u/Less-Bite

Getting those first 10 users is usually the hardest part of the solo founder journey. I spent weeks manually scrolling through subreddits and Twitter threads trying to find anyone who actually needed what I was building. Most people just talk about the problem in general terms, and by the time you find a real lead, you have already wasted hours of your workday.

I found that keyword alerts were pretty useless because they pull in every random mention without any context. I ended up building a tool called purplefree to solve this for myself. It uses semantic search and a vector database called Qdrant to identify actual buying intent. This approach filters out the noise so I only see people who are actually asking for a solution.

I am curious what specific hurdles you are running into right now. Is it the time it takes to filter through posts, the fear of sounding spammy when you reply, or just not knowing where your audience hangs out? I am trying to refine how the tool handles these interactions and would love to hear about the friction points you face daily.

I've spent months building out these features for purplefree that are supposed to make life easier by automating replies. On paper, it's the ultimate dream for a lazy marketer. But I looked at the database today and realized I'm essentially building a feature nobody actually wants to touch. Out of 331 total users, only 2 people have opted into auto-replies. That is a 0.6 percent adoption rate. It is embarrassing, but it is also a massive reality check.

Even linking a social account is a huge hurdle. Only 14 people have done it. Meanwhile, 181 users are happy to browse leads and 131 have set up product profiles. People are clearly using the tool to find opportunities, but as soon as the word automation or social linking comes up, they bolt. It makes sense because nobody wants to be the person whose AI accidentally insults a potential customer or gets their account banned for spamming.

I think I fell into the engineer trap of building what is technically cool instead of what is psychologically comfortable. Seeing that only 8.76 percent of users even want notifications tells me that most people want this to be a pull tool, not a push tool. They want to check it when they feel like it, not have an AI bot speaking for them in the background. I might have to rethink the entire automation roadmap if the trust gap is this wide.

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Key stats:

• 0.6 percent opt-in rate for auto-reply features
• Only 2 users out of 331 currently using AI automation
• 14 total users have linked a social account to the platform
• 8.76 percent notification opt-in rate across the user base
• 131 users have created product profiles but stopped before automation

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Current progress: 331 / 1000 users.

Previous post: Day 44 — Day 44 of sharing stats about my SaaS until I get 1000 users: My Reddit autopilot is failing 71 percent of the time and it is entirely my fault

I've been tinkering with different ways to pull Reddit data for lead signals without burning through API credits or getting my IP flagged every five minutes. Most people jump straight to PRAW, but if you're trying to monitor twenty different subreddits at once, the rate limits get annoying fast. I found that the most reliable method is actually using the .json endpoint trick combined with a randomized sleep jitter in a Python loop. It sounds basic, but it handles the headers much better than standard scraping tools.

I put together a script that fetches the latest posts, checks for intent using a simple semantic search approach, and pushes a notification to Discord. The key is to avoid keyword matching because people rarely use the exact words you think they will. I actually ended up building this logic into my own tool, purplefree, where I use Qdrant and vector embeddings to handle the matching instead of just looking for strings. It makes a huge difference when you're trying to find someone who has a specific problem but doesn't know your product exists yet.

If you're building your own version, make sure you're rotating your user-agent strings and using a backoff strategy. If you get a 429 error, don't just retry immediately or you'll get a longer ban. Wait at least 60 seconds and then double the wait time if it happens again. This keeps your automation running 24/7 without needing a massive proxy budget.

I spent tonight looking at the product profiles people are setting up in purplefree and there is a massive disconnect. When I ask what industry they are in, everyone says Digital Marketing or SaaS. But when I look at the actual keywords and pain points they are targeting, it is almost entirely low-level service work like web design or bookkeeping.

It is like we all want to call ourselves software founders because it sounds better, but 71.9 percent of the products in my system are just demo accounts where people are testing the waters with service-based ideas. Out of 580 total products, only 163 are actually registered and active. The rest are just founders throwing keywords at the wall to see if anyone is complaining about slow page speeds or bad UI.

