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How pricing experiments helped me reach $6,000 MRR
It’s been a while since my last post! Since then, I’ve been focusing on growing Remote Rocketship. I’m super excited to announce that it’s reached $2,000 MRR! 🥳 You may recall from the last post that I mentioned that the only sustainable channel to grow the website is SEO and that I was learning how to do it from scratch (and it’s now getting 19,000 monthly search clicks!). In this post, I want to share everything I’ve learned about SEO and how to approach it. In doing so, I hope you’ll also share your tips and help me fill in any gaps in my knowledge!
Over the last month, I’ve been exploring a new idea in the cold outbound sales space. The idea is to generate personalized cold emails at scale using AI. Currently, there is a trade-off between quantity and quality when it comes to sending cold emails: Either you spend lots of time researching a prospect and crafting a personalized email, or you send generic emails in bulk to a large group of people. Naturally, the response rate for personalized emails is much higher than the generic ones, so I’ve been looking into how to do this at scale.
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Kidz Fun Art is a drawing, colouring and animation app for kids that I’ve been building since 2021. It runs in the browser also as a simple wrapper app on iOS, iPadOS and Windows. It wasn’t getting a great click through rate on Google, even for people who directly searched for it. So, for two days I took a hard look at how fast it loads and how search engines see it. It wasn’t flattering. This post covers what I found, what I changed and what the graphs say now. Short version: on a simulated slow phone, the homepage’s Largest Contentful Paint got about 2.6× faster (15.9 s to 6.1 s) and its first load is about 82% smaller (4.2 MB to 0.75 MB). I also fixed a set of SEO mistakes that are, frankly, embarrassing to write down. I’ll write them down anyway. Part 1: Google had no idea what the site was for I started by reading 16 months of Google Search Console data. 9,380 clicks in total. About 9,200 came from people who had typed “kidz fun art” or a close spelling. People searching for what the app actually does (“coloring app for kids”, “ai art for kids”, “make a comic book”) sent the site 164 clicks. In 16 months. Total. When there was a relevant page, Google ranked it well. The site was #1 for things like “drawing app for kids ipad” and a German query that means “paint by numbers app without ads”. There just weren’t many relevant pages. Then I looked at the code, and the cause was obvious. The homepage <title> was “Kidz Fun Art” in all 12 languages. That’s a fine name, and a terrible title. It tells a search engine nothing. The homepage’s first <h1> was the pricing table’s “Choose your experience”. I was, in effect, telling Google that the most important thing on my homepage was the checkout. Every blog post had the same meta description: a generic line about “news, updates, tips”. Each post’s front matter already had a perfectly good excerpt field that nobody read. Blog posts had two <h1>s: the site header and the post title. There was no structured data at all. The sitemap that redirected every single URL This one stings. The sitemap is the one file whose whole job is to say “here are my URLs, please index them”. Mine listed 17 URLs, and every one of them redirected. The sitemap build used an environment variable that resolved to kidzfun.art. The site lives on www.kidzfun.art, so every URL got a 308. Only the English blog posts were listed. The other 11 languages appeared only as hreflang alternates, which pointed at redirecting URLs too. There were no <link rel="canonical"> tags on any page and no hreflang in the page <head>. Google was left to guess which URL was the real one, and it guessed wrong a lot. What I changed: The sitemap is now built on https://www.kidzfun.art, with 204 URLs: every home page, blog index, blog post, About page and gallery page, in all 12 languages. Each one lists all of its language alternates plus an x-default. A shared SeoLinks component adds an absolute canonical (www, no query string) and the full hreflang set to every public page. The ?v= cache-busting URLs that had been showing up as duplicates now canonicalise to the clean URL. /xx/blog/yy/... URLs, which returned a 500 in production (oops), now 308 to /blog/yy/.... Login, account, debug, export and embed pages send X-Robots-Tag: noindex, follow from next.config.js, so they stop using up crawl budget. robots.txt now mentions the sitemap. Novel idea. Why Google skipped half the site Search Console’s Pages report had 93 of 174 known pages not indexed. Every reason on that list traces back to the mistakes above: “Page with redirect” (22): that sitemap, plus internal links to the non-www host. “Duplicate without user-selected canonical” (18): I hadn’t selected any canonicals. Fair cop. “Crawled, currently not indexed” (39): mostly translated posts that Google reached through redirecting URLs, plus thin pages like /login. “Discovered, currently not indexed” (12): Google found these and decided they weren’t worth a visit. With no sitemap entry and no hreflang, I hadn’t given it a reason to. On-page fixes Titles and descriptions: Each blog post got its own seoTitle and description, in all 12 languages. The meta description now comes from the post’s excerpt, which is what that field was for all along. The About pages take their title and description from their own localized Markdown. They had been sharing an English title and a generic description. One <h1> per page: A # heading inside a post’s Markdown now renders as an <h2>, so the post title is the only <h1>. The About page opts back in with a keepH1 