Pratham Naik sent 80 LinkedIn DMs in a week: 12 replies, 8 users, 3 paying ($201 MRR)
- 3
- Paying customers
- $201
- First MRR
- Not disclosed
- Budget
- Not disclosed
- Duration
Instead of building an X audience or launching on Product Hunt, Pratham Naik DMed 80 agency owners from LinkedIn groups in one week, offering free access for honest feedback. 12 replied, 8 used BearConnect, and 3 paid within two weeks: his first $201 MRR.
01The problem
A new LinkedIn tool for agencies with no audience and no customers.
02The hypothesis
Agency owners already complaining in LinkedIn groups about managing client accounts will try a free tool, and some will pay.
03The experiment
He joined LinkedIn groups where agency owners complained about managing client accounts, and sent 80 DMs in one week offering free access in exchange for brutal feedback — not a pitch.
The conversations showed two things: nobody cared about the automation features; they cared about managing many LinkedIn accounts. And the flat $67/month price confused agencies with 10+ accounts, who assumed they'd pay $670.
He rewrote the pricing copy to “$67 per LinkedIn account you connect; 5+ accounts, $57 each”. Three of the eight beta users paid within two weeks.
04Results
| Metric | Result |
|---|---|
| Paying customers3 of 8 beta users, within two weeks | 3 |
| First MRR | $201 |
| DMs sentin one week | 80 |
| Replies | 12 |
| Used the product | 8 |
| Spend | Not disclosed |
“Not disclosed” means the source doesn't say. We never estimate or fill in missing numbers.
05What worked — and what didn't
What worked
- Finding prospects where they were already complaining about the problem (LinkedIn groups).
- Offering free access for honest feedback instead of pitching.
- Using the feedback to reposition (multi-account management, not automation) and to fix confusing pricing copy.
What didn't work
- The first customers kept cancelling after month two; he paused outreach for three weeks to talk to churned users and rebuild onboarding.
06Lessons
He later reached $2,400 MRR by returning to personal LinkedIn outreach once churn was fixed, then posting on Reddit and Indie Hackers. His rule: one channel at a time until it works.
“Nobody cared about our automation features.”
07Source & evidence
- View original
Originally shared on Indie Hackers · Feb 3, 2026
My exact distribution strategy I used to go from $0 to $2.4k MRR selling a LinkedIn automation tool
Public source. Extracted from publicly available content by the founder.
Want to try this?
Copy this experiment
A checklist built from what Pratham Naik actually did. Their numbers are a reference, not a promise.
- 1
Pick the channel and tactic
Cold DM — Free access for feedback, DMs to people complaining in LinkedIn groups.
- 2
Set a budget cap
Pratham Naik didn't say what it cost. Decide your cap before you start.
- 3
Set an end date
Pratham Naik didn't say how long it ran. Pick a review date before you start.
- 4
Copy what worked
From Pratham Naik's experience:
- ☐Finding prospects where they were already complaining about the problem (LinkedIn groups).
- ☐Offering free access for honest feedback instead of pitching.
- ☐Using the feedback to reposition (multi-account management, not automation) and to fix confusing pricing copy.
- 5
Avoid what didn't
Where it went wrong:
- ☐The first customers kept cancelling after month two; he paused outreach for three weeks to talk to churned users and rebuild onboarding.
- 6
Track the same numbers
So you can compare like for like:
- ☐Paying customers
- ☐First MRR
- ☐DMs sent
- ☐Replies
- ☐Used the product
- 7
Compare, then share what happened
Pratham Naik's headline result: 3 paying customers. Yours will differ — that's the point. Win or flop, the result is worth sharing.
Was this experiment useful?
Want the full playbook behind this?
Pratham Naik hasn't published a step-by-step playbook. If enough readers ask, we'll ask Pratham Naik for one.
Related experiments
- 200
- DMs sent
- 2
- replies
- 0
- users won
200 cold DMs, 2 replies — and she became the customer
Sofia
Sofia DM'd 200 potential users. Two replied: one wasn't interested; the other pitched her his own SaaS — a better pitch than hers — and she became a paying user of it.
- 183.6K
- impressions
- 337
- clicks (round 1, $300)
- $2K
- spent
Tony Dinh spent $2,052 on LinkedIn Ads for TypingMind Custom and stopped: the targeting couldn't reach his buyers
Tony Dinh · TypingMind Custom
Tony Dinh tested LinkedIn Ads for TypingMind Custom in three rounds: broad targeting, Lead Gen forms, then a Lead Gen form turned into an AI quiz. $2,052.03 bought 183,663 impressions and a handful of leads, none of whom had come back when he posted. He stopped the channel.
- 23K
- google impressions per day, after
- 52.7K
- clicks, whole chart
- 1.8%
- average click rate, whole chart
Tibo ran his SEO tool Outrank on SuperX: Google impressions went from about 2K a day to 23K
Tibo · SuperX
Tibo turned on Outrank — his own AI SEO tool — for SuperX in November 2025. It did the keyword research, wrote the articles, got contextual backlinks and built some free tools. By September 2026 daily Google impressions had gone from about 2K to 23K. Signups and revenue weren't shared.