u/Curious_Club8404

Hi everyone, I'm a Product Engineer with ~10 year of exp., this year I decided to start my own SaaS, here are the main things I'd do differently moving forward:

1. Research the niche and competitors before launch.

I launched with AdaptlyPost, a social media scheduling tool, the most cliche tool imaginable, with competition that is impossible to win, outbid, or outrank. How did I make $670 with that? Open Claw hype, I created a skill at the right time, and it brought hundreds of signups, and decent sales + translating my page to different languages, I rank for some of the keywords internationally

2. Don't focus on hype

I launched ClawOneClick as an instance deployer for OpenClaw in February, as everything was about OpenClaw at the time - result. A ton of devops work, hardening of the instances, and an absolute nightmare in customer support talking to non tech-savvy people, why their chat doesn't do what they want. And guess what - very high churn, the hype is over - people move on.

3. Don't waste your time on X

X is so saturated with founders promoting their product, and fake launches, the frank truth - nobody cares about your product, and nobody wants to hear your story until you've actually achieved anything, posting about product updates - won't get you any audience, and 100% not the customers.

4. Focus on making money, not optimizing the costs.

I re-wrote multiple parts of my websites many times. $50 bill on Vercel -> move to cloudflare. $2 a day bill on Cloudflare -> re-write marketing pages to static SSG. My biggest cost right now is my backend, already was thinking of moving from Fly to VPS, but decided that enough, swallow the cost for convenience, not worth it, spend money to make money.

5.Focus on SEO and organic first, not the Ads.

My initial instinct was Ads first, SEO for me was this thing about title and the meta tags right? No, it's much more than that. Keywords, SERPs. I jumped straight into ads, and immediately realized, ROI is not there, I don't know my ICP, I don't know my LTV, I'm guessing what keywords to target, instead of relying on data.

How do I apply what I learned?

ClawOneClick - is a lost cause for me, it sits currently on ~$130 MRR, it's obviously only downhill from here, just maintaining it. AdaptlyPost - against all odds is slowly growing by around ~$50/m, and is right now at ~$300 MRR, very low churn, and very low customer support effort, I don't see how I can grow it organically, probably, so maintaining the project Flowsery - my newest project, Google Analytics Alternative. I picked a freemium model, so right now no revenue, but ~30 signups. Very competitive niche, however I was able to find plenty of keywords, during my SERPs analysis.

The latest project is a child of my mistakes #1 and #3, it was born as a saving cost for the analytics, but I'm actively working and improving it, since I use it every single day.

Been thinking about this for months while building my own tool.

GA4, Plausible, Fathom, even PostHog. All of them open with pageviews and unique visitors. That's a 2010 metric. For any SaaS, ecommerce, or content site with revenue, pageviews are at best a leading indicator and at worst pure noise.

What I actually want to know is which channel generates paying customers, what the path from anonymous visit to revenue looks like, and which content pieces correlate with conversion, not just traffic.

I ended up building Flowsery (my analytics tool) specifically because Stripe attribution was missing from every privacy-first option I tried. Plausible has goals but no revenue context. Fathom is similar. PostHog has it, but the cookie consent stack adds about 80kb to your page, and the dashboard is overkill if you're a solo founder.

Curious what others here use. Is anyone actually happy with their revenue attribution setup? What did you stitch together to get a real picture, GA4 plus Stripe in a spreadsheet, a custom dashboard, something else?

Hi everyone, I'm a Product Engineer with ~10 year of exp., this year I decided to start my own SaaS, here are the main things I'd do differently moving forward:

1. Research the niche and competitors before launch.

I launched with AdaptlyPost, a social media scheduling tool, the most cliche tool imaginable, with competition that is impossible to win, outbid, or outrank. How did I make $670 with that? Open Claw hype, I created a skill at the right time, and it brought hundreds of signups, and decent sales + translating my page to different languages, I rank for some of the keywords internationally

2. Don't focus on hype

I launched ClawOneClick as an instance deployer for OpenClaw in February, as everything was about OpenClaw at the time - result. A ton of devops work, hardening of the instances, and an absolute nightmare in customer support talking to non tech-savvy people, why their chat doesn't do what they want. And guess what - very high churn, the hype is over - people move on.