prop. Its Markdown heading is the page title. This fix arrived in two parts. The first part left the About page with zero <h1>s. I noticed, eventually. Structured data and social tags: JSON-LD for the home page (the app), blog posts (articles) and the embedded videos. Open Graph and X/Twitter tags on every public page, so shared links get a proper card. A real 404 for deleted gallery images: The AI gallery shows a friendly “AI Artwork Not Found” page when an image has been deleted. It used to return 200 OK, which Google calls a “soft 404” and dislikes. It now returns a 404 with noindex, and a 503 if the Firestore lookup itself fails, so a database hiccup tells crawlers “come back later” rather than “this is gone”. Part 2: Making the homepage fast The homepage is the app. It works offline, so every dialog (save, stickers, colouring pages, “get an adult”, “no wifi”) is server-rendered into the HTML up front. That’s a deliberate trade-off, and I kept it because I want new users to be able to immediately be able to start drawing as soon as they launch the app. What I hadn’t thought about was what it meant for the network. What the homepage downloaded before the app could start I measured the live site with a Lighthouse-style mobile profile: slow 4G (1.6 Mbps, 150 ms latency), 4× CPU slowdown, empty cache. First load: 4.5 MB over 198 requests. The homepage HTML alone was 358 KB, with about 77 <img> tags in hidden dialogs. The browser dutifully fetched every one of those images. The script that starts the app (main.min.js, 191 KB) sat at the very end of the document, so the browser found it last and gave it whatever bandwidth was left. The app script finished arriving at about 14 seconds. The CPU was not the problem. Every long task was under 300 ms. This was purely about bandwidth and request order. I had built a very polite queue and put my own app at the back of it. Watch the queue The waterfall is a simplified illustration. The milestone times (first paint, LCP, load) are measured: slow 4G + 4× CPU, local production build, median of 3 runs. My Largest Contentful Paint was the “Contact support” link The canvas doesn’t count toward LCP, and the toolbar buttons are small. So on a slow load the largest thing painted was… the loading dialog. The loading dialog fades in its “Taking a while? Contact support” text after 5 to 7.5 seconds. On a slow connection, that text became the page’s LCP element, at 15.9 s. I was measuring my page speed by how long it took to suggest the user complain about my page speed. There’s a lesson in there somewhere. The fix wasn’t to change the dialog. It was to make the app start sooner, so it paints before that text ever appears. What I changed Preload the app script. I added <link rel="preload" as="script"> in <head> for main.min.js and errorHandler.min.js. The <script> tags stay where they were, so execution order doesn’t change. The browser just starts fetching them before any image. This one line did more than anything else on this list. It’s a little humbling. Turn the three dialog GIFs into MP4s. Three animated GIFs: an arrow pushing pictures into a tablet (927 KB), a dancing rainbow pencil (650 KB) and a paper plane (305 KB). That’s 1.9 MB of decoration in dialogs most visitors never open on their first visit. I re-encoded them with ffmpeg: H.264 High profile, -preset veryslow -crf 20, yuv420p, +faststart, constant frame rate taken from each GIF’s frame delay. The commands are committed as scripts/gif-to-mp4.sh. The result is 130 KB in total, with SSIM between 0.988 and 0.993 against the originals. The pencil needed tpad=stop_mode=clone:stop_duration=0.2, because ffmpeg’s GIF reader drops the final 250 ms hold and the dance lost its big finish. The new <video autoplay loop muted playsinline> tags render at exactly the same size and class as the old <img> tags. Alt text moved to aria-label. Locked colouring thumbnails were full-size PNGs. In the colouring page picker, locked pages used the full-size colouring PNG as their background image, inlined into the HTML. That came to about 1.3 MB on every first visit, to draw thumbnails in a dialog that was closed. They now use the small image, set when the picker opens, like the unlocked ones always did. Sticker thumbnails wait their turn. I tried loading="lazy" first. It didn’t help: Chrome fetched the images before the stylesheet that hides the dialogs had arrived, so as far as it knew they were visible. Sticker thumbnails and the media library’s YouTube thumbnail now use data-deferred-src. They load 3 seconds after the load event, or as soon as their dialog opens, whichever comes first. The service worker preload starts after load. The offline preload queue (about 2 MB of colouring pages and stickers) used to start while the page was still loading and compete with it. Now it starts after the load event. Same files, same offline result, no fighting for bandwidth. Analytics is async. Nothing waited for it, so nothing needed to block on it. Cache headers. /images/*: max-age=86400, stale-while-revalidate=604800. It had been max-age=0, so every image was re-checked on every visit. Versioned /js, /css and /addToHomescreen files are immutable for a year in production. Offline still has to work Offline support is a core feature, so “just don’t download it” was never an option. Some of the changes above put it at risk, and a couple of things turned up along the way: Safari plays video from byte ranges. Safari requests video with Range: bytes=.... Answer that with a full cached response and the video won’t play. The service worker now answers Range requests from its cache with a proper 206 Partial Content slice (lib/util/rangeResponse.ts, with unit tests). First-visit gap: on a first visit the service worker isn’t controlling the page yet, so dialog images