How to Vet a Lovable SEO Partner Without Getting Burned

A SaaS founder asked three agencies to pitch Lovable SEO services. All three sent nearly identical proposals: keyword research, technical audit, content calendar. Two weeks after signing with the cheapest bid, the founder discovered the agency had never worked on a Lovable site. They were applying WordPress SEO tactics to a TanStack Start framework. The site wasn't ranking. ChatGPT had never cited it. And the founder had just burned $8,000.

That story repeats every month as more businesses build on Lovable and discover traditional SEO agencies can't deliver what they promise. The vetting process most buyers use — checking reviews, comparing prices, asking about "SEO experience" — doesn't filter for Lovable-specific capability. A checklist built for WordPress partnerships fails completely when the underlying technology is TanStack Start, Supabase, and server-side rendering.

Here's how to vet a Lovable SEO partner without learning the expensive way.

Why Do Most Lovable SEO Pitches Sound Identical?

Every agency claims they "do SEO for modern frameworks." Ask what makes Lovable different from Next.js or Astro, and most pivot to generic answers about site speed and clean code. The reality: most agencies discovered Lovable in the last six months when their clients started asking about it.

The standard pitch follows a template. Keyword research. Technical audit. Content strategy. Backlink outreach. All tactics that work on WordPress but miss what actually makes a Lovable site visible to AI engines. Zero mention of ChatGPT citations. No discussion of how Perplexity decides which business to recommend. No proof they've ever gotten a Lovable site into Google AI Overviews.

One Lovable-built consulting firm hired an agency that promised "cutting-edge SEO for React-based platforms." Three months in, the agency delivered blog posts optimised for traditional search but formatted as long-form articles ChatGPT would never extract from. They built backlinks from directories Perplexity doesn't crawl. They tracked keyword rankings but never tested whether ChatGPT could answer "best [service] in [city]" with the client's business. The site ranked on page two of Google. AI engines ignored it completely.

When every pitch sounds identical, the vetting checklist needs to go deeper than surface claims.

Can They Show You a Lovable Site Ranking in Google AI Overviews?

Ask for proof. Not a case study PDF. Not a testimonial. A screenshot of Google AI Overviews including a Lovable site they optimised, with the domain visible and the date stamp showing it's recent.

Then verify the domain is actually built on Lovable. View source. Check for TanStack Start signatures in the HTML. Look for Supabase API calls in the network tab. Agencies that claim Lovable expertise but show Next.js or Webflow examples don't have transferable knowledge. According to Google Search Central, JavaScript framework differences matter significantly for how crawlers process content.

Traditional rank tracking screenshots prove nothing about AI visibility. A site can rank #3 for a keyword in standard Google results but never appear in AI Overviews, never get cited by ChatGPT, never surface in Perplexity answers. Those are separate visibility layers with separate optimisation requirements.

Red flag: the agency pivots to "we focus on organic rankings first, then AI visibility." That's backwards. In 2026, a Lovable business that ranks on page one but doesn't get AI citations is leaving 40-60% of potential traffic on the table. AI visibility isn't a phase-two add-on. It's the foundation.

Do They Understand TanStack Start's Rendering Requirements?

Lovable uses TanStack Start for server-side rendering. That's not a minor technical detail. It's the difference between a site that Google can crawl properly and one that serves blank HTML to bots.

Ask the agency to explain the difference between server-side rendering (SSR) and client-side rendering (CSR) and why it matters for Lovable SEO. They should be able to describe how TanStack Start renders pages on the server before sending them to the browser, ensuring crawlers see full content immediately. If they start talking about "progressive enhancement" or "hydration" without connecting it to crawler visibility, they're reciting framework docs without understanding the SEO implications.

Then ask how they verify Googlebot sees rendered content. The answer should involve Google Search Console's URL Inspection tool, checking the rendered HTML view, and comparing it to what users see. Should mention testing with crawlers that don't execute JavaScript to catch SSR failures.

One agency edited a Lovable client's content entirely in client-side React components, assuming the changes would rank. They didn't. Googlebot saw the pre-render shell. The optimised content never made it to the index. Three months of work disappeared because the agency didn't understand how TanStack Start serves content to crawlers versus browsers. Lovable's documentation covers SSR requirements, but agencies that haven't built on the platform miss the nuances.

