How I Would Fix slow pages and weak Core Web Vitals in a Make.com and Airtable marketplace MVP Using Launch Ready.

How I Would Fix slow pages and weak Core Web Vitals in a Make.com and Airtable marketplace MVP Using Launch Ready

If a marketplace MVP built on Make.com and Airtable is slow, the symptom is usually not "the internet is bad." It is usually one of three things: too much work happening in the browser, too many third-party calls on first load, or a backend flow that waits on Airtable and Make before showing anything useful.

The first thing I would inspect is the actual user journey from landing page to first meaningful action. I want to see what blocks Largest Contentful Paint, what shifts layout during load, and whether any API keys, webhooks, or embeds are exposed in the page source before I touch code.

Triage in the First Hour

1. Open the site in Chrome DevTools and run Lighthouse on mobile. 2. Check Core Web Vitals in Search Console or PageSpeed Insights. 3. Load the homepage with network throttling set to Fast 3G and watch the waterfall. 4. Inspect the browser console for failed scripts, CORS errors, and long tasks. 5. Review all third-party scripts: analytics, chat widgets, embeds, trackers, maps, video players. 6. Open the Airtable base and count how many linked records, formulas, rollups, and attachments are used on hot paths. 7. Review Make.com scenarios for synchronous chains, retries, loops, and unnecessary HTTP modules. 8. Check whether any public forms or marketplace listings hit Airtable directly from the client. 9. Confirm Cloudflare is active with caching rules, compression, and bot protection enabled. 10. Inspect DNS, SSL status, redirects, and subdomain routing for extra hops or misconfiguration.

If I can only do one thing in hour one, I would identify what blocks first paint and what delays interaction. That tells me whether this is mostly frontend weight, backend latency, or both.

curl -I https://your-domain.com

I use that quick check to confirm redirect chains, cache headers, compression hints, and whether SSL is clean before I go deeper.

Root Causes

| Likely cause | What it looks like | How I confirm it | |---|---|---| | Heavy frontend bundle | Slow LCP, poor INP, long main-thread tasks | Lighthouse shows large JS payloads and high execution time | | Too many third-party scripts | Page loads but feels sticky and unstable | Network waterfall shows multiple blocking external requests | | Airtable used as a live database for every view | Slow listing pages and search filters | API calls spike on each page view or filter change | | Make.com flows doing too much synchronously | Forms hang while waiting for automation | User action waits on webhook completion before success state | | Bad caching or no CDN edge caching | Every visit re-downloads content | Response headers show no cache control or Cloudflare bypass | | Weak security controls around public endpoints | Bot traffic or abuse inflates load | Logs show repeated form submits, scraping patterns, or noisy errors |

1. Heavy frontend bundle

This is common when founders build fast in React or a no-code wrapper around dynamic components. The page may look fine in development but ship with big libraries, unoptimized images, and too much client-side rendering.

I confirm it by checking bundle size, LCP element timing, and main-thread blocking time. If JavaScript execution is taking more than 2 seconds on mobile mid-tier devices, users will feel it even if the design looks polished.

2. Third-party scripts everywhere

Marketplace MVPs often accumulate chat widgets, review widgets, analytics tags, embedded calendars, social pixels, and ad scripts. Each one adds latency and can worsen INP or cause layout shift.

I confirm this by disabling non-essential scripts one by one and re-running Lighthouse. If performance jumps after removing two widgets, I know where the drag is coming from.

3. Airtable as a real-time app database

Airtable is great for an MVP control plane. It is not great as a high-traffic read model for every browse action if you query it directly from the client.

I confirm this by looking at request counts per session and response times from Airtable endpoints through your app layer. If every category browse triggers multiple Airtable reads plus linked record expansion, you have a bottleneck.

4. Make.com doing synchronous work

Make.com should orchestrate workflows after user-facing actions are already acknowledged whenever possible. If your submit button waits for email sending, record creation updates multiple tables live on screen first load suffers.

I confirm this by tracing scenario execution time end to end. If the user sees a spinner while Make does five downstream steps that do not need to block response time, that is wasted latency.

5. No edge caching or bad Cloudflare setup

Without Cloudflare caching rules or proper static asset headers you pay full origin cost every time. That hurts both speed and resilience under traffic spikes.

I confirm this by checking response headers for cache status and comparing repeat-load performance against cold-load performance. If repeat visits are almost as slow as first visits there is no real caching benefit.

6. Security noise creating performance drag

From a cyber security lens this matters because abuse often shows up as "performance" problems first. Scrapers hitting public listing pages or bots hammering forms can inflate load times and create false error spikes.

I confirm it by reviewing logs for repeated IPs,user agents,and burst patterns around public routes. If traffic patterns look unnatural,I treat that as both a security issue and a performance issue.

The Fix Plan

My approach is to reduce work before adding more infrastructure. I would not start by rebuilding everything; I would start by removing blockers from the critical path.