I noticed 92 different people are all chasing the same small business owners audience. They say they are building a MarTech or Fintech startup, but then they search for leads who are stressed about tax season or have typos on their website. It is a weird ego gap between the high-level industry tag and the actual gritty work they are trying to find leads for. I am starting to think the niche isn't in the industry name, it is in the specific frustration you actually solve.

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Key stats:

• 71.9 percent of products are temporary demo profiles
• 92 unique products are all targeting the exact same small business owner audience
• 29 products are fighting over the lead generation keyword alone
• Only 163 products out of 580 have actually moved past the demo stage
• Digital Marketing is the top claimed industry with 17 products

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Current progress: 325 / 1000 users

Previous post: Day 41 — Day 41 of sharing stats about my SaaS until I get 1000 users: 711 subreddits are basically fortresses and it's changing how I build

I spent tonight looking at the product profiles people are setting up in purplefree and there is a massive disconnect. When I ask what industry they are in, everyone says Digital Marketing or SaaS. But when I look at the actual keywords and pain points they are targeting, it is almost entirely low-level service work like web design or bookkeeping.

It is like we all want to call ourselves software founders because it sounds better, but 71.9 percent of the products in my system are just demo accounts where people are testing the waters with service-based ideas. Out of 580 total products, only 163 are actually registered and active. The rest are just founders throwing keywords at the wall to see if anyone is complaining about slow page speeds or bad UI.

I noticed 92 different people are all chasing the same small business owners audience. They say they are building a MarTech or Fintech startup, but then they search for leads who are stressed about tax season or have typos on their website. It is a weird ego gap between the high-level industry tag and the actual gritty work they are trying to find leads for. I am starting to think the niche isn't in the industry name, it is in the specific frustration you actually solve.

---

Key stats:

• 71.9 percent of products are temporary demo profiles
• 92 unique products are all targeting the exact same small business owner audience
• 29 products are fighting over the lead generation keyword alone
• Only 163 products out of 580 have actually moved past the demo stage
• Digital Marketing is the top claimed industry with 17 products

---

Current progress: 325 / 1000 users

Previous post: Day 41 — Day 41 of sharing stats about my SaaS until I get 1000 users: 711 subreddits are basically fortresses and it's changing how I build

I've been digging deeper into the 'Lens' intelligence data from purplefree and honestly the numbers are depressing if you're trying to grow a product here. Out of 1101 subreddits my system analyzed, 711 are flagged as straight up hostile to marketers. We're talking about places where the mods are on a hair-trigger and the community tone is basically a middle finger to anyone suggesting a tool. The average risk score across the board is sitting at 73.2 which is way higher than I expected when I started this.

What's actually wild is the moderation strictness. 788 subs are either high or very high strictness. It's not just that they have rules. They have automated filters and human mods who spend their lives looking for even a whiff of self-promotion. I'm realizing that the old 'just go post your link' advice is a death sentence for your account. If you aren't in that tiny 11% bucket of 'friendly' subreddits like r/indiebiz or r/saasbuild, you're basically walking into a minefield without a map.

This data is forcing me to pivot the autopilot logic. Instead of just looking for keywords, I'm having to bake in these risk scores to stop my users from getting banned. It's better to not post at all than to post in a sub with a 90+ risk score. Seeing subs like r/test at the top of the 'friendly' list is a joke because there's zero real engagement there. The challenge is finding the overlap between 'people actually talk here' and 'mods won't kill me on sight'.

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Key stats:

• 711 subreddits classified as explicitly hostile to marketing efforts
• 78.0 percent of communities rated as high or very high risk for founders
• 73.2 average risk score across 1101 total analyzed subreddits
• 421 subreddits tagged with high moderation strictness
• Only 131 subreddits out of 1101 are actually marketer friendly

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Current progress: 324 / 1000 users.

