u/Broworks-Studio

Like a lot of people here, we have probably found out the hard way that Webflow has no way to serve a bare .txt file at the domain root. That's a dealbreaker for IndexNow, since it verifies ownership by hosting a plain key file at your host. There's an open Wishlist request for this that's been sitting since 2022 with no movement.

Without IndexNow, we were waiting on Bing's own crawl schedule after every publish, which for us meant new or updated pages sometimes took days or weeks to show up in Bing's index. Annoying on its own, but it also matters more than it used to because Copilot is grounded in Bing's index; a page Bing hasn't indexed yet is a page Copilot can't cite, regardless of how it'd rank.

The workaround: skip IndexNow entirely and use the Bing Webmaster Tools API directly. It authenticates with a single API key rather than a hosted file, so there's nothing to serve from the site; the credential lives in CI. We built a small script that:

• pulls our sitemap
• diffs it against the last known state (saved as a JSON file, committed back to the repo each run)
• checks remaining quota before sending anything (the batch endpoint caps at 500 URLs per call)
• submits whatever's new or changed
• runs on a 15-minute cron via GitHub Action

First run just baselines the current sitemap and submits nothing, so you don't torch your quota re-submitting everything you already had indexed. After that, it's only ever sending new or updated URLs.

One catch worth knowing if you try this yourselves: it only catches genuinely new URLs reliably. Whether it catches edited pages depends on whether your sitemap lastmod actually updates when you edit a CMS item's content (on Webflow that's not well documented and seems to vary), so worth testing on your own site before you rely on it (save the sitemap, edit a CMS item without touching the slug, republish, and diff the two files).

Also worth flagging for anyone on Webflow who is sitting behind Cloudflare: you don't need any of this. Cloudflare has a Crawler Hints feature that does the IndexNow relay for you with zero code, since it can serve the key file. We're on GoDaddy for DNS, so that wasn't an option for us, hence the API route.

Wrote up the full build (script structure, GitHub Actions config, the IndexNow vs. API tradeoffs) on our blog if anyone is interested in learning more about this.

We've lost a few projects in the last couple of months to AI builds. They all seem to have the same reasoning, cheaper and faster, which usually isn't true.

For small sites (few pages, no CMS, or agents to update it) yeah sure, it can be fast and cheap. But for larger and more complex websites it will probably take longer than in Webflow and cost a lot more. So you wonder why anyone would go with AI builds at all, and the reason is actually pretty simple.

Remember 10-15+ years back, when we all custom coded most websites and platforms were super limited? That's what AI builds are, just boosted. With AI you can fully own your website and have no restrictions at all. Agents can help you update and manage it, all information is accessible to AI tools and easily extractable. But it takes time to set all that up and make it work flawlessly.

So we get the appeal, it makes total sense. What we don't get is why you'd actually need it.

We're a Webflow agency that built over 200 websites in Webflow and never had a client site go down because of the platform. Not once.

And the extraction thing people think they're buying with an AI build, you already have it. You can set a Webflow site up to be highly crawlable by AI and SEO bots and genuinely citable. We've spent the last 12+ months experimenting with every possible thing you can imagine on our own site around visibility, crawlability, citations and mentions, and none of it needed custom code.

So an AI built website is NOT cheaper and NOT faster. It gives you more control, which is what you already had with custom coded sites, just "easier" now. Still expensive, still slow.

Don't get us wrong, we're all in for innovation and this will only get better over time. We just don't think this is the moment. Webflow gives you what a business actually needs from a website right now, that's what it's done for us and our clients.

Anyone noticed raised demand for AI built websites, what's your experience with that?

Hi all, Milos (SEO guy) from Broworks here. Need to vent a bit and also ask if anyone has actually solved this.

I've spent days literally on this. GSC keeps flagging some of our pages as "Page with redirect" in the coverage report. Nothing broken, checked everything I could think of, and every single tool I use (Screaming Frog, manual checks, you name it) says the page is fine. Even the Live Test inside GSC itself shows a green result.

