includes a brand-exclusive ad unit that highlights an advertiser’s catalog, giving products prominent placement over competitors.

Early results. According to Pinterest:

  • Top of Search ads have driven a 29% higher average CTR compared to standard campaigns.
  • Top of Search ads are 32% more likely to attract new clickers.
  • Wayfair, an early tester, reported a 237% CTR lift in just two weeks compared to its typical campaigns.

Between the lines. For advertisers, Top of Search ads offer a way to intercept undecided shoppers earlier in their journey, effectively turning Pinterest’s visual-first search into a new performance channel.

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OpenAI turns ChatGPT into a shopping tool with Instant Checkout

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OpenAI is launching Instant Checkout inside ChatGPT to Plus, Pro, and Free users in the U.S.

  • Users will be able to buy products from Etsy sellers.
  • Purchases are powered by the new Agentic Commerce Protocol (ACP), co-developed with Stripe.

How it works. Users search in plain language (e.g., “gifts for a ceramics lover”). Then:

  • ChatGPT returns product recommendations ranked by relevance, not payment.
  • If an item supports Instant Checkout, users tap “Buy,” confirm shipping and payment details, and complete the order without leaving chat.
  • Orders, payments, and fulfillment run through the merchant’s existing systems; ChatGPT passes information securely.
  • Merchants pay a small transaction fee; shoppers pay no extra cost.

Between the lines. OpenAI said products are ranked only by relevance – not sponsorship or whether Instant Checkout is enabled. Merchants remain the merchant of record, keeping control over fulfillment and customer relationships.

What’s next. Coming soon, according to OpenAI:

  • Multi-item carts.
  • Expansion to Shopify’s million-plus merchants (e.g., like Glossier, SKIMS, and Spanx)
  • More regions beyond the U.S.

Why we care. If AI chat becomes a mainstream way for people to discover products, OpenAI is now at the start of that purchase journey. For brands or businesses selling products, this could mean a new channel to optimize for – one that bypasses traditional search and funnels discovery straight into checkout.

How to sign up. Merchants can apply to have their products included in ChatGPT search results and enable Instant Checkout via ACP.

  • Etsy and Shopify sellers are already eligible and don’t need to apply.
  • OpenAI is onboarding merchants on a rolling basis through an online application form.

Dig deeper. How ChatGPT search ranks products and merchants

Different from Google. OpenAI is taking a different approach than Google’s agentic search capabilities. Whereas OpenAI is going all the way to completing purchases on behalf of users, Google (for now at least) is letting users take the final conversion action.

OpenAI’s announcement. Buy it in ChatGPT: Instant Checkout and the Agentic Commerce Protocol

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TikTok launches Travel Ads to capture trip planning moments

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TikTok (Credit: Shutterstock)

TikTok is introducing a new ad solution, Travel Ads powered by Smart+, designed to help brands connect with travelers during the discovery and booking phases.

Why now. Travel is one of TikTok’s fastest-growing verticals. According to internal TikTok data:

  • 66% of users say the app is their most helpful source of travel inspiration.
  • Users are 2.6x more likely to book after searching on TikTok.

How it works. Travel Ads leverage TikTok’s travel intent model and catalog integration to automatically serve personalized creatives at scale. Smart+ AI powers campaign setup, creative generation, and delivery optimization, aiming to convert discovery into bookings seamlessly.

Why we care. TikTok Travel Ads put hotels, flights, and destinations in front of a massive audience already using the app for trip planning, with two-thirds calling it their top source of travel inspiration. Smart+ AI tools then streamline setup and optimization, helping brands scale personalized ads that influence bookings at the earliest, most impactful stage.

The details:

  • Ads can showcase hotels, flights, and destinations using dynamic, visually rich formats.
  • Advertisers can choose among:
    • Single video ads: A hero video paired with personalized travel cards (hotel name, flight route, price).
    • Catalog video ads: Auto-built from product catalogs with tailored calls to action.
    • Catalog carousel ads: Scrollable, interactive ads pulling directly from catalog images.

