Have I missed out on the joke?

99% of this sub, posts & comments reads like LinkedIn AI bot slop.

I'm a freelance product strategist and for the longest time my client acquisition strategy was basically cold email and pray so like I'd spend 2 hours every morning writing personalized intros, building sequences, sending follow ups and honestly the whole thing felt like a part time job on top of my actual job and the conversion was brutal. Maybe 2 to 3 calls booked per month from hundreds of emails sent

About 6 months ago I just stopped doing that Completely killed the cold outreach and started putting that same 2 hours into LinkedIn instead

I started doing 3 to 4 posts a week about product strategy, growth frameworks, teardowns of real products I found interesting, it was nothing revolutionary just sharing what I actually know from doing this work for years

The posts were doing okay, they were getting decent engagement, growing slowly, people seemed to appreciate the content, but I had this nagging feeling that I was posting into a void because I had no idea who was actually reading my stuff, I always thought like a head of Product at a funded startup could be liking my posts every week and I'd never know because I wasn't looking, I was just hoping that eventually someone would slide into my DMs and say hey can you help us

That's not a strategy that's wishful thinking

So I set up a workflow where every person who engages with my content gets automatically checked against my ideal client profile, so like If someone who fits the criteria likes or comments I get an alert with their full context like Job title, company, size, what they engaged with, The whole picture shows up in real time

My process now is dead simple, I post in the morning and throughout the day alerts come in when qualified people engage, I spend maybe 30 seconds checking their profile to make sure it's a real fit...

Then I send a short message that references the specific post they interacted with and opens a conversation around the topic

It doesn't feel like outreach at all because it genuinely isn't, I'm not interrupting someone's day with a pitch they didn't ask for, I'm starting a conversation with someone who already demonstrated they care about the thing I do and most people respond because the message is actually relevant to something on their mind

14 discovery calls last month, Closed 4 of them......

That's more revenue than I generated from 6 months of cold email and it takes me maybe 30 minutes a day instead of 2 hours, the entire dynamic shifts when you stop pushing messages at strangers and start pulling in people who already engage with your thinking

Quick context: spent the last few months building Molverine — a web-based detective game where you solve crimes by examining evidence and interrogating AI-driven suspects (GPT under the hood). Launched 14 days ago.

Numbers so far:

- 0 paying users

- YouTube Shorts: 1 video hit 1.5k views with 21.5% retention. 4 others stuck under 150.

- Instagram Reels: <200 views per post, 0 followers

- Direct traffic to the site: basically nothing

What I've tried:

- Short-form video (true-crime-style hooks, mystery teasers)

- Landing page with a playable free case

- A couple of organic posts in adjacent communities — flat

Where I'm stuck:

- The one Shorts hit suggests the top-of-funnel formula works, but it didn't convert. Don't know if it's the landing page, the offer, the audience mismatch, or all three.

- Can't decide whether to (a) double down on content/audience building, (b) do a Product Hunt-style launch, or (c) go niche — true crime subreddits, mystery Discord servers, AI hobbyist communities.

- It's B2C and impulse-buy-friendly, so I'm not sure the "10 cold DMs a day" SaaS playbook even applies.

The ask: what's the ONE thing you'd do right now to get the first 5 paying users? Not a checklist — the single move that worked for you when you were stuck at zero.

Happy to share the link in comments if anyone wants to look at the landing/product.

How’s your journey going?

I want to know the challenges you are facing now and what are the ways you are solving them. What then do you see the medium term future of your startup, and do you see it making it to much later stages?

What would be your advice to those yet to start?

I'll be straight with you, I was never the guy who dreamed of starting a company since childhood. I was the guy who was exceptionally good at building things for other people and honestly for a long time that felt like enough

I did my MBA from IIM Calcutta which is where I first started thinking seriously about products and markets and why certain things work and certain things don't. That way of thinking never really left me

At Booking(dot)com I got promoted from Senior Product Owner to Director in 9 months, that same journey typically takes 3 to 5 years, I built the world's largest restaurant reservation platform over 100,000 venues globally, the numbers were good and the results were real and by every external metric I was doing great

But I kept seeing something that nobody around me seemed to want to talk about, I went from Booking(dot)com to Foodics to Yoco to Everli to Blacklane and the same thing was happening everywhere

Content teams were sitting on hours of recorded footage, interviews panels keynotes podcasts events and barely using any of it, not because they didn't want to but because nobody had figured out how to make that footage usable without burning out an editor

Video editors were making decisions they were never supposed to make, which clip goes out, what moment represents the brand and what soundbite connects with the audience,to be very honest, that's not an editing decision, that's a strategy decision and it was landing on the wrong desk every single time…..