So why is the coverage report still showing it as an issue?

I read a bunch of threads, watched videos, and tried different things, and honestly, most of the answers say "wait for Google to recrawl" or "check your redirects," which I already did. It's frustrating when you're doing everything right, and the tool still won't clear the flag.

We're on Webflow, so I'm going to double-check the canonical URL setup next, since I've heard GSC can misread the canonicals sometimes (but at this point I'm not even sure that's the real issue).

Has anyone actually fixed this, or found out why it happens? Is this just a GSC reporting delay thing, or is there something deeper I'm missing?

Hi all, Milos (SEO guy) from Broworks here. Need to vent a bit and also ask if anyone has actually solved this.

I've spent days literally on this. GSC keeps flagging some of our pages as "Page with redirect" in the coverage report. Nothing broken, checked everything I could think of, and every single tool I use (Screaming Frog, manual checks, you name it) says the page is fine. Even the Live Test inside GSC itself shows a green result.

So why is the coverage report still showing it as an issue?

I read a bunch of threads, watched videos, and tried different things, and honestly, most of the answers say "wait for Google to recrawl" or "check your redirects," which I already did. It's frustrating when you're doing everything right, and the tool still won't clear the flag.

We're on Webflow, so I'm going to double-check the canonical URL setup next, since I've heard GSC can misread the canonicals sometimes (but at this point I'm not even sure that's the real issue).

Has anyone actually fixed this, or found out why it happens? Is this just a GSC reporting delay thing, or is there something deeper I'm missing?

Got asked recently why two agencies quoted the same project at $8k and $35k respectively. It's a fair question and the answer isn't that one of them is ripping you off.

Here's what's actually driving the variance.

1. CMS complexity is the biggest hidden variable

A five-page brochure site and a site with eight CMS collection types, dynamic filtering, and 200+ pages look similar in a brief but are completely different projects. The second one requires architectural decisions upfront that affect everything downstream from how content editors work, how the site scales, to how fast it loads. Agencies that have built both know this. Agencies that mostly do brochure sites will underprice it and either cut corners or come back with change orders.

2. Who owns the design

If you're handing over finished Figma files, you're buying development. If the agency is designing from scratch, you're buying strategy, creative direction, and production. Those are not the same service and shouldn't cost the same. A lot of confusing quotes come from agencies not being explicit about which one they're actually offering.

3. Integrations multiply cost fast

HubSpot, Marketo, custom APIs, membership logic, localization, each one adds real engineering time. A clean Webflow build with no integrations is a fundamentally different project from one that needs to sync with a CRM, trigger automations, and handle gated content. If your brief mentions any of these and the quote doesn't go up meaningfully, someone is either not accounting for it or planning to use a fragile workaround.

4. The post-launch model changes how agencies price the build

Agencies that work on retainer often price the initial build differently than project-only shops, sometimes lower, because they're pricing for a long-term relationship. Neither model is better, but they're not comparable. If you're getting quotes from both types without knowing which is which, you're not comparing the same thing.

For what it's worth, rough industry ranges for B2B Webflow projects in 2026:

• Simple redesign, existing content, no CMS complexity: $5k–$10k
• Mid-size B2B site, custom CMS, basic integrations: $15k–$25k
• Large site, complex CMS, HubSpot or similar, AEO/SEO baked in: $35k–$55k+
• Ongoing retainer (design, dev, content, AEO): $3k–$8k/month

These aren't our rates specifically, they're what honest conversations in this industry look like. Your mileage will vary based on agency location, team size, and whether they're a one-person shop or a full team.

The $8k vs $35k quote situation? Turned out one was a freelancer scoping a brochure site and the other was a full agency scoping the actual CMS architecture the client described in the brief. Neither was wrong, they just answered different questions.

We're posting here from the Broworks account, Webflow agency for B2B tech companies. Happy to answer questions if useful.

