u/ickmk27

I've been running a small SaaS for appointment-based businesses for about 6 months. It sends automated SMS reminders, handles confirmations, and tracks no-show rates.

Currently priced at $29/month. Thinking about moving to $49/month based on the value it delivers (average salon saves $800-1,200/month in recovered appointments).

My questions for r/entrepreneur:

1. At what price point does this feel like a no-brainer vs "I should think about it"?
2. Would you pay more for a dedicated phone number vs shared pool?
3. What integrations would make this actually worth enterprise pricing?

I've mostly been selling through cold outreach to salon owners — conversion is decent but slow. Any advice from people who've grown B2B SaaS targeting local businesses?

Happy to share more details about what's working and what isn't!

Spent 3 months doing customer discovery calls before writing a line of code. Here's the actual data:

Top problems mentioned (unprompted):

1. No-shows / last-minute cancellations (37/40 mentioned this)
2. Chasing payments (28/40)
3. Rebooking after appointments (24/40)
4. Tracking which stylists are performing (18/40)
5. Social media content (15/40)

The interesting part: when I asked "which one costs you the most money?", 35/40 said no-shows — but only 8/40 had done the math. The rest were guessing it was around $200-300/month when it was usually $1,000-1,500.

What they were already using: Most had tried at least one booking software. 70% were unhappy with it. Main complaints: too complex, took too long to learn, clients didn't like the booking interface.

What they actually wanted: Something that works with their existing booking tool. Not a replacement — an add-on that handles the reminder/confirmation layer.

This shaped everything about how I built the product.

Anyone else here doing B2B SaaS targeting non-tech business owners? Happy to share more of what I learned.

Posting the honest story of building NoReject AI — a tool that checks your app metadata for likely rejection reasons before you submit to Apple/Google.

Why I built it: personal pain. My apps kept getting rejected for dumb, preventable reasons. I reverse-engineered the pattern and productized it.

The technical challenge: Apple's guidelines are vague by design. "We reserve the right to reject" means almost anything could get rejected. Building a useful scanner means not just checking against explicit rules, but predicting reviewer judgment.

My approach: I collected 500+ real rejection notices, categorized them by guideline section, and built pattern-matching rules. Not perfect, but it catches 70-80% of what I'd have caught doing a manual review.

Business side:

• Distribution: organic from indie dev communities
• Pricing: $19/month or $149/year
• Conversion: 6% from free scan to paid
• Churn: lower than expected (2.8%/month) — developers come back for every submission

What I'd do differently: Ship faster. I spent 3 months on the AI when rule-based checks would have caught 80% of the value. Perfect is the enemy of shipped.

Current focus: Google Play is growing faster than App Store. Their auto-rejection system is more aggressive and less documented — bigger pain point.

Happy to answer anything!

Posting the honest story of building NoReject AI — a tool that checks your app metadata for likely rejection reasons before you submit to Apple/Google.

Why I built it: personal pain. My apps kept getting rejected for dumb, preventable reasons. I reverse-engineered the pattern and productized it.

The technical challenge: Apple's guidelines are vague by design. "We reserve the right to reject" means almost anything could get rejected. Building a useful scanner means not just checking against explicit rules, but predicting reviewer judgment.

My approach: I collected 500+ real rejection notices, categorized them by guideline section, and built pattern-matching rules. Not perfect, but it catches 70-80% of what I'd have caught doing a manual review.

Business side:

• Distribution: organic from indie dev communities
• Pricing: $19/month or $149/year
• Conversion: 6% from free scan to paid
• Churn: lower than expected (2.8%/month) — developers come back for every submission

What I'd do differently: Ship faster. I spent 3 months on the AI when rule-based checks would have caught 80% of the value. Perfect is the enemy of shipped.

Current focus: Google Play is growing faster than App Store. Their auto-rejection system is more aggressive and less documented — bigger pain point.

Happy to answer anything!