SaaS unfold is the team behind marketing of many major $1 million ARR projects including Complily.
We work with SaaS between $10k to $50k MRR scale their revenue to reach $1-$5 million in yearly revenue.
Book a free consultation: https://t.co/SPgmRmjQxN
I have made $79 when walking, with AI.
Crazy, right?
1. Asked chatGPT to generate list of 100 people who might be interested in Screlio. People on YouTube with 10k subs or less in Pakistan.
2. I asked AI to find their emails from their websites, got 72 people whose emails were on their listed websites or somewhere online.
3. Sent emails through 3 gmails , highly personalised
4 . One person replied in like 10 minutes.
5. AI replied to conversation with little of input. And boom, the guy has just made a purchase.
AI is your best friend or worst enemy, choice is yours.
I am hoping to make more sales from those 100 emails.
Download and test screlio yourself for your videos at https://t.co/YTVLTg6bQc
Let AI shorten the distance from a tested idea to a working product.
Keep doing the work that makes the idea worth buying: understand the customer, choose a clear position, earn trust, and learn how to reach buyers.
Speed helps when you're building the right thing.
After a user signs up, watch them complete the task your SaaS promises to improve.
Where do they hesitate?
What do they misunderstand?
Do they get the result?
Watching someone use the product can reveal problems that a positive review misses.
Try this before your next SaaS build: talk to ten people who face the problem.
Ask about the last time it happened and the workaround they used.
Ten conversations won't prove demand. They can expose assumptions before those assumptions become features.
A customer leaving a spreadsheet gives up a system they already understand.
Your SaaS has to offer enough value to justify setup, learning, and moving their data.
'Better features' is a starting point. Explain why the switch is worth the effort.
Technical debt can hide behind a polished interface.
The app looks finished, but a small change breaks three other things.
When AI helps you ship code quickly, leave time to understand it, review it, and test the paths customers depend on.
A useful first SaaS product should let you test one valuable outcome.
Watch whether users reach it, return for it, and pay for it.
More features can wait when you still don't know whether the core job matters enough.
Customer acquisition deserves space on the calendar while you're building.
Who needs this?
Where do they look for help?
What would make them try it?
A finished app won't answer those questions for you. Start learning before launch.
@Riazhatvi Riaz, thanks for your recent n8n email-validation lesson. I appreciate the practical walkthrough of routing invalid emails away from Google Sheets. Which screen recorder do you use for your tutorials?
@muzafaralipro I appreciate your recent Python OOP lesson in Urdu. The student-record example makes the reason for using objects easy to follow. Which screen recorder do you use for your YouTube videos?
@Automationsguru Haider, thanks for sharing your recent A2P tutorial. I appreciate the annotated walkthrough of the setup in GoHighLevel. Which screen recorder do you use for your YouTube videos?
@IRizwantariq Rizwan, I appreciate the practical walkthrough in your Claude Code + GoHighLevel masterclass, especially turning the page details into a Claude prompt. Which screen recorder do you use for your tutorials?
@DevopsMolvi Thanks for sharing your recent AWS ELB tutorial and hands-on lab. I appreciate the practical AWS console walkthrough. Which screen recorder do you use to make your videos?
@waleedcodes Waleed, thanks for sharing your Node.js fundamentals session on YouTube. I appreciate the live, follow-along format. Which screen recorder do you use for your videos?
@fastcollege1 Zahid, thanks for sharing these Excel lessons in Urdu. The on-screen walkthrough of the shortcut menu and Backstage View is helpful. Which screen recorder do you use for your tutorials?
AI can help you summarize customer interviews. It cannot supply the customer evidence you never collected.
Bring it real conversations, examples, and objections. Otherwise, you're asking it to reason from your guesses.
When studying a fast SaaS launch, look at what existed before the first line of code.
Customer relationships?
An audience?
Years spent learning a workflow?
The build time gets the headline. The preparation may explain much more of the result.
My test for a SaaS homepage: can a visitor tell who it's for, what painful task it improves, and why it's worth changing their current process?
If the headline could fit ten unrelated products, it needs more customer detail.
A successful demo doesn't tell you whether customer data is safe.
Before people depend on your app, check access controls, test restoring backups, and separate development from production.
AI can help implement the safeguards. Verify that they work.
Before building the next SaaS feature, write down:
Which customer asked for it?
What problem were they trying to solve?
How will we know it helped?
If the answers are vague, another customer conversation may be more useful than another coding session.