1. Split pages into critical above-the-fold content and everything else. 2. Move non-essential scripts to deferred loading or remove them entirely. 3. Compress images aggressively and serve responsive sizes only. 4. Replace direct client-to-Airtable reads with a lightweight server endpoint or cached layer where possible. 5. Turn slow list views into paginated views with default limits of 20 to 30 items. 6. Cache stable marketplace data at the edge using Cloudflare where content does not need real-time freshness. 7. Move long-running Make.com steps out of the user request path. 8. Add loading states that show useful progress instead of blank spinners. 9. Set up environment variables properly so secrets never live in frontend code. 10. Verify DNS redirects so there are no extra hops between apex domain,www,and app subdomain.

For marketplace search results,I would strongly prefer precomputed filtered views over live joins on every request if freshness requirements allow it. That usually gives better p95 latency without making the system harder to support.

For Make.com,I would redesign scenarios so user-facing actions return fast:

• create record
• acknowledge success
• queue downstream enrichment
• notify later by email or dashboard update

That reduces timeout risk and makes failures easier to recover from without losing user trust.

For Airtable,I would audit formulas,references,and attachment-heavy fields because those often become hidden latency multipliers when records grow past a few thousand rows per table. If one base has become operationally heavy,I would split hot data from admin data rather than letting everything pile into one table.

Regression Tests Before Redeploy

Before shipping,I want proof that speed improved without breaking marketplace behavior or exposing data.

Acceptance criteria:

• Mobile Lighthouse Performance score at least 80 on key pages.
• LCP under 2.5 seconds on common landing pages.
• CLS under 0.1 across homepage,listings,and checkout/contact flows.
• INP under 200 ms for primary interactions like filter,sort,and submit.
• No console errors on initial load in Chrome,Safari,and Firefox.
• No public page exposes secrets,tokens,file URLs meant to be private,endpoints intended only for admin use.
• Form submissions succeed even if downstream Make.com steps fail later.
• Uptime monitoring alerts fire within 5 minutes of outage detection.

QA checks: 1. Load homepage cold twice: once with cache disabled once with cache enabled. 2. Test browse,listings detail,page search,and contact/submit flows on mobile emulation. 3> Verify empty states,no-results states,and error states render cleanly. 4> Trigger rate-limited form submits to ensure abuse controls do not block normal users. 5> Confirm emails send correctly with SPF,DKIM,and DMARC aligned domains if outbound mail is part of Launch Ready scope. 6> Re-run Lighthouse after each fix so regressions are visible immediately.

If there are automated tests,I want at least smoke coverage on routing,data fetches,and form submission paths before redeploying anything that touches production traffic.

Prevention

The easiest way to stop this coming back is to put guardrails around every new feature request.

I would add these rules:

• No new third-party script goes live without an owner and business reason.
• Any new collection,page template,input flow gets a performance check before merge.
• Public endpoints get rate limiting,CORS review,and input validation by default.
• Secrets stay in environment variables only,no exceptions.
• Any Make.com scenario that touches customer-facing actions must have retry logic,error alerts,and manual fallback steps documented.
• Any Airtable base used in production gets reviewed for field bloat,indexing pressure,and access scope every sprint.

From a UX angle,I would also keep pages simpler than founders usually want at MVP stage because clutter costs conversion when load times are already weak. A cleaner listing page with fewer visual elements often converts better than an overdesigned page that takes 5 seconds to become usable.

From a security angle,the rule is simple: public does not mean open-ended exposure.If you let bots scrape listings,use forms without protection,and leak internal structure through client-side calls,you will pay for it later in support load,downtime risk,and fraud cleanup.

When to Use Launch Ready

Launch Ready fits when you already have a working MVP but deployment hygiene is holding back speed,reliability,and trust.It is especially useful if your domain,email,DNS,caching,secrets,and monitoring are still stitched together manually across tools like Webflow,Carrd,Bubble,Lovable,Bolt,Cursor React apps,next.js wrappers,Airtable,and Make.com automations.

• domain setup
• email authentication
• Cloudflare
• SSL
• redirects
• subdomains
• caching
• DDoS protection
• production deployment
• environment variables
• secrets handling
• uptime monitoring
• handover checklist

What you should prepare: 1. Domain registrar access 2> Cloudflare access if already connected 3> Hosting or deployment access 4> Airtable base access with admin rights 5> Make.com workspace access 6> A list of all active forms,inboxes,and automations 7> Any brand email addresses that need SPF/DKIM/DMARC setup

If your pages are slow because deployment basics are messy,this sprint pays off fast because it removes avoidable friction before we touch deeper product work.I use it when founders need fewer outages,faster pages,and less fear about shipping changes again next week.

References

1. roadmap.sh frontend performance best practices: https://roadmap.sh/frontend-performance-best-practices 2> roadmap.sh backend performance best practices: https://roadmap.sh/backend-performance-best-practices 3> roadmap.sh API security best practices: https://roadmap.sh/api-security-best-practices 4> Google Web Vitals: https://web.dev/vitals/ 5> Cloudflare docs: https://developers.cloudflare.com/

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Take the next step

If this is a problem in your product right now, here is what to do next:

• [Use the free Cyprian tools](/tools) - estimate cost, score app risk, check launch readiness, or pick the right service sprint.

• [Book a discovery call](/contact) - I will tell you honestly whether you need a sprint or if you can DIY the next step.

*Written by Cyprian Tinashe Aarons - senior full-stack and AI engineer helping founders rescue, launch, automate, and scale AI-built products.*