What they’re saying. David Hoctor, TikTok’s head of US verticals for travel and gaming, said:

  • “Travel on TikTok goes beyond the For You feed, unlocking real-life travel experiences. Every swipe can be a step toward conversion.”

Between the lines. By integrating catalog feeds with intent signals, TikTok is pitching Travel Ads as a direct competitor to Google and Meta in the lucrative travel advertising market, where inspiration and conversion increasingly overlap.

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‘Mistakes make you stronger’: PPC lessons from Inderpaul Rai

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In episode 325 of PPC Live The Podcast, I sat down with Inderpaul “Indi” Rai, group account director at WeDiscover, to explore the lessons learned from mistakes, team dynamics, and the evolving role of automation and AI in paid search.

Indi, a veteran with over a decade of experience in AdTech, MarTech, SEO, analytics, and multilingual paid search, shared candid insights on how errors can shape careers and client relationships.

Embracing mistakes to grow

Indi opened up about one of the most significant mistakes in his career: an automated budget feature in Search Ads 360 went unchecked during his holiday, resulting in the U.S. account overspending by a substantial amount.

Despite the magnitude of the error, the client’s response was surprisingly supportive – they recognized it as an honest mistake and collaborated to mitigate the impact.

Key takeaway. Mistakes are inevitable, but transparency, a calm response, and collaborative problem-solving can turn potential disasters into learning opportunities. Indi emphasizes that experiencing and managing errors is essential for personal and professional growth.

The importance of team communication and handover

Indi reflected on how the overspend could have been avoided with better team preparation:

  • Ensuring critical information isn’t solely in the manager’s head.
  • Documenting handovers thoroughly and leaving room for junior team members to step in effectively.
  • Establishing multiple layers of oversight to prevent single points of failure.

He stressed that team members should feel empowered to act and communicate when issues arise, even if the manager is unavailable. In his experience, the junior team caught the overspend themselves and waited for Indi’s return rather than panicking – a testament to clear communication and a supportive team culture.

Lesson for managers: Maintain composure during crises, focus on solutions over blame, and ensure your team knows their role in resolving issues.

Automation and AI: Tools, not crutches

The discussion turned to automation and AI, where Indi shared practical advice:

  • Treat AI as an assistant, not a replacement. Blind reliance on AI can lead to errors, especially if users don’t understand the subject matter.
  • Always validate outputs and run rigorous testing before implementing AI-driven changes. He cited an example from his past work rewriting product descriptions: AI produced repetitive, generic content that wasn’t an improvement over the original, highlighting the need for careful oversight.
  • Automation can enhance efficiency but requires clear rules, regular checks, and accountability to prevent mistakes like unmonitored budget overspend.

Insight. Automation amplifies efficiency but cannot replace thoughtful human oversight and strategic decision-making.

Client relationships matter

A recurring theme in Indi’s story was the importance of cultivating strong client relationships. The supportive response of a previously “difficult” client revealed that mutual respect, trust, and proven value can turn challenging situations into opportunities for stronger partnerships.

Lessons in leadership and mindset

Indi also shared broader reflections applicable beyond PPC:

  • Resilience matters: he likened his career journey to Rocky, emphasizing that success isn’t about avoiding hits but about how you respond and keep moving forward.
  • Learning through experience: setbacks are essential; they teach you to handle pressure, improve processes, and grow professionally.
  • Balanced guidance: leaders should manage crises calmly, focus on facts, and support their teams without panicking.

From mistakes to momentum

The conversation underscores that mistakes are not the end – they are a catalyst for learning, collaboration, and improvement.

From automation missteps to client communication, Indi’s insights provide a roadmap for PPC professionals aiming to thrive in a fast-evolving industry.

Whether refining handovers, managing automation, or responsibly leveraging AI, the core lesson remains the same: anticipate errors, respond calmly, communicate clearly, and use each experience to build stronger teams and smarter processes.