Marketing teams were spending serious money on video production and then posting one highlight reel and calling it done, meanwhile 90% of the footage that could have been powering their content for weeks just sat on a hard drive somewhere

I saw this also in startups, I saw it in scaleups and I saw it in enterprise teams with actual budgets, the problem wasn't resources it wasn't talent it was that nobody had built the right infrastructure for video to actually work the way modern content teams need it to

I won't pretend the path here was clean but before Montage I founded Floost and raised money built it out and walked away having learned that being right and being early are two completely different things and the market doesn't care which one you are, then came Kitnebaje same energy different circumstances same lesson

After that I went deep on podcasting and video tools and honestly that one hurt the most because we had real customers and the revenue potential was there but when I looked at the market clearly I knew we were too late for that specific angle and walking away from something that actually has momentum is a different kind of hard than walking away from something that never worked

Most people would have kept going because the numbers looked okay on paper but I've been on the wrong side of timing enough times to know that conviction alone doesn't save you

So here's what I'm building……

After everything I saw across all those companies across all those teams I'm launching Montage,the core idea is simple,the person who understands your audience and your message should be the one deciding what clips get made, not the editor, the editor should be executing not deciding

And Montage puts that control back where it belongs, you write a brief describing what you're looking for the AI surfaces the best moments from your footage ranked by how well they match, you edit at the word level like a Google doc smart reframing handles vertical formats, automatically 4K files up to 20GB export straight to Premiere Final Cut or social

It's built for content teams and producers who post consistently and actually care whether what they put out performs, the people backing this include founders of Fiverr Wix and Daily(dot)co and AI leaders from Amazon Meta and YouTube, people who understand what video infrastructure looks like when it actually works

And now the part what I learned

Timing beats being right every single time, your failed attempts aren't detours they're what qualifies you for the thing you're actually supposed to build, and that pattern you keep seeing that nobody else seems to notice that's not you overthinking it that's your edge

I'm going to keep documenting this whole journey here also we are going to launch it on product hunt on 23rd….It’ll be everything the wins the hard days the decisions that don't have clean answers

If you're building something or thinking about making the leap follow along, happy to answer anything below

Been chewing on this lately and figured I'd ask.

There's a handful of things I added to our setup this year that I'd hate to operate without, so I'll go first with 3 of mine.

1. Something that listens to our sales and support calls, pulls themes across them weekly or bi-weekly, and tells me the top patterns of what prospects and customers are asking about. I used to spend Fridays scrolling transcripts, now I get a digest and I'm 80% of the way to the synthesis I used to do by hand.
2. An open-source thing that does what Clay does but markdown-configured, runs from the CLI, so the per-step pricing you'd hit on Zapier doesn't enter the picture. our enrichment costs dropped to basically zero because we run it as part of a nightly job rather than paying per row.
3. A workflow tool that glues the rest of the stack together. new leads come in from the form, get routed by condition (size of company, country, source), fire the right Slack alerts, and write back to our CRM, all in one shot. It replaced 4 separate zaps that kept choking on the conditional logic, which dropped our automation bill to almost zero.

What's running in your background that you'd never tear out? let's make this thread the go-to reference for must-have automations.

Been lurking here for a while and finally shipped something worth sharing.

A few months ago I got obsessed with a simple question: how accurately can -AI determine the location of a random photo? Not just "probably Europe" — actual coordinates.

Turns out it's a genuinely hard problem. The naive approach (just ask Claude/GPT to look at the image) gets you maybe 40-50% accuracy on urban photos and falls apart completely on rural ones.

So i went deeper. The pipeline I ended up with:

1. EXIF extraction first — if GPS metadata exists, done instantly, zero AI needed. Covers ~20% of mobile photos.
2. Visual feature extraction via a fast/cheap model — pulls out specific searchable elements (architecture style, visible text, infrastructure details) with a specificity score. Low-score generic queries get dropped before they waste API calls.
3. Google Vision Web Detection + Landmark Detection in parallel — if the image exists somewhere on the web or contains a known landmark, this catches it.
4. Web search on the high-specificity queries — feeds real-world results back into the final reasoning step.
5. Final reasoning with a stronger model that gets the image + all aggregated context. Contradiction detection built in — if web results point to 3+ different locations it flags it and tells the model to weight visual analysis higher.