3. Don't waste your time on X

X is so saturated with founders promoting their product, and fake launches, the frank truth - nobody cares about your product, and nobody wants to hear your story until you've actually achieved anything, posting about product updates - won't get you any audience, and 100% not the customers.

4. Focus on making money, not optimizing the costs.

I re-wrote multiple parts of my websites many times. $50 bill on Vercel -> move to cloudflare. $2 a day bill on Cloudflare -> re-write marketing pages to static SSG. My biggest cost right now is my backend, already was thinking of moving from Fly to VPS, but decided that enough, swallow the cost for convenience, not worth it, spend money to make money.

5.Focus on SEO and organic first, not the Ads.

My initial instinct was Ads first, SEO for me was this thing about title and the meta tags right? No, it's much more than that. Keywords, SERPs. I jumped straight into ads, and immediately realized, ROI is not there, I don't know my ICP, I don't know my LTV, I'm guessing what keywords to target, instead of relying on data.

How do I apply what I learned?

ClawOneClick - is a lost cause for me, it sits currently on ~$130 MRR, it's obviously only downhill from here, just maintaining it. AdaptlyPost - against all odds is slowly growing by around ~$50/m, and is right now at ~$300 MRR, very low churn, and very low customer support effort, I don't see how I can grow it organically, probably, so maintaining the project Flowsery - my newest project, Google Analytics Alternative. I picked a freemium model, so right now no revenue, but ~30 signups. Very competitive niche, however I was able to find plenty of keywords, during my SERPs analysis.

The latest project is a child of my mistakes #1 and #3, it was born as a saving cost for the analytics, but I'm actively working and improving it, since I use it every single day.

Why I've chosen datafast in the first place? I have a background in Product Engineering, my company uses enterprise grade tools: Sentry, Datadog, PostHog etc, so when I launched my SaaS I went for those solutions automatically.

PostHog was a no-brainer, 100% free for millions of events, the rest I had to research, since the costs for a tiny saas were incompatible with reality.

However I found PostHog frustratingly complicated, It's a no-brainer for a Product Team, that loves analyzing every user behavior, but I wanted to have something simple that can be shown on one dashboard, since I found myself asking Claude to run MCP on my database, instead of building and checking the dashboards in PostHog.

I've seen tons of screenshots on X, from other founders, all of them use datafast, so I went with it, I also added plausible, however plausible didn't have a user breakdown, so I dropped it after the free trial.

A couple of months later I started noticing huge increase of events on my website, without much conversions, so I would need to move to a $39/m plan, would be one of the most expensive part of my setup, so I've decided to build a simple version for myself.

While working on it I found an uncomfortable truth. my traffic increased because 70% of it were bots from datacenter IPs, I ran traffic from my website through arcjet - and the real number of users dropped from >350 to ~150.

That's how I learned that DataFast has 0 bot filtering in place, and 60% of your bill are literal bots... After I finished Flowsery, I compared the results, here is the immediate day of the rollout:

https://preview.redd.it/jz8jn6lzh22h1.png?width=3570&format=png&auto=webp&s=93bdeb1c31432f38501ec813ada048c84de970c9

Result: Reported values dropped by 50%, with additional behavior bot filtering by over 60%.

https://preview.redd.it/5e2ij122i22h1.png?width=3566&format=png&auto=webp&s=92aa62dbee9a0107d23e804b2b2e7151092dfd21

What surprises me the most - was how easy it was to implement: eliminate broken user-agents and devices (10000px wide screens), known bots, obvious data-center IPs, and that's it, some advanced behavior includes fast bounces, lack of scrolls, and some other metrics, those might be false-positives, but always nice to have.

Why I've chosen datafast in the first place? I have a background in Product Engineering, my company uses enterprise grade tools: Sentry, Datadog, PostHog etc, so when I launched my SaaS I went for those solutions automatically.

PostHog was a no-brainer, 100% free for millions of events, the rest I had to research, since the costs for a tiny saas were incompatible with reality.

However I found PostHog frustratingly complicated, It's a no-brainer for a Product Team, that loves analyzing every user behavior, but I wanted to have something simple that can be shown on one dashboard, since I found myself asking Claude to run MCP on my database, instead of building and checking the dashboards in PostHog.