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Google pushes Demand Gen deeper into performance marketing

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How to tell if Google Ads automation helps or hurts your campaigns

Google Ads’ Demand Gen campaigns – once thought of as mid-funnel discovery tools – are evolving into full-funnel, conversion-focused campaigns, with YouTube at the core.

Why we care. Marketers are under pressure to prove ROI across channels. Demand Gen now blends social-style ad formats with Google’s AI-driven targeting, giving advertisers new ways to drive sales, leads, and app installs from audiences they can’t reach elsewhere.

What’s new:

  • Target CPC bidding: Advertisers can now align Demand Gen with social campaigns for apples-to-apples budget comparisons.
  • Channel controls. Run ads only on YouTube, or expand to Display, Discover, Gmail, and even Maps.
  • Creative tools. Features like trimming and flipping help repurpose social assets for Shorts and other placements, lowering barriers to entry.
  • Feeds + app support. Product feeds in Merchant Center show a 33% conversion lift; Web-to-App Connect now extends to iOS for smoother in-app conversions.

By the numbers. According to Google advertisers using Demand Gen have seen on average:

  • 26% YoY increase in conversions per dollar
  • 33% uplift when attaching product feeds

Between the lines. Google says Demand Gen’s shift from contextual matching to predicting user intent and purchase propensity has made it a contender for bottom-funnel performance. In short: YouTube is no longer just discovery – it’s decision-making.

What’s next. Expect more AI-driven creative tools, expanded shoppable formats, and deeper integrations across channels.

The takeaway. Don’t wait for “perfect” YouTube creative. Lift, adapt, and test now — Demand Gen is no longer a mid-funnel experiment, it’s a performance channel.

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Your GEO content audit template

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GEO content audit

My SEO mantra in the age of GEO is from the great Lil Wayne, “Real G’s move in silence like lasagna.”

Translation for SEO marketers: the most effective GEO moves aren’t loud growth hacks. They’re the subtle edits and formatting that make AI cite you without fanfare.

To help with your GEO audit, here’s an inside peek into my secret menu.

Take a look at my GEO content audit template.

It’s an evolution of my SEO content audit.

As Google’s Danny Sullivan has been telling rooms full of marketers, “Good SEO is good GEO.”

That’s why I like to think of GEO as SEO’s MTV Unplugged version. It’s the same band, same lyrics, just stripped down, reimaged, and way more personal.

Alright, enough philosophy. You came here for the secret recipe. Let’s crack open the GEO content audit template and see how it works in practice.

Use this GEO content audit template

Cool. You’ve made a copy of the GEO content audit template. Now what?

Here are the key sheets you’ll work through:

  • Summary: High-level snapshot once you’ve scored everything.
  • Action list: Quick recap of next steps that summarizes all your findings from the other tabs.
  • Content inventory: This is the backbone. Filters include:
    • URL.
    • Action.
    • Strategy.
    • Page title.
    • Last updated date.
    • Author.
    • Word count.
    • Readability.
    • Average words per sentence.
    • Keywords.
    • Canonical.
    • Internal links.
    • And more.
  • Indexability/architecture/ URL design/on-page: Your technical health is still important.
  • Structured data: Markup needed and where.
  • International: Hreflang, language, local cues (currency, units, spelling, trust marks).
  • Speed: Yes, page speed is still important.
  • Content and gaps: Quality scoring and what’s missing.
  • Linking: Internal link plans and external targets.
  • Refresh: Cadence schedules by asset type.

You’ll bounce between content inventory, structured data, content, content gaps, and linking the most.