Previous post: Day 40 — Day 40 of sharing stats about my SaaS until I get 1000 users: My Reddit autopilot is getting slaughtered and I think I'm done with submissions

I spent way too much time trying to find potential users on Reddit by hand. Most existing tools rely on basic keyword matching, but that creates a lot of noise. If you track a word like "email," you get thousands of posts that have nothing to do with someone looking for a new provider. I wanted to build a semantic pipeline that understands intent without spending a fortune on API credits.

I ended up using Qdrant for the vector database. I used multi-faceted named vectors to separate product descriptions from customer intents. The system uses cosine similarity to find matches based on the actual meaning of a post rather than just specific words. I built a three-stage pipeline where posts are embedded and then filtered through an LLM only if the similarity score hits a specific threshold. This keeps the costs manageable since I am not sending every single Reddit post to a language model.

One of the trickier parts was handling adaptive thresholds. Some subreddits are much noisier than others, so a flat similarity score doesn't work across the board. I had to implement a system that adjusts based on volume so it doesn't flood users with low-quality matches. I also added a feature called Lens that analyzes subreddit risk and moderation history to help with strategy. I would love to get some technical feedback on the matching logic or the UI if anyone has a few minutes to check it out.

Most solo founders waste a lot of time setting up keyword trackers for their niche. The problem is that keywords like marketing tool or lead gen usually just surface spam, blog posts, or other founders pitching their own stuff. If you want to find people who are actually ready to buy, you have to look for semantic intent rather than just specific words.

I spent months manually scrolling through subreddits trying to find people asking for recommendations. I realized that a user saying they are tired of their current setup has way more buying intent than someone just mentioning a product name. To solve this for myself, I built a system that uses vector embeddings to analyze the actual meaning behind a post. It uses a vector database called Qdrant to compare what a user is saying against specific buyer utterances. This is much more effective than old-school keyword matching because it understands the context of a problem.

Moving to this model changed how I handle outreach. Instead of getting fifty irrelevant notifications a day, I get a handful of leads where the person is actually expressing a pain point. If you are doing manual outreach, try searching for phrases that signal a struggle like is there a way to or does anyone else have trouble with instead of your product category. I eventually turned this workflow into a tool called purplefree to automate the discovery process. It has saved me dozens of hours of manual searching every week.

I've been watching my autopilot metrics for Lens and the results are pretty brutal. Right now I am sitting at a 21.7 percent success rate for posts. That is not just bad, it is basically a death sentence for an automation tool. I have 17 failed attempts this week alone and most of those are coming from subreddits like r/indiehackers where I haven't successfully landed a single post yet.

The data shows I am leaning way too hard on submissions over comments. I have 32 submissions scheduled versus 16 comments. Submissions are high risk because moderators and bots scan them instantly. If you look at r/soloentrepreneur or r/automation, the failure rate is double or triple the success rate. It is clear that the community walls are just too high for automated threads right now.

I am starting to think that comments are the only path forward. Comments feel less like an invasion and more like joining a conversation, which is what Reddit is supposed to be anyway. If I keep pushing these automated submissions, the tool is going to get banned everywhere before I even hit my user goal. I need to pivot the strategy to be 90 percent comments if I want that success rate to climb back into a respectable range.

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Key stats:

• 21.7 percent overall post success rate across all active strategies
• 17 failed post attempts compared to only 5 successful posts this week
• 32 submissions scheduled vs 16 comments currently in the pipeline
• 0 successful posts out of 6 attempts in r/indiehackers
• 25 posts still sitting in the scheduled queue waiting for execution

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Current progress: 321 / 1000 users

Previous post: Day 39 — Day 39 of sharing stats about my SaaS until I get 1000 users: My AI thinks these leads are perfect but my users completely disagree

I've been watching my autopilot metrics for Lens and the results are pretty brutal. Right now I am sitting at a 21.7 percent success rate for posts. That is not just bad, it is basically a death sentence for an automation tool. I have 17 failed attempts this week alone and most of those are coming from subreddits like r/indiehackers where I haven't successfully landed a single post yet.