Total cost per analysis: under €0.02. Most of the accuracy gains came from steps 2-4, not from using a more expensive model.

The interesting failure cases:

- Photos with visible text are almost always nailed correctly

- Rural/forest photos are still genuinely hard regardless of pipeline

- The AI confidently wrong cases dropped significantly once I added

the web search layer

Built it as a SaaS with multi-prediction output (up to 4 ranked hypotheses with confidence %), radius estimate, and a 3D map view.

Still early but the technical side was interesting enough to share.

Happy to go deep on any part of the pipeline if useful.

I underestimated how fast “small tweaks” turn expensive once animation and motion graphics are involved.
every revision sounds harmless until suddenly the project timeline doubles and the original message gets buried somewhere along the way.

Too cheap to be true? Yes. And the catch is not what you think. Before we touched any AI, we spent time just organising (the boring stuff).

The Situation

Property documents scattered across WhatsApp. Brochures in Telegram. Floor plans buried somewhere in Google Drive. Project updates in email threads nobody reads anymore.

The Steps

1. Getting everything into Drive properly.
2. Name folders by project.
3. Files named consistently.
4. Choosing one place the whole team agrees on.
5. Google Sheet: Projects as rows. Status, unit count, availability — all in columns. Simple stuff.

Once the data was clean, we didn’t need AI to count anything. A formula does that. It’s free, (almost) never wrong.

An Automation Script runs every night, scans the Drive folders, and writes a flat index file — project name, document name, link. Thirty lines of text.

That’s it. That’s the “database.”Then we deployed the AI. It reads the Sheet for numbers. It reads the index file for documents. It handles the conversation.

$12/month. Works for 1,000 users.

Not because the AI is smart.

Because we did the boring work first.

I follow a developer who builds his SaaS in public on YouTube. 300K+ subscribers watching him code, ship, and share revenue.

I looked at his product from a security perspective. Not as a test — as someone who builds in the same space and noticed patterns I keep seeing.

Three things were sitting in production that nobody noticed:

1. The framework auto-mounted an upload route that required zero login. Anyone could push files to the cloud storage bucket. The feature wasn't even being used — the framework set it up by default.

2. Rate limiting was per-IP only. A pool of rotating IPs pushed 564 requests through in one hour without triggering a single alert. The analytics dashboard was showing inflated numbers to product owners.

3. A login callback route accepted any input as a parameter. When it hit something unexpected, it returned a server error with internal details in the logs. Free information for anyone poking around.

The app worked. Users were paying. Everything looked fine on the surface.

The founder acknowledged everything, fixed all three, and published the full breakdown publicly. Transparent, professional, no drama.

Three things I took away from this:

Speed creates blind spots. AI builds fast and builds features. It doesn't check what the framework left behind.

"It works" is not the same as "it's safe." The most dangerous state for a SaaS is when everything looks perfect in the demo but there are open doors in production.

The first security pass is boring. It's checking routes, testing limits, and reading configs. No fancy tools needed. Two hours.

If you're shipping something built with AI and haven't done this check — start with your framework's route list. That's where most of the surprises live.

Started this about 3 months ago. My dad runs a dental clinic and his usual ad guy was charging him $1500 for a single Instagram video. I'd been messing with AI video tools and figured I'd try to make him something for free.

The first one was rough but it got more bookings than the $1500 video had. So I made him a couple more. Then his friend who owns a med spa asked if I'd do one for her. Then it kind of kept going.

Where I am now:

• About to cross $3k MRR this month
• 7 ongoing clients on monthly retainers, one in trial
• Pricing: $600/mo for 5 ads, $1000/mo for 10 ads. One-off ads are $250-300 but I push everyone to monthly.
• Costs are maybe $50-80/mo in tools, the rest is mine
• Honestly I think I should be at $5-6k by now and I'm leaving money on the table by being slow on outreach. Sales is the bottleneck, not production.

I'll get this out of the way because Reddit will bring it up otherwise. Yes, some of these ads look obviously AI. That's actually fine for the businesses I work with. Their previous ads were stock footage of a different dental office in a different country. AI video that's specifically about their location, their service, their offer outperforms generic stock every time, even when you can tell it's AI. I'm not pretending it's the next Spielberg. It's a $30 ad that books appointments.