Tools you’ll want on hand

  • Crawling and gaps: Screaming Frog, Ahrefs, or Semrush for keywords and links.
  • Search Console: Build a regex brand view (brand + misspellings + product names) to watch demand move as AI answers spread.
  • Prompt testing: Manually test core buyer prompts in ChatGPT, Google AI Overviews/AI Mode, Gemini, Copilot, Perplexity. Log inclusions and citations. BrightEdge’s dataset shows that you’ll see a lot of disagreement across platforms. Expect that.
  • Attribution: Roadway AI (or similar) to connect topics/pages to pipeline and revenue for your QBR.

How to do a GEO content audit (with the template)

1. Set goals

Pick outcomes that map to how people actually find you now:

  • Inclusion rate: Percentage of target prompts where your brand is mentioned inside ChatGPT/AI Overviews/AI Mode/Perplexity/Copilot.
  • Homepage and direct lift: Buyers often go to AI → Google → your homepage. This is why you’ll want to watch branded impressions and homepage sessions.
  • Revenue by topic/page: Wire this to your attribution tool.

Why this mix?

Because AI boxes change, and engines disagree.

A blended scoreboard helps you avoid chasing one fragile metric.

Pro move: Add “ChatGPT/AI Search” to “How did you hear about us?” in forms and sales notes and review weekly. Many teams report this is where the hint of AI-assisted discovery shows up first.

2. Build your content inventory

Using Screaming Frog, export every URL with: title/H1, last updated, author, canonical, word count, readability metrics, internal links, and a target query/theme.

Add a few custom fields:

  • Direct-answer present (Y/N): Is there a <120-word summary up top that answers the main question?
  • FAQ present (Y/N): Does it mirror prompt fragments and include FAQ schema?

Why?

If your page is tidy, answer-first, and properly marked up, it’s far easier to reference.

3. Segment by site, market, and language 

Break your inventory into:

  • Domain/subdomain/folder (e.g., .co.uk, /fr/).
  • Market language variations (U.S. vs. U.K. English, Spain vs. Mexico Spanish).
  • Indexability quirks (hidden duplicates, parameters, session IDs).

For international pages, score:

  • Hreflang implementation (pointing to the right alternates; reciprocal).
  • Local cues (currency, units, spelling, trust marks like local badges, VAT specifics).
  • CTAs (country-specific copy, phone numbers, store links).

A shaky international setup is a fast way to look sloppy to users and AI models.

4. Pull the numbers

Look at more than organic:

  • Organic sessions and conversions.
  • Direct sessions and homepage trend 
  • GSC clicks/impressions/queries and brand regex trendline.
  • Manual AI inclusion log (engine, prompt, did we show, who else got named?).

Google says the AI experiences drive “higher-quality clicks,” while many SEO marketers report general traffic decline. 

Read both, and measure your own reality.

5. Judge the substance

Score every high-value page for “citable signal”:

  • Direct answer up top (<120 words).
  • Evidence: Proprietary data, SME quotes, methods, and links out to credible sources.
  • Trade-offs: Where your product is not the best fit.
  • FAQ block that mirrors prompt syntax (e.g., “best X for Y,” “X vs Y,” “pricing,” “implementation time”).
  • Schema: FAQ, HowTo, Product, Organization/Author with published/updated dates.

6. Map gaps and conflicts

Create a hit list:

  • Duplicates and cannibalization: Merge or redirect. If two pages answer the same thing, decide which one lives.
  • Missing BOFU pages:
    • “[Competitor] alternatives.”
    • “X vs Y.”
    • “Pricing.”
    • “Industry-specific use cases.”
  • Offsite holes: Are you absent from “Best of” lists, comparison hubs, review sites, and relevant forum threads? That’s where AI models shop for context. The more you appear on those domains, the likelier you are to get named in answers.