The data shows I am leaning way too hard on submissions over comments. I have 32 submissions scheduled versus 16 comments. Submissions are high risk because moderators and bots scan them instantly. If you look at r/soloentrepreneur or r/automation, the failure rate is double or triple the success rate. It is clear that the community walls are just too high for automated threads right now.

I am starting to think that comments are the only path forward. Comments feel less like an invasion and more like joining a conversation, which is what Reddit is supposed to be anyway. If I keep pushing these automated submissions, the tool is going to get banned everywhere before I even hit my user goal. I need to pivot the strategy to be 90 percent comments if I want that success rate to climb back into a respectable range.

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Key stats:

• 21.7 percent overall post success rate across all active strategies
• 17 failed post attempts compared to only 5 successful posts this week
• 32 submissions scheduled vs 16 comments currently in the pipeline
• 0 successful posts out of 6 attempts in r/indiehackers
• 25 posts still sitting in the scheduled queue waiting for execution

---

Current progress: 321 / 1000 users

Previous post: Day 39 — Day 39 of sharing stats about my SaaS until I get 1000 users: My AI thinks these leads are perfect but my users completely disagree

I have been staring at my matching algorithm for two hours trying to figure out why my math is so different from reality. My system generated 13958 matches recently and most of them have these massive similarity scores. I am talking about an average score over 1.0, which should basically mean the lead is a mirror image of what the user asked for. I was feeling pretty good about it until I looked at the actual feedback coming back from the people using purplefree.

Only about 26.74% of the feedback I get is positive. That is a brutal gap. I have over 10,000 matches sitting in the 0.7 bucket and hardly anyone is giving them a thumbs up. It is a wake-up call that a high mathematical similarity score does not mean a damn thing if the human on the other end doesn't find it valuable. My ML brain thinks a post is a 'match' because the embeddings align, but the user just sees noise.

I am starting to realize that 'buying intent' is way more subjective than I treated it. Someone might be asking for a tool that does exactly what purplefree does, but if they sound like they are just venting or if they are in a specific niche my users don't like, the lead is dead on arrival. I have only gotten feedback on 0.62% of these matches so far, but the signal is clear. I need to stop obsessing over the similarity math and start figuring out how to weight for actual human 'helpfulness'.

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Key stats:

• 13,958 total matches generated by the current algorithm
• 1.0095 average similarity score across all matches
• 26.74 percent positive feedback rate from users
• 10,194 matches sitting in the 0.7 similarity bucket
• 0.62 percent feedback coverage across the total match set

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Current progress: 315 / 1000 users.

Previous post: Day 38 — Day 38 of sharing stats about my SaaS until I get 1000 users: 122 people signed up and then did absolutely nothing

I was looking at my onboarding funnel for purplefree today and it's a bit of a reality check. Out of 305 total users, I have 122 people who hit the dashboard and never even reached the first step of the process. They just signed up and vanished into the void. It’s a huge chunk of my user base essentially just staring at a blank screen and deciding it’s not worth the effort to move forward.

The real friction starts when I ask them to actually define what they're building. Only 123 users have actually created a product profile in the app. That’s a massive drop-off from the 305 who took the time to create an account. I think I’ve made the initial setup too heavy. People want to see the value immediately, but right now I'm making them work for it before I show them any leads.

Even more telling is the social side of things. Only 12 people have linked a social account. That’s less than 4 percent. I knew people were protective of their accounts, but seeing that number next to 171 people who are active enough to view leads is wild. It tells me they are definitely finding value in the data, they just don't trust the tool or the process enough yet to let it act on their behalf. I need to figure out how to bridge that trust gap without forcing the integration too early.

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Key stats:

• 122 users have completed zero onboarding steps
• 123 total users managed to create a product profile
• 171 users are actively viewing leads in their dashboard
• 12 total users have linked a social account to the platform
• 305 total users currently registered on the platform

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305 / 1000 users. Long way to go and a lot of onboarding flow to fix.