Last week we posted about how ChatGPT, Claude, Perplexity and Gemini retrieve page information on Webflow sites, specifically around on-page structure and citation behavior. That post is here if you missed it.

This is a follow-up on a related but different question: what's the actual difference between a mention and a citation, and how do Perplexity and Google AI Overviews extract for each?

-----------------------

Most AEO content treats mentions and citations as the same thing. They're not.

Citations = traffic signals. When an AI model cites your page, it links to it. Users can click through, it's the closest thing to organic traffic in an AI-generated answer.

Mentions = brand awareness signals. Your name shows up in an answer, but no link, no click, no page attribution. Still valuable, but different and much harder to earn.

Understanding which one you're optimizing for changes everything about how you structure your content.

What we tested

We ran structured changes across our own site and tracked visibility through Profound, focusing on Perplexity and Google AI Overviews, the two platforms where we had the clearest before/after signal.

Baseline: Perplexity visibility at ~16%, Google AI Overviews at ~0.6%.

3 days after implementing these changes: Perplexity up to 21%, Google AI Overviews up to 4%.

Here's what we changed and why it worked.

Finding 1: Perplexity rewards specificity

Perplexity's citation behavior responds to concrete, quantified information. Not vague claims but actual numbers, specific outcomes, named results.

Pages that contained exact stats, measured results, and named specifics got pulled more consistently than pages with descriptive but unquantified content.

If you want Perplexity citations, every key claim needs a number attached to it. "Significant improvement" doesn't get cited. "284% organic traffic growth" does.

Finding 2: Google AI Overviews respond to page architecture, not just content quality

This one is structural. Google AI Overviews extract from specific positions on the page, and the pattern we observed:

• H1 framed as a direct question performs better than a declarative title
• The first paragraph directly below the H1 needs to answer that question in 2–3 sentences
• For articles: this direct answer should sit above the TL;DR and body content, or conditionally visible if not all articles follow this structure
• H2s also matter, they function as signal anchors for what each section covers

We updated H1s, H2s, and first and second paragraphs across key pages with this in mind. The 0.6% → 4% Google AI Overviews move happened within 3 days.

Finding 3: These changes aren't only for AI they're better UX too

The framing we keep coming back to internally: we now have two audiences for every page, AI models and humans.

The good news is optimizing for AI citation behavior mostly aligns with better human UX. Leading with the direct answer, surfacing the key information immediately, structuring headings as navigational cues, these things help both audiences.

The era of burying your point three paragraphs in is over.

What this doesn't solve: mentions

Getting cited is achievable through on-page work. Getting mentioned is a different problem entirely.

Mentions require AI models to know who you are independent of a specific query, that comes from:

• Third-party validation (podcasts, directories, listicles, backlinks)
• Co-occurrence with competitors in existing indexed content
• Topical authority built over time across multiple sources

On-page changes don't move mention rates meaningfully, that's an authority and distribution problem, not a structure problem.

The short version if you skimmed:

• Citations drive traffic. Mentions drive brand awareness. Don't conflate them.
• Perplexity responds to specific numbers and quantified claims
• Google AI Overviews extract from H1 (question format) + first paragraph (direct answer)
• These structural changes moved our Google AI Overviews visibility from 0.6% → 4% in 3 days
• Mentions require external authority signals, on-page optimization alone won't get you there

We build and optimize Webflow sites for B2B clients, and a few months ago we decided to stop guessing about AEO and actually test what changes citation behavior, not just whether your domain gets cited, but which specific page gets pulled and why.

Here's what we found (some of it confirmed what we suspected and some of it surprised us).

First, the distinction most AEO content ignores: indexing vs. live browsing

AI models retrieve information from two fundamentally different points, and they behave differently at each.

Indexing is when the AI crawls and stores your content independently, on its own schedule. You can influence how often it happens (frequent updates, authority signals, inbound links) but you can't control the timing. Most of what gets cited in a standard query comes from indexed content.