only reached the offline cache on the second online visit. The page’s own dialog images and videos now go to the front of the offline preload queue on the first visit. I nearly downloaded my whole site, 12 times over. The service worker cached every <link href> it found in the page. The new SEO work had just added canonical and hreflang <link>s pointing at all 12 localized homepages. So every new visitor would have downloaded about 12 extra homepages, in languages they don’t speak, “for offline use”. I caught it before production. The service worker now skips rel=canonical and rel=alternate. Safari stopped the service worker mid-download. The old preload queue ran on timers after the request had been answered. Safari considers an idle service worker fair game, so it stopped it after the first few images. The page now sends images in batches of 10, and the service worker caches each batch before it replies. A page lock-up I’d never noticed. resizeDialog added a new “image loaded” listener every time the window resized. With lots of images loading at once, the listeners multiplied until the page locked up. It now attaches one listener per image, which, in hindsight, is how many it needed. Part 3: The blog Blog index cards used the full 1920 px screenshots as covers, up to 500 KB each, in a box about 200 px wide. Each card was a little billboard, shrunk down by the browser on every visit. Covers now go through next/image with sizes that match the actual card widths, so the browser gets a resized WebP. The first few cards get priority. The rest load lazily. The first sizes hint was too small at some widths and made covers blurry. It now matches the real card widths, up to about 630 px between 769 px and 1028 px wide. Post pages: The cover image gets fetchpriority="high", and images further down the post load lazily. Five images were recompressed in place, keeping the same filenames and dimensions. The PNGs came out about 4× smaller and the JPEGs about 40% smaller. I deleted a 1.1 MB cover.png that nothing referenced. All 12 translations of that post used cover.jpg. The PNG had just been sitting in public/ taking up space. Results on the slow 4G profile: /blog LCP went from 13.3 s to 1.8 s. A typical post went from 3.9 s to 1.7 s. The gallery didn’t get faster, on purpose. It got a 5-minute edge cache and a cached Firestore image count, which fixed its slow server responses. I decided not to change its 20 full-size PNG thumbnails, so its lab LCP barely moved (8.4 s to 8.6 s). That’s a choice, and the chart owns it. Part 4: Lighthouse homework After the speed work went live I ran Lighthouse on the production homepage (mobile) and cleaned up what it flagged. Performance stayed in the low 70s, so I have some more work to do, but it’s moved nicely in the right direction. Part 5: Telling the search engines Fixing the site is half the job. The other half is getting crawlers to come back and notice. Google Search Console: Resubmitted the www sitemap. Clicked “Validate fix” on “Duplicate without user-selected canonical” and on the redirect errors. Requested indexing for the main language homepages and the top blog posts. The quota is about 10 a day, so it’ll take a few days. Wrote down a baseline from the Performance report, so in 4 to 8 weeks I can tell whether any of this worked. Bing Webmaster Tools: Submitted all 204 sitemap URLs through URL Submission. The daily quota is 10,000, so no trickle-feeding needed. Bing’s index also feeds DuckDuckGo and several AI search tools, so it’s cheap extra reach. Most of Bing’s “SEO recommendations” pointed at old ?v= URLs and old titles. They’ll clear as Bing recrawls. What I’m not watching: the Lighthouse score. Google ranks on real-user Chrome data (the Chrome UX Report): a rolling 28-day window, judged at the 75th percentile. So the honest answer to “did it work?” is “ask me in a month”. How I kept from breaking things The app has hundreds of unit and integration tests, all of which still pass (even though they do take over 30 minutes to run). I also manually regression tested all the riskiest changes. Hopefully I don’t make things worse before they get better… Lessons, mostly at my own expense Read your own sitemap. Actually open it and click a URL. Mine had been quietly redirecting for who knows how long. <link rel="preload"> for the script that boots your app is the cheapest big win there is. Browsers fetch resources in the order they find them. If your app script is at the bottom of a 358 KB document full of images, it really is last in line. Check what your LCP element actually is before you try to make it faster. Mine was a “Contact support” link. GIF is an image format from 1987 that I was using as a video format. A real video codec beats it by an order of magnitude at the same quality. try/catch doesn’t catch promise rejections. I knew that. My code didn’t. Every <link> you add to <head> is something your service worker might decide to download. Speed scores are for diagnosis. Rankings come from real users. Fix what the lab finds, then wait for the field data. Epilogue You’re still here? Wow. Cool. After all this, I’m hoping that users notice nothing other than quicker app start times. I’m looking forward to keeping an eye on traffic and retention in the coming weeks. Wish me luck!
Interesting stuff here. This guy found that Marc Lou's ShipFast boilerplate dived in revenue from a height of $125k per month to $2,000.
Chris Oliver has announced the pricing of hosting on Hatchbox is going up. Hatchbox is a specialist hosting provider for web apps built with Ruby, Rails and Node.
Sharing a fun experiment I created recently: a top-down shooter game built with AI!
Why “just a GPT wrapper” is the best way to start a company — and the token reseller test that tells you if yours will survive.