Previous post: Day 37 — Day 37 of sharing stats about my SaaS until I get 1000 users: Why I stopped posting on Wednesday and started watching Monday afternoons instead

I have been staring at the engagement heatmap for purplefree and it is pretty clear that Reddit is a ghost town at times I thought would be gold. I used to think mid-week was the sweet spot for finding people with high buying intent. Looking at the data from the last week, Wednesday was a total wash. Engagement barely cracked 115 even at its peak around 3pm, while Monday at 1pm was seeing 182 active interactions. It is weird how much energy drops off in the middle of the week.

Saturday surprised me too. I usually ignore the weekends for B2B stuff, but 5pm on Saturday hit 175. It is almost as busy as the Monday afternoon rush. It makes me think that people are doing their deep research and asking for tool recommendations when they finally have a minute to breathe on the weekend, rather than during the actual work week when they are just trying to survive their inbox.

Tuesday is another strange one. It has this really consistent hum around lunch time with 142 interactions at noon, but then it just falls off a cliff by 9pm. If you are not hitting that 12pm to 5pm window on Monday or Tuesday, you are basically shouting into an empty room. I am probably going to tweak the autopilot schedules for my users because right now, some of these early morning slots like Thursday at 1am with only 38 interactions are just a waste of a good post.

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Key stats:

• 182 peak engagement interactions on Monday at 1pm
• 175 surprise engagement spike on Saturday at 5pm
• 38 lowest recorded engagement point on Thursday at 1am
• 115 maximum engagement reached on Wednesday at 3pm

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Current progress: 290 / 1000 total users.

Previous post: Day 36 — Day 36 of sharing stats about my SaaS until I get 1000 users: Why I ingested 10,000 posts just to get 42 people to talk to each other

I have been staring at the engagement heatmap for purplefree and it is pretty clear that Reddit is a ghost town at times I thought would be gold. I used to think mid-week was the sweet spot for finding people with high buying intent. Looking at the data from the last week, Wednesday was a total wash. Engagement barely cracked 115 even at its peak around 3pm, while Monday at 1pm was seeing 182 active interactions. It is weird how much energy drops off in the middle of the week.

Saturday surprised me too. I usually ignore the weekends for B2B stuff, but 5pm on Saturday hit 175. It is almost as busy as the Monday afternoon rush. It makes me think that people are doing their deep research and asking for tool recommendations when they finally have a minute to breathe on the weekend, rather than during the actual work week when they are just trying to survive their inbox.

Tuesday is another strange one. It has this really consistent hum around lunch time with 142 interactions at noon, but then it just falls off a cliff by 9pm. If you are not hitting that 12pm to 5pm window on Monday or Tuesday, you are basically shouting into an empty room. I am probably going to tweak the autopilot schedules for my users because right now, some of these early morning slots like Thursday at 1am with only 38 interactions are just a waste of a good post.

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Key stats:

• 182 peak engagement interactions on Monday at 1pm
• 175 surprise engagement spike on Saturday at 5pm
• 38 lowest recorded engagement point on Thursday at 1am
• 115 maximum engagement reached on Wednesday at 3pm

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Current progress: 290 / 1000 total users.

Previous post: Day 36 — Day 36 of sharing stats about my SaaS until I get 1000 users: Why I ingested 10,000 posts just to get 42 people to talk to each other

I was looking at my lead funnel today and the drop-off is actually hilarious. My engine chewed through 10,349 posts across Reddit and X. Every single one of those was classified as a potential lead. That resulted in 14,667 matches being created because some posts fit multiple products.

Then you look at the bottom of the bucket. Only 164 actions were taken in the app, and a tiny 42 were marked as actual follow-throughs. This used to worry me, but now I think it just highlights how much noise you have to filter out to find one person actually worth talking to.

If you tried to do this manually, you would lose your mind. Sifting through ten thousand posts to find forty-two meaningful conversations is a full-time job. It's the efficiency gap that usually kills social selling before it even starts. Most founders just give up after the first hundred posts because they haven't found a 'hit' yet.