What's Their Process for Getting ChatGPT to Cite a Lovable Site?

This is where most agencies reveal they're guessing. Ask them to walk through their AEO workflow step-by-step. They should describe a repeatable process, not a vague strategy.

The answer should include answer capsule format — writing 2-3 sentence direct answers immediately under headings so ChatGPT can extract them cleanly. Should mention entity density — ensuring brand names, product names, and category terms appear with enough frequency and context for LLMs to understand relationships. Should reference llms.txt files and how they structure them to guide AI crawlers.

Red flag: "The agency writes high-quality content and hopes ChatGPT finds it." That's not a process. That's publishing and praying.

Strong agencies test prompts in ChatGPT during optimisation. They ask "best [service] for [use case]" and see if the client appears. They iterate on content structure until ChatGPT starts citing the site. They track which content formats get pulled into answers and which get ignored. OpenAI's documentation on how ChatGPT search works explains the retrieval process, but applying it to Lovable sites requires hands-on testing.

If the agency can't show you ChatGPT citing a site they've worked on, they don't have proven AEO capability. They're experimenting on your budget.

How Do They Handle Lovable's Schema Markup Limitations?

Lovable doesn't auto-generate schema like WordPress plugins do. There's no Yoast equivalent that adds JSON-LD with a few clicks. Schema implementation on Lovable requires manual injection into page templates or component-level code.

Ask the agency to explain their schema implementation method for Lovable sites. They should describe injecting JSON-LD structured data into the document head, testing it with Google's Rich Results Test, and validating that it doesn't break the build when Lovable regenerates code.

Request schema validation reports from past Lovable clients. Not generic schema examples. Actual validation screenshots showing Organisation schema, LocalBusiness schema, Product schema, or Article schema implemented on a live Lovable domain and passing Google's validator.

One Lovable-built local service business hired an agency that promised "full schema implementation." The agency added schema to a staging environment but never tested it on the production Lovable build. When the site went live, the schema broke because it conflicted with Lovable's default meta tag structure. Google Search Console flagged errors. Rich results disappeared. The agency didn't know how to fix it without breaking other elements.

Schema on Lovable isn't plug-and-play. Agencies that treat it like WordPress implementation will create more problems than they solve.

Can They Prove Lovable Sites They've Worked On Actually Got Faster?

Core Web Vitals matter for Lovable SEO just like any other platform. But Lovable's architecture gives it inherent speed advantages — if the agency knows how to optimise it properly.

Request before/after PageSpeed Insights or Lighthouse scores from past Lovable projects. The "after" score should hit 90+ on performance when the optimisation is done right. Lovable sites that score below 85 are either poorly configured or carrying unoptimised images and scripts.

Ask how they optimise images on Lovable. They should mention lazy loading, next-gen formats like WebP, and proper sizing for different viewports. Ask about Supabase query optimisation — slow database calls tank Lovable site performance faster than anything else.

Red flag: the agency doesn't mention Supabase at all. Lovable sites use Supabase for backend data. An agency that ignores database performance doesn't understand the full stack. They'll optimise frontend code while slow queries kill page load times.

In AIFun Agency's work with Lovable clients, sites that hit 95+ Lighthouse performance scores see 30-40% better crawler efficiency and higher AI citation rates. Speed isn't vanity. It's infrastructure for visibility.

Do They Have a Prerender Strategy for Lovable Sites?

TanStack Start handles SSR well for most pages, but some Lovable sites have edge cases where crawlers still struggle. Dynamic content. Client-side state. Heavy JavaScript interactions. Those scenarios sometimes need prerendering to ensure full crawler visibility.

Ask if the agency has experience with Prerender.io or similar solutions for Lovable sites. They should know when to recommend prerendering versus relying on native SSR. Should explain how prerendering works as a middleware layer between crawlers and the Lovable site.

Then ask when they've used it. If they've never implemented prerendering on a Lovable site, they're missing a tool that solves real indexing problems.

One Lovable-built SaaS company's product pages weren't indexing despite proper SSR configuration. Google Search Console showed crawl attempts but no indexed pages. AIFun Agency added Prerender.io to serve pre-rendered HTML to bots while users got the full interactive experience. Within two weeks, all product pages indexed. Within six weeks, ChatGPT started citing them in SaaS comparison answers.

Prerendering isn't always necessary. But agencies that don't know it exists can't solve the problems where it's the only fix.

