I launched SubPulse with 0 users. Here's what happened after 90 days

Hey Signum, thanks for reading! The retention struggle is definitely the hardest part of building SaaS.

Your tool sounds incredibly timely—AI Search Optimization is basically the new SEO, so knowing where competitors show up in LLM answers is a very strong value proposition. Regarding your retention challenge: maybe pushing automated 'competitor shift' email alerts (e.g., 'Competitor X just overtook you in ChatGPT prompts') could create that recurring habit without forcing them to log in every day?

I'll definitely check out your post and drop some feedback there. Best of luck with the experiment!

Thanks Muzzamil! It is definitely tempting to just keep coding new features when growth feels slow, but forcing myself to stop and look at activation data (like setting up uninstall feedback) is proving to be way more valuable. Appreciate the support and thanks for reading!

The distinction between “installed” and “reached a useful moment” is really interesting.

I’m building a tool that shows brands how visible they are in AI-generated answers compared with their competitors. It gives them a simple way to see whether AI is mentioning their brand or competitors more often.

I think the same activation question applies here too — getting someone to use the tool once is very different from them seeing enough useful insight to actually care about it.

Really interesting point about measuring the useful moment instead of just downloads or signups. I am documenting my experiment so you can check out my post on indie hackers if you have time: )

This is arguably the most valuable feedback I’ve received so far. You completely nailed the structural problem: the 'Aha!' moment (the notification actually saving them money) might be too far away from the installation moment.

If their first renewal is 25 days out, I'm relying on them keeping the extension installed based purely on a promise, and features like Dark Mode or CSV exports won't bridge that gap.

The uninstall URL is a brilliant, low-friction way to get qualitative data on this. I’ll set up a simple redirect today with a one-click survey to find out if the churn is happening before or after adding their first subscription.

I've been looking too closely at the CWS impressions and completely missed that my real bottleneck right now is 'Time to Value'. Thanks for the reality check, seriously.

The point about learning from the people who already tried the product really resonates.

I’m building a tool that shows brands how visible they are in AI-generated answers compared with their competitors. It helps make something that’s otherwise difficult to see — whether AI is mentioning your brand or consistently choosing your competitors.

I’m also finding that the interesting part isn’t just getting someone to try the tool, but understanding whether the result gives them enough useful insight to actually care about it.

Really like the advice on going deeper into one channel instead of spreading attention across too many. I am documenting my experiment so you can check out my post here on indie hackers if you have time :)

You are completely right, and it's funny because another commenter just pointed out the exact same thing about the uninstall URL. It was a huge blind spot for me. I'm implementing chrome.runtime.setUninstallURL in my next update today to catch those exit intents.

Your point about reverse-engineering competitor paywalls is brilliant. I've been trying to 'guess' my Pro features instead of looking at what the market has already validated. The local-privacy angle is my acquisition hook, but you are right: I need to see if privacy-focused users are willing to pay for insights, or if I need to pivot the Pro tier towards purely financial features (like advanced forecasting).

Regarding the channels: guilty as charged. I've been splitting my limited time between TikTok, YouTube Shorts, and Indie Hackers itself. I need to look closely at my CWS analytics, identify the exact source of those 34 active users, and just double down on that one platform for the next 30 days.

Thanks for taking the time to write this, it's incredibly actionable advice.

Thanks a lot, Victor! Let me know if you have any questions about the journey.

Thanks! I really like the distinction between “adding subscriptions” and actually reaching the first useful moment.

The idea of cohorting users based on whether they received a renewal reminder within their first 30 days is especially interesting. I hadn't thought about activation that way, but it makes a lot of sense for SubPulse.

I'm going to start tracking that and compare it with 30-day retention. If the difference is significant, it would give me a much clearer direction than just adding more features.

I also agree about the privacy angle. I initially treated “no account, no bank connection, no server storing your subscription list” mostly as an architectural choice, but I probably haven't pushed that positioning enough in the distribution.

Thanks for the thoughtful feedback — this gives me a couple of things I can actually test.

That's exactly what I'm trying to figure out right now, but I haven't tracked those signals separately yet.

My initial assumption was that renewal reminders would probably be the main trigger, while things like spending reports or price changes might create more occasional returns.

But with such a small user base, I don't want to treat that assumption as fact. I'm going to start tracking which event happens before each return and compare reminders, price changes, and spending reports.

The timing point is especially interesting to me — the feature might not be what creates the habit, but when the value actually reaches the user. Thanks for the idea!

Thanks! I really like the idea of keeping the feature set stable for a bit and focusing on the funnel instead. I haven't instrumented those exact events yet, so this is actually a good push for me to do it. I also agree that asking users why they came back (or why they didn't) could be much more useful than guessing from feature requests. With such a small user base, I think those conversations could teach me a lot.

That's actually something I don't know yet — and I think I need to start measuring it properly. My guess going in was that renewal reminders would be the main reason people come back, while spending and upcoming payments might drive more occasional usage. But I don't want to assume that's true. I'm going to start tracking those behaviors separately and see what actually correlates with users coming back.