What I've learned:

The hard part is sales, not production. I can make an ad in like 90 minutes. Finding a business that will say yes takes way longer. I cold-message local businesses I find on Google Maps. About 1 in 15 of those replies, maybe 1 in 30 closes.

Lead with a free spec ad. I make the ad first, then send it to them. "Hey, made this for your business, here's the link." Conversion on this is way higher than pitching the service abstractly. Most of my closed clients said yes because they already had the ad in their hand.

Go for businesses that already advertise. Don't try to convince a small business to start running paid ads. Find the ones who are already running mediocre ads and offer to replace them. The pitch writes itself.

Tools I use:

• Google Maps for finding local businesses and grabbing images of their storefront, food, interior, whatever I need as a reference
• For the ads themselves I use bonzi studio because it has all the video models in one place and lets me try different ones for the same scene. Was on Runway before that. Honestly any of them work, the tool isn't the moat.
• Capcut for final edits and captions

That's the whole stack. People assume there's a complicated workflow behind it but it's three tools.

Cons / what I'd do differently:

• I undercharged for the first month. Should have been at $600/mo from the start.
• I didn't get contracts signed for the first few clients. One ghosted after I delivered. Now everything is invoiced upfront.
• I tried scaling by hiring a friend to help. Quality dropped. Went back to doing it myself.
• I'm still bad at outbound volume. If I sent 50 cold messages a day instead of 10 I'd probably be at $6k MRR by now. Working on it.

Not passive income. It's a service business and you have to do client work. But the production speed of AI lets one person handle way more clients than a traditional video freelancer, which is where the margin lives.

Happy to answer specifics on outreach scripts, pricing, the ad style itself, anything.

Started this in September. Launched it this morning.

There were months in between where I had nothing to show, where the idea kept shifting, where I'd build something for three weeks and scrap it. The version that's live today isn't even the 3rd version of what I was trying to make. It's the literal 35th build.

VTapr is an AI physique scanner. You take 3 photos (front, side, back), the AI gives you a score out of 100, breaks down which muscles are developed vs which are lagging, and builds a workout plan around your weak points. I'm 21, self taught coder, no co-founder, no funding, no team. Just me.

Stack for anyone curious: Expo + React Native + TypeScript, Supabase for backend, Claude API for the physique analysis, RevenueCat for subscriptions. (P.S also had the help of Cursor which saved me haha)

The build that's live right now is build 35. I submitted to Apple on April 13. They rejected it the first time because I hadn't attached the in-app purchase products to the binary review (that's a separate submission in App Store Connect, I had no idea). I also hadn't set up a demo account with Pro pre-enabled, so the reviewer couldn't actually test the paid features. Fixed both, resubmitted, approved.

Today, within hours of launch, real users hit three bugs:

- Auth session wouldn't persist when the app got backgrounded

- No way to take a photo with the camera, only pick from library

- Pre-upgrade scans showed 0 for every muscle in the breakdown for users who upgraded after taking them

Fixed all three tonight. 1.0.1 is already submitted to Apple for review. Genuinely surreal to fix bugs that are affecting people who are USING something I made.

I haven't slept properly in months. There were stretches in February where I genuinely thought I was building something nobody would want. The Cursor Hackathon at IE in March was the first time I built something AI-related and it clicked, that's actually where the seed for VTapr came from. Then late March I started building this starting completely over, 5-8 hours a day every day, while still working full time.

Distribution feels harder than building, and building was already the hardest thing I've done.

I just wanted to actually mark this somewhere because most days the work felt invisible and today there are real people with accounts and scans in a database and I can see them in Supabase and it's the strangest feeling. Eight months ago this was a Notion doc.

If anyone wants to talk about the App Store submission flow, RevenueCat setup, building solo with AI tools, or just wants to commiserate about how long it takes to ship something that looks simple from the outside, I'm here for the next few hours and will reply to everything.

I am the founder of an open source delivery platform. The frontend is on GitHub, the backend is proprietary, and I sell one-time source code licenses rather than a subscription. I have sold around 500 of those over the years and get about 40 new signups a week.

The one-time model has upsides. No churn, no monthly bill to justify, and people own what they buy. But revenue is lumpy with no recurring base, so every month starts close to zero. The one recurring piece I have is backend customisation, where clients come back for custom work after buying the license.