What Do They Actually Deliver in Month One?

Vague proposals kill Lovable SEO projects. Ask for specific deliverables with dates. Not "strategy development" or "initial audit." Concrete outputs.

Month one should include a technical audit document identifying SSR issues, schema gaps, and Core Web Vitals problems. Should include schema implementation — not just recommendations, but live JSON-LD validated in Google Search Console. Should include a content plan with target queries, answer capsule formats, and publication dates.

Red flag: "Month one is discovery and strategy." That's agency speak for "we haven't started the real work yet." Discovery should take one week maximum on a Lovable site. Strategy should be embedded in deliverables, not a separate phase.

Compare deliverable lists across three agencies before deciding. The agency with the most specific, dated, measurable outputs in month one is usually the one that's done this before. The one with the vaguest proposal is the one that's figuring it out as they go.

How Do They Measure Success Beyond Google Rankings?

Traditional rank tracking is table stakes. Modern Lovable SEO requires tracking AI citations across ChatGPT, Perplexity, Google AI Overviews, Gemini, and Bing AI Copilot.

Ask how they monitor AI citations. Manual checks? Automated tools? How often? What prompts do they test? If they don't have a clear answer, they're not actually tracking the visibility layer that drives 40-60% of modern search traffic.

Request a sample dashboard or reporting template. It should show traditional keyword rankings AND AI citation frequency AND traffic from AI referrals. If the dashboard looks like a 2018 SEO report with keyword positions and backlink counts, the agency is measuring the wrong things.

One Lovable consulting firm tracked only Google rankings for six months. Rankings improved. Traffic stayed flat. Turns out most of their target audience was asking ChatGPT for recommendations, and the site never appeared in answers. They were optimising for a channel that wasn't driving their business. When they switched to an agency tracking AI citations, they saw which content formats ChatGPT preferred and adjusted accordingly. Citations doubled in eight weeks. Inbound leads followed.

Traditional rank tracking alone signals an outdated approach to Lovable SEO.

What AIFun Agency Sees in Vetting Calls with Lovable Businesses

In AIFun Agency's vetting calls with Lovable businesses, a clear pattern emerges: the teams that ask technical questions upfront close deals 40% faster than those who choose based on pitch decks alone. They're not wasting time with agencies that can't deliver. They're filtering for proven capability before the contract conversation.

Most buyers don't ask technical questions until after signing. They evaluate agencies on brand presentation, pricing, and vague promises about "results." Then they discover three months in that the agency doesn't understand TanStack Start, can't implement schema without breaking the build, and has never gotten ChatGPT to cite a client.

The common mistake: choosing based on price without proof. The cheapest agency is usually the one that's never worked on Lovable before and is using the project to learn. The most expensive agency is often charging for a brand name built on WordPress SEO that doesn't transfer to modern frameworks.

Businesses that vet deeply — asking for Lovable-specific proof, technical explanations, and measurable deliverables — close deals faster because they're confident in capability. They see results sooner because the agency isn't learning on their budget. They avoid the expensive mistake of hiring an agency that sounds right but can't execute.

The vetting checklist isn't about being difficult. It's about filtering for agencies that have actually done this before.

In AIFun Agency's work with clients building Lovable websites, the teams that ship answer-capsule sections under every H2 are the ones that start earning AI citations within a few weeks. ## Ask These Questions Before Signing Anything

The agencies that can answer every question on this checklist with specific proof are rare. Most will stumble on TanStack Start rendering, pivot away from AI citation tracking, or admit they've never implemented schema on Lovable.

That's the point. The vetting process should eliminate agencies that claim Lovable expertise but can't demonstrate it. Should surface the ones that have repeatable processes, proven results, and technical depth specific to Lovable's architecture.

Before signing a contract, ask for a technical audit checklist for Lovable sites the agency uses. Ask to see their process for implementing AEO on Lovable websites. Ask for client references who can verify results on Lovable specifically, not WordPress or Webflow projects.

The right Lovable SEO partner should welcome technical vetting. They should have proof ready. They should explain their process clearly because they've done it multiple times. If an agency resists detailed questions or pivots to generic SEO concepts, they're not the partner for a Lovable site.

Ready for ChatGPT to recommend your Lovable site instead of a competitor's? See how AIFun Agency does it →