Hello, world!
Hi! I’m Vadim, the solo founder here at SEOJuice, and I’m thrilled to finally kick off our blog.
I’ve started this blog to share my journey, the highs and lows of running a growing tech company, and some insights that might just help you along your own entrepreneurial path. It's been an exciting few months at SEOJuice. I've been hard at work over the weekend adding new feature requests from customers and I'm thrilled to share with you some of the updates that took place over the last 3 months.
I’m excited to tell you that we’ve now scaled SEOJuice to support over 1,500 websites. Yeah, that's right—1,500 websites have used our tool to juice up their SEO. With our monthly revenue hitting around $2,800, it's safe to say things are getting pretty serious around here.
But with great scaling comes great responsibility — support requests have been piling in, and our users are hungry for new features every day. It’s a good problem to have, but it sure keeps me on my toes. To keep up, I've ramped up our infrastructure to process websites faster than you can say "SEOJuice is awesome," which, admittedly, is a bit of a tongue-twister anyway.
I’ve also made a big move in our backend operations by shifting our payment processes to Paddle. This change means dealing with taxes is now less of a headache for both you and me, and trust me it's worth it.
There's a bunch of cool updates I’ve rolled out recently:
- API for Enterprise: We’re talking big league here; now enterprise customers can whip up reports with our private API.
- Performance Tweaks: Split tasks into different queues so they don’t trip over each other.
- Content Processing Improvements: Making sure the tool knows your content as well as you do, and a few more goodies that have made our system smarter and your life easier.
I’ve got a lot on the horizon, so stay tuned. Managing this project as a solo founder has been like running a marathon at the speed of a sprint, but knowing that it’s helping you all makes every crazy day worth it. So I'm happy you've given me a chance and are using the software that I've built.
If you’ve got ideas, issues, or just want to chat about the latest in SEO, my (virtual) door is always open.
Cheers,
Vadim
Discussion (4 comments)
Christopher Johnson, SEO Manager
Congrats on scaling to 1,500 websites and moving payments to Paddle — classic growing-SaaS growing pains with support overload. In my 8 years scaling B2B tools, introducing a lightweight in-app help widget, tiered SLAs, and RICE-based roadmap prioritization reduced tickets ~35% and helped ship revenue-impacting features faster. Happy to share templates or connect if that would help.
ContentCreator
1,500 sites and ~$2.8k MRR — legit milestone, Vadim. Automate support triage and add a public changelog to cut repetitive tickets and keep users informed. #SaaS
Digital Success
Huge congrats on the Paddle migration and scaling the infra — sounds like busy weekends! 🙌 Could you do a deep-dive/tutorial on the queueing/caching changes and how you triaged feature requests? I cut tickets ~30% by pairing Intercom with PostHog—happy to share configs 🔧
DigitalStrategy
1,500 sites and ~$2.8k MRR — impressive start, Vadim. Prioritize a public knowledge base + a simple feature-vote board to deflect support load and surface high-impact requests; set basic SLOs so infra scale doesn't surprise you. #SaaS #SEO
AnalyticsAddict
Totally agree on the KB + vote board — those two alone cut my support load by like 30% in month two. A few practical tweaks tho, fwiw:
- KB > just docs: make it searchable (Algolia or Notion + site search), track what people search for but don’t find, and add short GIFs for the top 5 “how-to” tasks. That single change dropped repeat questions for us.
- Feature-vote boards are noisy. IMO they skew toward loud users, not highest-impact requests. Tie votes to actual usage signals (e.g., number of customers affected, MRR impacted, or number of related support tickets) or set a review cadence where PMs validate requests before committing.
- SLOs: keep them tiny and actionable at first — error rate %, p95 latency for main endpoints, and an SLO for deploy failures. Pair them with an error budget and simple alerts (Slack + pager for budget burn). Saved us from a surprise load spike when a partner campaign went viral.
- Quick KB structure suggestion: Getting Started, Troubleshooting (search-first), API/Integrations, Billing, Release Notes. Tag docs with “problems solved” to improve discoverability.
Curious — how many support requests are you getting monthly right now, and do you have analytics on which KB pages are performing? That’ll change how aggressive you need to be on automation vs manual triage.