7. Establish next steps

Turn findings into a real plan:

  • Fixes
    • Hreflang clean-up.
    • Canonicals.
    • FAQ/HowTo/Product/Organization/Author schema.
    • Direct-answer summaries added to target pages.
  • Net-new assets
    • “Alternatives,” “X vs Y,” pricing explainer, implementation guide.
    • Video explainers (YouTube) with clear chapters.
    • Region-specific FAQs and CTAs.
  • Earned presence
    • Shortlist the publishers and communities your buyers read.
    • Pitch data-led pieces. Offer SME quotes and screenshots.
    • For review sites (G2/Capterra), set up a gentle ask after X days live.
  • Attribution
    • Connect the page/topic to the pipeline and revenue so that GEO progress is reflected in QBRs (e.g., Roadway or similar).

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Worked example: Filling the template

Let’s see what this looks like in practice. Here’s a sample workflow that uses the GEO content audit template step by step. 

  • Create your goals:
    • Hit 40% inclusion across 50 priority prompts in AI Overviews/ChatGPT
    • +15% homepage sessions QoQ
    • +25% topic revenue for X cluster.
  • Load all URLs. Pick the top 100 URLs to tackle first. Manually update columns with and complete the action with: keep, update, merge, redirect.
  • Plan to add FAQ where you mirror prompt fragments. Think about adding Organization/Author (with bios and dates).
  • Check hreflang and copy cues (currency, units, etc.). Flag any market where your “local” page reads like a machine translation or uses the wrong signals.
  • List missing BOFU pages and industry variants. Prioritize by buyer impact.
  • Add internal links from top-traffic pages to the pages you want cited. Short, descriptive anchors that mirror the question asked.
  • Turn your action list into tickets. Dates. Owners. Status. Nothing lingers.
  • For each of your 50 prompts, record: engine, date, question, inclusion (Y/N), snippet, and other brands named. Check weekly for movement. Why weekly? Because Google keeps tinkering with AI Mode, links, carousels, and new UI, your presence can shift with those tweaks.

Keep these moves in mind to keep your audit on beat

Refresh cadence

Fast vertical (finance, travel, fast-moving SaaS)? Aim for quarterly.

Other verticals can run biannual or annual content refreshes.

Fresh, cited, and updated content tends to fare better for AI Overviews and Perplexity. 

Both are leaning hard on recency and clarity, and Google is actively testing more visible links in those AI blocks.

Local content beats translation

U.K. ≠ U.S.

Spain ≠ Mexico. 

Adjust spelling, units, currency, trust marks, and examples.

Tune the FAQ to local search habits and buyer objections. 

If your Canadian page says “sales tax” instead of GST/HST, people notice – so do models.

Track what matters, not just what’s easy

  • Inclusion rate across engines
  • Brand regex impressions in GSC
  • Homepage/direct lift
  • Revenue by topic/page

Chasing “LLM rankings” is sketchy. Use trackers as signals, not gospel.

What’s really the difference between a GEO content audit and an SEO content audit?

It’s a review of your content and your offsite footprint through an AI lens: Is your stuff scannable, citable, up-to-date, and backed by authority that LLMs trust?

SEO audit focuses on ranking and traffic on your own site. You crawl, fix indexing, resolve cannibalization, etc. It’s the classic playbook.

GEO audit focuses on representation and citability. You still care about structure and technicals, but you also score whether your brand appears in AI answers, even when the cited page isn’t yours.

You check if your content opens with a direct answer, mirrors prompt questions (and has FAQ schema), and is referenced by publishers, YouTube videos, Reddit threads, and review sites.

You need both

Skipping either is like training your upper body only. You’ll look fine in a tank top, but probably should avoid shorts.

Rankings still matter for discovery and for the content AI scrapes.

GEO pushes you to become answer-worthy across the broader web.

Or in Sullivan’s phrasing, good SEO already points you toward good GEO.

Pour one out for your old SEO friends – GEO is part of the scene

GEO is here to stay. Call it bad news delivered with a good whiskey. 

Visibility is shifting to AI answers. If you’re referenced in AI answers, you’ll feel it in your top-funnel numbers.

Competitors can “win” even when their site isn’t ranking because third-party pages that mention them get cited.

“You want a content plan that isn’t sipping vodka Red Bulls like it’s still 2015, then blacking out the second AI changes the playlist.

