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Small businesses miss 62% of incoming calls.
Not 6%. Sixty-two.
Every missed call is a customer who either goes to voicemail (85% never call back) or dials a competitor (62% do).
The average annual cost of that leak: approximately $126,000.
Most owners think their problem is marketing. It's usually the phone.
What's your business's answer rate right now? Most people are unaware, and that's the first problem.
The network for creativity
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Connect with clients, get discovered, and run your business 100% commission-free
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I had a startup reach out last week. They wanted a design system from scratch. All their existing work refactored and redesigned. Probably 4-5 months worth of work part-time.
I quoted them $45,000 because they wanted it done in less than 2 months.
They said that price was fine and they'd get back to me today.
They decided to hire a designer full-time at $80K a year. I think they will fire them after 2 months and get it done for a few grand.
Oh man!
Just delivered a finance automation for a dental clinic in Texas.
Their leads were growing fast and manual tracking was becoming impossible.
Now they just send a WhatsApp message, voice or text, and everything logs automatically.
"I spent $10 on coffee" → logged.
"I earned $1,000 developing a website" → logged.
Income source, amount, category, all recorded instantly into their spreadsheet.
No manual entry. No missed transactions. Just message and move on.
This is what automation looks like for a real client with a real problem 💪.
Comment FINANCE BOT for a free demo. 👇
aiautomationfinanceautomationmakeautomationAI Agent DevelopmentAI AutomationBusiness Workflow AutomationGoogle SheetsMakeTelegram bots
FINANCE BOT
Built this one for an e-commerce customer behavior project - 18,000+ customers, segmented using RFM (Recency, Frequency, Monetary) analysis.
The interesting part wasn't the segmentation itself, it was what it revealed: nearly 22% of customers were "at risk" of churning, and most businesses wouldn't know that until those customers had already stopped buying.
This is the kind of insight that's usually sitting in your order data already, it just needs the right lens. Happy to take a look at your numbers if you're curious what's hiding in yours.
Tools used: Power BI, SQL, Python (Pandas, Scikit-learn for clustering)
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