My main concern with switching to SaaS is the math. I could charge maybe $100 to $200 a month. But hosting runs around $100 of that, and then marketing and everything else eats into the rest. Even if a client stays a full year, that is $1,200 before costs, and once you strip those out it does not leave much. With a one-time license I get a real chunk up front. I am not convinced the recurring version actually nets more.

For anyone who has run both or switched between them: did going recurring actually grow the business, or just trade one problem for another?

it needs to be an area i can get a solo place without having a full-time job so i can focus 100% on getting to revenue for the next 6-12 months.

i tried northern kentucky - that may be good and i'm not opposed to it. it snows, but i've adapted to it and kinda like it.

i tried georgia, atlanta area - it's okay, but i don't like their law enforcement system aggressively trying to reach quotas and targeting people

i tried nyc - no car needed, which removes tons of hassle. but of course, it's expensive af housing wise.

tell me, where are your gold mines to focus without having to get a job? (so no sf)

obviously the best place would be "with family so you pay nothing".

and obviously, "it depends on your savings". this is true. let's say i can acquire 50k total for this with the help of a loan. and there is no time cap - the only criteria is get to revenue.

so this just happened, one of my employees in germany sent me a photo of a letter from the Finanzamt this morning saying he personally owes 38k in unpaid social security contributions going back over a year.

I panicked and called our EOR, who ghosted me for 2 hours before sending a one-line email saying their partner network in germany was experiencing operational delays.

i did some digging because what the hell…

turns out the EOR we've been paying every month is a cyprus-based holding company that subcontracts to a german GmbH for employment, except that german GmbH filed bankruptcy back in February, which means our money has been getting pocketed somewhere in the chain ever since.

The EOR obviously knew the whole time because they kept billing us anyway.

We bit the bullet and paid the 38k out of pocket for our employee yesterday because what else are you going to do, leave him on the hook for someone elses fraud.

we fired the EOR the same day and we’ll be moving everyone over to a more established EOR like Deel or Workmotion who at least own their own GmbH and can be looked up in the Bundesanzeiger.

Anyway, if you're hiring through an EOR check that your employer of record exists as a real legal entity in the country (should be the bare minimum but here we are).

Running growth for my previous startup completely changed how I look at “signals” on the internet. In the beginning we were doing what most early stage startups do.

Cold emails going out every day, founder content on linkedin, outbound lists, scraping tools, lead databases, engagement tracking, website analytics, trying to create momentum from everywhere possible because honestly at that stage survival itself feels like growth.

And for a while the numbers looked good. More impressions. More profile visits. More email opens. More replies. More engagement on founder posts.

So naturally I assumed we were moving in the right direction. But after a few months I noticed something that kept bothering me. A lot of the people interacting with us looked interested but very few of them were actually converting into meaningful conversations. Then one day while reviewing campaign data I noticed something strange.

Some people had opened multiple emails over weeks without replying once. The same people were also viewing founder content consistently on linkedin. A few of them had publicly posted about the exact problem we solved. Some were comparing alternatives openly in comments and reddit threads and a few had visited our pricing page multiple times. 

Individually these actions looked insignificant but together they formed something much more valuable. Marketers now call them “intent” . That was the first time I realized how broken most growth workflows actually are. Because almost every tool we were using was optimized around visibility instead of buying behavior.

• apollo gave us databases
• clay enriched data
• phantombuster automated actions
• apify scraped information
• linkedin analytics showed engagement

But none of them naturally connected the most important layer: Who is actually showing intent across the internet before becoming a customer?

So I started manually tracking patterns, who repeatedly engaged, who matched ICP, who interacted across channels, who publicly talked about the pain point, who silently kept showing up over time and honestly it completely changed how we approached growth afterwards. Because I realized the internet is full of noise pretending to look like traction.

Real buying intent is much quieter.

It usually hides inside repeated behavior patterns that most founders ignore because they are too busy looking at surface level metrics. And weirdly enough, some of our best conversations later came from people who never once filled out a lead form. It’s 2026 if you’re still just scraping data you’re already 10 years late.

If you use any free or paid AI tools to help you with your small business, where have they been most useful? Have you got any hacks where AI has actually saved you time, money or headache?

And where hasn’t it helped you? What do you still absolutely need to do yourself?

Been scanning Amazon US BBQ bestseller lists over the weekend. Thought some of you selling on FBA might find this useful.