I’m starting to realize that the value isn't in the high volume. It's in the fact that the system ignores the 10,300 posts that don't matter so you don't have to. The follow-through rate looks small, but 42 real conversations is actually a lot of work if they are the right ones.

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Key stats:

• 10,349 total posts ingested and classified as leads
• 14,667 total matches generated for users
• 1.58 percent rate of in-app actions taken from matches
• 42 total recorded follow-throughs at the bottom of the funnel

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Current progress: 280 / 1000 users

Previous post: Day 35 — Day 35 of sharing stats about my SaaS until I get 1000 users: I analyzed 988 subreddits for marketing risk and most of them are total landmines

I’ve been spending a lot of time lately digging into the risk scores my tool calculates for different communities. I wanted to see exactly how many subreddits actually tolerate marketing versus the ones that will ban you on sight. The numbers are honestly pretty depressing if you're trying to grow a business here. Out of 988 subreddits we scanned, 647 are explicitly hostile. That is almost two-thirds of the platform where even a helpful mention of your own product is basically a death sentence for your account.

The average risk score across the board is sitting at 73.7 out of 100. When I look at the distribution, 589 subreddits fall into that very high risk bucket. That is more than half. It explains why so many founders feel like they are walking on eggshells. You spend an hour writing a thoughtful response and it gets nuked in seconds because the moderation strictness is set to high or very high for 720 of these communities.

I did find a few bright spots though. There are about 114 subreddits that are actually friendly to marketers. Most of them are small, but a few like r/indiebiz or r/saasbuild have decent numbers. It's just a massive reality check. Most people think they can just spray and pray across Reddit, but the data shows you're literally fighting a losing battle in 79 percent of the places you'd think to post. I'm starting to think the only way to survive here is to find those 41 very low risk sandboxes and stay there.

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Key stats:

• 73.7 average risk score across 988 analyzed subreddits
• 647 subreddits classified as explicitly hostile to marketers
• 79.0 percent of communities rated as high or very high risk
• 720 subreddits have high or very high moderation strictness
• Only 41 subreddits fall into the very low risk category

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Currently at 277 / 1000 users. Still a long way to go.

Previous post: Day 34 — Day 34 of sharing stats about my SaaS until I get 1000 users: My demo users are looking for things my real users don't actually build

I’ve been spending a lot of time lately digging into the risk scores my tool calculates for different communities. I wanted to see exactly how many subreddits actually tolerate marketing versus the ones that will ban you on sight. The numbers are honestly pretty depressing if you're trying to grow a business here. Out of 988 subreddits we scanned, 647 are explicitly hostile. That is almost two-thirds of the platform where even a helpful mention of your own product is basically a death sentence for your account.

The average risk score across the board is sitting at 73.7 out of 100. When I look at the distribution, 589 subreddits fall into that very high risk bucket. That is more than half. It explains why so many founders feel like they are walking on eggshells. You spend an hour writing a thoughtful response and it gets nuked in seconds because the moderation strictness is set to high or very high for 720 of these communities.

I did find a few bright spots though. There are about 114 subreddits that are actually friendly to marketers. Most of them are small, but a few like r/indiebiz or r/saasbuild have decent numbers. It's just a massive reality check. Most people think they can just spray and pray across Reddit, but the data shows you're literally fighting a losing battle in 79 percent of the places you'd think to post. I'm starting to think the only way to survive here is to find those 41 very low risk sandboxes and stay there.

---

Key stats:

• 73.7 average risk score across 988 analyzed subreddits
• 647 subreddits classified as explicitly hostile to marketers
• 79.0 percent of communities rated as high or very high risk
• 720 subreddits have high or very high moderation strictness
• Only 41 subreddits fall into the very low risk category

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Currently at 277 / 1000 users. Still a long way to go.

Previous post: Day 34 — Day 34 of sharing stats about my SaaS until I get 1000 users: My demo users are looking for things my real users don't actually build

I've been staring at the industry breakdown for purplefree and I think the tool is having a bit of an identity crisis. When people hit the landing page and try the demo, they're searching for leads in Digital Marketing and Real Estate. Digital marketing is the biggest slice of the demo pie at around 11 percent, with Real Estate right behind it. It makes sense because those are high-churn, high-velocity industries where everyone is desperate for new clients.