Live browsing is triggered when a user pastes a URL directly into the prompt or explicitly asks the model to visit a page. It's real-time and accurate, the model reads exactly what's there.

Why does this matter? Because most on-page AEO changes are optimized for live browsing behavior, but the majority of actual citation queries run on indexed content. These are not the same thing, and conflating them leads to bad conclusions about what's working.

What we tested

We ran structured tests across a telecom client (two product pages) and our own website. We tested across ChatGPT, Claude, Perplexity, and Gemini. Measurement was through Profound tracking plus manual prompting (before changes, immediately after, and again 3–4 weeks later). We used multiple prompt variations: some highly specific (product name, no URL) to trigger indexing behavior, some with URLs to trigger live browsing.

Finding 1: On-page structure influences which page gets cited, not just whether your domain gets cited

This is the most actionable finding. Before our changes, when someone queried product-specific information, AI models were pulling from a blog article and a PDF spec sheet, not the actual product page.

After we restructured the product pages to use what we're calling declarative sentences (single paragraphs that contain the product name, key specifications, and context all together, in plain visible HTML) ChatGPT and Claude began citing the product page more often than the blog and PDF.

The operative word is "plain visible HTML." We confirmed that content inside JavaScript animations, elements with 0% opacity, or anything that isn't purely rendered in the DOM does not get reliably extracted at the indexing layer. If your content isn't raw and accessible, it effectively doesn't exist for indexing purposes. This is particularly relevant in Webflow where content inside interactions, Lottie animations, or elements set to display:none for animation purposes won't be reliably extracted at the indexing layer.

The declarative sentence structure matters too. The same information spread across multiple sections of a page (intro, features block, spec table, CTA) was cited less reliably than the same information consolidated in a single, direct paragraph.

Finding 2: ChatGPT and Claude behave differently than Gemini and Perplexity at the citation layer

This one was consistent across all our tests and we've since seen it replicated enough times to treat it as a working pattern.

ChatGPT and Claude appear to weight source relevance and structural clarity more heavily. When we improved on-page structure, citation behavior shifted toward the optimized page, even when other pages had more inbound links or were older and more established.

Gemini and Perplexity consistently defaulted to higher domain authority sources first. Structural changes on our pages didn't move what they cited, they cited the same external high-authority pages regardless. Our domain-level changes had minimal effect here.

The practical implication: if your audience is primarily using ChatGPT or Claude to research, on-page AEO work has a real ROI. If they're on Gemini or Perplexity, you need to focus on external authority signals, getting cited by the pages that those models are already pulling from.

Finding 3: TOFU AEO FAQs moved our domain citation position from 8th to 4th in 3–4 weeks

Separate from the declarative sentence tests, we added AEO-optimized FAQs to top-of-funnel pages on our own site. Not the standard BOFU FAQ accordion, these were structured specifically around the questions AI models are already answering in our category, written to directly address query intent.

Profound tracking showed our domain moving from 8th to 4th citation position across our tracked queries within 3–4 weeks of those pages being indexed.

This was the clearest quantified result from everything we tested. The declarative sentence changes moved which page got cited. The TOFU FAQ changes moved where our domain ranked in the citation hierarchy overall.

What we still don't know

Indexing timing is genuinely uncontrollable. We can't isolate every variable authority changes, external links, and model updates all happen in parallel. Our sample size is limited. These findings are a working model, not a definitive study.

We're also not sure yet how durable the citation position improvement is, or whether it degrades without continued content updates.

The short version for anyone who skimmed:

• Indexing and live browsing are different retrieval behaviors, optimize for indexing first
• Consolidate product/service information into single declarative paragraphs in raw HTML
• ChatGPT and Claude respond to on-page structure changes; Gemini and Perplexity respond to domain authority
• TOFU AEO FAQs had the clearest impact on domain-level citation position (8th → 4th, ~3–4 weeks)