I've seen tons of screenshots on X, from other founders, all of them use datafast, so I went with it, I also added plausible, however plausible didn't have a user breakdown, so I dropped it after the free trial.

A couple of months later I started noticing huge increase of events on my website, without much conversions, so I would need to move to a $39/m plan, would be one of the most expensive part of my setup, so I've decided to build a simple version for myself.

While working on it I found an uncomfortable truth. my traffic increased because 70% of it were bots from datacenter IPs, I ran traffic from my website through arcjet - and the real number of users dropped from >350 to ~150.

That's how I learned that DataFast has 0 bot filtering in place, and 60% of your bill are literal bots... After I finished Flowsery, I compared the results, here is the immediate day of the rollout:

https://preview.redd.it/a4s0yywx7a1h1.png?width=3692&format=png&auto=webp&s=0cd0c826b9886181b62677e14c827559bb2f5d5c

Result: Reported values dropped by 50%, with additional behavior bot filtering by over 60%.

https://preview.redd.it/6ywkrs408a1h1.png?width=3668&format=png&auto=webp&s=52a42e5781effd730663e5fc39a2a0be3e4b7edf

What surprises me the most - was how easy it was to implement: eliminate broken user-agents and devices (10000px wide screens), known bots, obvious data-center IPs, and that's it, some advanced behavior includes fast bounces, lack of scrolls, and some other metrics, those might be false-positives, but always nice to have.

Hey all, I built my first SaaS this year, and one of my biggest concerns was the churn and disputes, I ran e-commerce in 2022-2023, and it was miserable, I did around ~$500k in revenue during that period and decided to drop that idea, since I was extremely burned out, by constant issues with payment processors, disputes, returns, refunds, and overall customer support.

When I was launching my SaaS, I was scared about this repeating, that people will be buying the subscription, bombarding me with the messages, that they did not intend on buying, they want a refund, disputes, and that people are going to be churning like crazy.

Turned out it's not the case, at all, people who forget to cancel - don't even bother contacting me, just cancel the sub the day of the charge (I send reminder of charge 2 days before the charge), there are multiple customers who schedule a couple of posts a week, and still pay for the services (for the context my product is AdaptlyPost).

It might be early to say, but my effective churn rate right now is only 11%.

I guess the takeaway is, don't be scared to launch, don't overthink.

[ Removed by Reddit on account of violating the content policy. ]

[ Removed by Reddit on account of violating the content policy. ]

Why I've chosen datafast in the first place? I have a background in Product Engineering, my company uses enterprise grade tools: Sentry, Datadog, PostHog etc, so when I launched my SaaS I went for those solutions automatically.

PostHog was a no-brainer, 100% free for millions of events, the rest I had to research, since the costs for a tiny saas were incompatible with reality.

However I found PostHog frustratingly complicated, It's a no-brainer for a Product Team, that loves analyzing every user behavior, but I wanted to have something simple that can be shown on one dashboard, since I found myself asking Claude to run MCP on my database, instead of building and checking the dashboards in PostHog.

I've seen tons of screenshots on X, from other founders, all of them use datafast, so I went with it, I also added plausible, however plausible didn't have a user breakdown, so I dropped it after the free trial.

A couple of months later I started noticing huge increase of events on my website, without much conversions, so I would need to move to a $39/m plan, would be one of the most expensive part of my setup, so I've decided to build a simple version for myself.

While working on it I found an uncomfortable truth. my traffic increased because 70% of it were bots from datacenter IPs, I ran traffic from my website through arcjet - and the real number of users dropped from >350 to ~150.

That's how I learned that DataFast has 0 bot filtering in place, and 60% of your bill are literal bots... After I finished Flowsery, I compared the results, here is the immediate day of the rollout:

Result: Reported values dropped by 50%, with additional behavior bot filtering by over 60%.

What surprises me the most - was how easy it was to implement: eliminate broken user-agents and devices (10000px wide screens), known bots, obvious data-center IPs, and that's it, some advanced behavior includes fast bounces, lack of scrolls, and some other metrics, those might be false-positives, but always nice to have.