But then I look at who actually sticks around to register a product. The numbers flip. The people who actually sign up and create a profile are almost entirely in Software Development and SaaS. Only 2 people from the Digital Marketing crowd actually registered a product compared to the dozens who played with the demo. It looks like the 'lookers' are marketers, but the 'doers' are devs building their own tools.

This is a weird spot to be in. I'm attracting one crowd with the marketing copy but retaining a completely different one. Even looking at the keywords, 'Lead Generation' and 'Web Design' are the most searched, but the actual pain points being solved are things like 'Poor mobile responsiveness' or 'Low conversion rates.' It's like people come in looking for a quick sales list but the ones who find value are the ones using it to find specific technical problems to fix for others.

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Key stats:

• 68.29 percent of all products created stay in the demo phase without a full registration
• Digital Marketing makes up 11 percent of demo searches but only 1.2 percent of registered products
• Software Development is the top registered industry with 13 products currently active
• 80 unique products are targeting the Small Business Owner audience
• 351 total demo products created compared to 163 registered products

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Current progress: 274 / 1000 users.

Previous post: Day 33 — Day 33 of sharing stats about my SaaS until I get 1000 users: I'm watching 89% of my active users vanish at the finish line

I've been staring at my conversion funnel all morning and it's pretty brutal. People are actually getting through the hard parts of the app. They sign up, they set up their product, and they get matches. I have 149 people right now who have active leads waiting for them, but only 16 of them have actually clicked an action button in the app.

That is a massive 89.3% drop-off right at the moment of truth. At first I thought the app was just broken or the leads sucked. But then I remembered how I use purplefree myself. I often find a lead, read the post, and then just open Reddit or X in a new tab to reply manually instead of using my internal tracking buttons. The 'action' and 'follow-through' steps are totally optional, so my analytics make it look like a graveyard even if people are actually getting value.

It's a weird spot to be in as a founder. Do I force people to use my buttons just so my data looks better, or do I just accept that my most important metric might always be a lie? I have 611 demo submissions that turned into 267 signups, so the top of the funnel is working. But seeing only 11 people 'follow through' on paper when 149 have leads feels like I'm flying blind on whether the product is actually solving their problem or just giving them a nice list to look at before they leave.

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Key stats:

• 89.3 percent drop-off between users getting matches and taking an in-app action
• 267 total signed up users from 611 initial demo submissions
• 149 users have successfully generated lead matches for their products
• Only 11 users have officially marked a lead as 'followed through' in the dashboard
• 56.3 percent of people who try the demo never actually create an account

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Current progress: 267 / 1000 users

Previous post: Day 32 — Day 32 of sharing stats about my SaaS until I get 1000 users: My reddit autopilot is hitting a wall and I think I know why

I've spent a lot of time trying to automate lead discovery on here, and the biggest hurdle is always the noise. If you set up a basic script to watch for keywords like "recommendation" or "how do I," your Discord or Slack just gets flooded with irrelevant junk. Most people start with PRAW and some basic regex, but you end up spending more time filtering notifications than actually talking to potential users.

The fix I found was moving away from keywords and into semantic intent. Instead of looking for specific strings, I started embedding posts and running them against buyer utterances in a vector database like Qdrant. Using cosine similarity lets you find posts where the actual meaning matches what you're looking for. This stops the notifications from firing when someone mentions a term in a completely irrelevant context.

I eventually turned this workflow into a tool called purplefree to handle the heavy lifting. It uses a multi-stage pipeline where it does the semantic search first and then uses an LLM to verify the match before it ever sends a notification. If you are building your own version, focus on the vector search layer rather than just adding more filters to your keyword lists. It takes more work to set up the embeddings, but the signal quality is significantly better than anything you can get with standard rule-based automation.