Here’s what stood out.

1. Wireless meat thermometer (ThermoPro)

- 9,400+ monthly sales, BSR up 22% last 7 days

- Main hooks: 4 probes, long-range wireless (~305m max / ~152m min)

- $50 for 4 probes, $41 for 2 probes

Tenergy has a 6-probe version at ~$60. But it's not waterproof.

There’s a premium option (waterproof + dishwasher-safe + battery/USB + app logging) at $113 ($199 MSRP).

Yet the bestseller has none of those premium features. Buyers seem to care about core function and price. Doubling the cost for waterproof + app? Probably too niche for the mass market.

2. BBQ gloves (Grill Armor Gloves)

- 5,000+ monthly sales, but BSR growth +91% – hotter momentum than the thermometer

- EN407 certified, up to 500°F, aramid outer, silicone on both sides (so no left/right), machine washable, hidden loop

- Wrist-extended version, 3 sizes, 5 colors (bright = visible on a crowded grill)

- ~$30–32

Why the spike? My guess:

- People prioritize cooking results over safety. Most buy gloves after getting burned or realizing the risk.

- Gloves wear out (heat, damage, aging) → repeat purchases. Thermometers are often a one-time household buy.

3. 2-in-1 grill brush (GRILLART)

- 4,400+ monthly sales, BSR up +185% (fastest growth of the three)

- Double-sided stainless steel wire – spiral for tough residue, straight for detail

- 46cm handle, detachable into two pieces for storage (screw assembly)

- $14 ($20 MSRP)

Downside: complaints about bristle wear/breakage. Seller added a note to use a soft cloth for final cleaning. Smart CYA move.

Key takeaway for anyone selling BBQ gear

Function + value > premium extras for the volume segment. Thermometer buyers are price-sensitive on "nice-to-haves." Glove buyers convert after a close call. Brush buyers love storage hacks but worry about bristles.

Anyone else seeing similar patterns in other outdoor/cooking niches?

Hello,

Where do I seek assistance with adding a new user type to our platform in order to add subscription revenue?

Who should I talk to?

To summarize, currently we have an internet platform that allows users to post content. The original plan was to scale up and monetize via advertising, but we're too niche for that, so we need to figure out how to make subscriptions work.

I’m starting a small agency around one specific problem I keep noticing with appointment-based businesses:

They get interest from Instagram, but a lot of those people never make it to the booking stage.

The niche I’m looking at first is medspas, aesthetic clinics, injectors, and laser clinics in Canada and Australia.

My thinking is that these businesses are usually active on Instagram. They post treatment videos, before-and-afters, promos, educational content, and they often get comments like:

“How much?”
“Where are you located?”
“How do I book?”
“Can you DM me?”
“Do you have availability this week?”

But in a lot of cases, the next step still seems very manual. Someone on the team has to reply, answer basic questions, send the booking link, follow up if the person disappears, and then remember to keep track of the lead.

The service I’m testing is a DM-to-booking system for these businesses.

Not more leads. More like:

Let’s make sure the people already showing interest don’t go cold before they book.

The first version would be a simple one-treatment flow. For example, Botox, fillers, laser hair removal, body contouring, or a skin consultation.

The flow would look something like this:

Someone comments or DMs about a treatment.
They get an instant reply.
The system asks what they’re interested in.
It answers a few common questions.
It collects their name, phone, and email.
It sends them to book a consultation.
If they don’t book, it follows up.
The business gets the lead organized in a CRM.

I’m thinking of pricing the first few clients at around $500 setup + $500/month, then increasing once I have proof and case studies.

My 90-day plan is:

Build 2 demo flows.
Create a list of 500 to 700 qualified prospects.
Focus on Canada and Australia first because the US feels more saturated.
Send 40 to 70 personalized outreaches per week.
Use short audits instead of pitching immediately.
Try to close 3 to 5 clients.

The biggest things I’m thinking through are:

Instagram cold DMs often go to message requests.
A lot of clinics may already have agencies.
Some businesses may not want bots talking to potential clients.
I need to position this as appointment recovery, not just automation.
I’m based outside the client’s country, so trust/proof matters even more.

I’m curious what you’d change before I start outreach.

Would you narrow the niche further?
Would you start with Canada/Australia or just go straight for the US?
Is $500 setup + $500/month reasonable for a first offer, or would you structure it differently?