This is your GEO content audit curtain call 

ChatGPT doesn’t even have a SERP. It has an answer. If Google leans further into AI Mode, that answer becomes the main act.

Your job: be the source cited.

You want a content plan that doesn’t involve sipping vodka Red Bulls like it’s still 2015 and blacking out the second AI changes the playlist.

So run the audit, tighten structure, add proof, win some offsite mentions, and track inclusion, not just rankings.

Tie this to revenue so nobody calls this a science project.

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Google Ads streamlines scripts documentation

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Trusting Google Ads AI

Google has refreshed its Ads scripts documentation to make it easier for advertisers and developers to build, test, and customize automations.

Why we care. Scripts help advertisers save time and scale campaigns, but the old documentation was clunky and fragmented. The overhaul puts guides, references, and examples into a more intuitive flow that reduces friction for both beginners and power users.

What’s new:

  • Guides are now grouped by experience level and campaign type.
  • A dedicated reference tab makes it easier to browse available script objects.
  • Solutions and examples have been merged, centralizing sample code in one place.

Bottom line: Advertisers and agencies relying on automation should be able to work faster and with less guesswork, while new users have a smoother entry point into scripts.

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Microsoft clarifies nonprofit ad grant program status

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Microsoft Ads

Microsoft Ads Liaison Navah Hopkins confirmed that the company’s Ads for Social Impact program, which grants nonprofits ad credits across Microsoft’s ad inventory, is currently on a waitlist.

Why we care. The program gives nonprofits free ad credits to reach audiences across Bing, Outlook, MSN, Microsoft Edge, and even Yahoo and AOL via syndicated partners. With no strict feature requirements, charities can apply the credit to strategies that best fit their goals, while also accessing training and optional AI tools for creative support.

Eligibility: To qualify, nonprofits must be registered 501(c)(3) or equivalent, have a functioning mission-aligned website, and not fall into excluded categories like hospitals, schools, or government entities. Applying is not a guarantee of acceptance and all applications will be reviewed on the merits.

Bottom line. While details around nonprofit support have been murky, Microsoft is reaffirming its commitment to helping charities stretch their marketing budgets and amplify their missions through free ad spend.

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LinkedIn Company Intelligence API links ads to pipeline, revenue

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5 tests to run to drive growth with LinkedIn Ads

B2B marketers under pressure to prove ROI now have a new tool from LinkedIn – the Company Intelligence API. It is designed to connect campaign performance directly to sales pipeline and revenue outcomes.

Why we care. Traditional attribution models struggle with complex B2B buying journeys, often missing early signals and undervaluing campaigns. LinkedIn’s new API aims to bridge the gap between ad performance and real business outcomes, letting them see which companies are actually moving through the funnel, prove ROI with hard numbers, and make smarter budget shifts toward what drives pipeline and revenue.

By the numbers: Early beta users reported (LinkedIn data):

  • 288% increase in companies engaged
  • 93% increase in pipeline value
  • 30% boost in ROI
  • 37% reduction in cost per acquisition

How it works: Advertisers can access aggregated company-level data (e.g., impressions, clicks) through LinkedIn’s certified analytics partners (Channel99, Octane11, Dreamdata, Factors.ai, Fibbler). The data is ingested into CRM-connected dashboards, giving marketers clearer visibility into ROI, pipeline acceleration, and company engagement across the funnel.

What they’re saying:

  • DataSnipper: “We can now clearly see the impact on pipeline and revenue, uncovering nearly twice as much influenced pipeline as before.”
  • Eftsure: “Reductions in cost per SQL give me strong evidence to justify investment to leadership.”
  • Inovalon: “We plan to shift budget from other channels to LinkedIn.”

What’s next. The Company Intelligence API is now available globally through LinkedIn’s B2B attribution and analytics partners. Adoption could grow as marketers seek stronger proof of performance in a tight-budget environment.

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