How We Use Outboundy
Case Study
How we used Outboundy to find our first 1,000 paying customers
We built a cold email platform. Then we used it to grow our own business. These are the real numbers, the exact strategy, and everything we learned along the way.
310K
Emails sent
11.2%
Reply rate
3,600
Free trials
1,000
Paying customers
The context
We have the same problem as our customers
We sell cold email software. Our customers use Outboundy to find new business. So we asked ourselves the obvious question: could we use our own platform to grow Outboundy?
Over 8 months, we ran Outboundy's AI campaigns targeting sales leaders, agency founders, and startup CEOs. Every email was individually researched. No templates. No mail-merge. This is what happened.
Over 8 months, we ran Outboundy's AI campaigns targeting sales leaders, agency founders, and startup CEOs. Every email was individually researched. No templates. No mail-merge. This is what happened.
310,000
Total emails sent
34,800
Total replies
11.2%
Overall reply rate
19,200
Interested replies
3,600
Free trials started
1,000
Paying customers
Our reply rate vs industry benchmarks
Outboundy achieved elite tier (top 10%) performance across all campaigns
The funnel
310,000 emails. 1,000 customers. Here's the journey.
Every number is real. The funnel below shows the exact path from first email to paying customer.
310,000
AI-personalised emails sent
Over 8 months
34,800
Total replies received
11.2% reply rate
19,200
Interested / positive replies
55% of replies were positive
3,600
Free trials started
18.7% reply-to-trial
1,000
Paying customers
28% trial-to-paid
Conversion at each stage
Horizontal bars show the drop-off at every step of the funnel
Our ICP
Who we targeted and what converted best
We tested three ICP segments over 8 months. Sales leaders at B2B SaaS companies converted best because they understood the pain of generic outreach immediately.
| Segment | Titles | Company Size | Emails Sent | Reply Rate | Result |
|---|---|---|---|---|---|
| B2B SaaS Sales Leaders | VP Sales, Head of Sales, Sales Director | 20-200 employees | 142,000 | 13.1% | Top performer |
| Agency Founders | CEO, Founder, Managing Director | 5-50 employees | 108,000 | 10.8% | Strong |
| Startup Founders | CEO, Founder, CRO | 5-30 employees | 60,000 | 8.2% | Moderate |
Reply rate by ICP segment
B2B SaaS sales leaders responded 60% more than startup founders
Infrastructure
The sending infrastructure behind 310,000 emails
Deliverability is everything. We treated our sending infrastructure like a production system: monitored daily, rotated on schedule, never pushed past safe limits.
38
Total domains purchased
15 active sending, 8 warming up, 7 resting at any given time. Staggered rotations, never all at once.
45
Active mailboxes
3 mailboxes per domain. 70% Gmail, 30% Outlook via Mailpool. Max 40 sends per mailbox per day.
0.9%
Average bounce rate
Well under the 2% danger zone. Every list was verified before sending. Bad addresses removed immediately.
8-10 wks
Rotation cycle
Domains rotated every 8-10 weeks before burnout. Rested for 4-6 weeks, then brought back for a second cycle.
3-4 wks
Warm-up period
New domains warmed for 3-4 weeks via Outboundy's free unlimited warmup before any live campaigns.
62,000
Unique leads contacted
310K emails across a 5-step sequence. Every lead verified before sending. Lists cleaned weekly.
1
Month 1: Start small
5 domains, 15 mailboxes. 50 emails/day total. Focused on warming infrastructure and testing initial copy. Watched bounce rates like a hawk.
2
Month 2-3: Scale carefully
Ramped to 15 active domains, 45 mailboxes. 800 emails/day. First rotation cycle started. Added new domains to warming pipeline while sending from established ones.
3
Month 4-6: Full velocity
1,500-1,800 emails/day. First domains rotated out for rest, fresh ones rotated in. Bounce rate held at 0.9%. Reply rate steady above 11%.
4
Month 7-8: Optimise and sustain
Some rested domains came back for second cycles. Retired underperformers permanently. Stabilised at 1,600 emails/day with consistent deliverability.
Campaign strategy
5-step sequence. Mon/Wed/Fri cadence. Zero templates.
Every email was individually crafted by Outboundy's AI using Product Knowledge (our own features, pricing, differentiators) and real-time prospect research powered by Perplexity.
1
Monday
AI-personalised first touch
Individual research on their company, their role, their current tools. Every email references what they actually do. Under 80 words. One question.
58% of all replies came from this step
2
Wednesday
The reply-style follow-up
"Quick follow-up on my note below." Feels like a human reply, not a scheduled blast. Adds one new angle: a specific pain point relevant to their segment.
19% of replies
3
Friday
Social proof angle
Short case study or result from a similar company. "We helped [similar company] do X" with a specific number attached. Still under 80 words.
11% of replies
4
Tuesday (Week 2)
Different pain point
New angle entirely. If step 1 led with deliverability, step 4 leads with personalisation. Perplexity detects any recent company news to reference.
8% of replies
5
Thursday (Week 2)
The breakup email
Respectful close. "Looks like the timing isn't right. Happy to reconnect whenever it makes sense." Low pressure, high class. Surprisingly effective.
4% of replies
Reply distribution across sequence steps
Step 1 captures the majority, but follow-ups contribute 42% of total replies
Why this worked
The difference between our 11.2% reply rate and the industry average of 3.43% comes down to one thing: every email referenced what the prospect's company actually does. Not their industry. Not their job title. Their specific situation.
Outboundy's AI researched each prospect individually. Product Knowledge ensured every email connected our value to their world. Perplexity flagged timing signals like hiring SDRs, raising funding, or switching tools. Not one of the 310,000 emails was a template.
Outboundy's AI researched each prospect individually. Product Knowledge ensured every email connected our value to their world. Perplexity flagged timing signals like hiring SDRs, raising funding, or switching tools. Not one of the 310,000 emails was a template.
Real examples
What our AI-generated emails actually looked like
These are real emails Outboundy generated for our campaigns. Purple highlights show product knowledge. Green highlights show Perplexity research.
Hi Sarah,
Saw your team just opened 3 SDR roles on LinkedIn — scaling outbound is exciting until your reply rates tank from generic templates.
We built Outboundy's AI research engine specifically for teams like yours. It researches every prospect individually and writes emails that reference what they actually do, not just their job title.
Worth a quick look?
Saw your team just opened 3 SDR roles on LinkedIn — scaling outbound is exciting until your reply rates tank from generic templates.
We built Outboundy's AI research engine specifically for teams like yours. It researches every prospect individually and writes emails that reference what they actually do, not just their job title.
Worth a quick look?
Product Knowledge
Perplexity Research
Hi James,
Your agency landing page mentions you run outbound for 40+ B2B clients. Managing that many campaigns with per-seat pricing gets expensive fast.
Outboundy includes unlimited team members on every plan and a built-in CRM so you can manage pipelines without bolting on another tool.
Is this something your team would find useful?
Your agency landing page mentions you run outbound for 40+ B2B clients. Managing that many campaigns with per-seat pricing gets expensive fast.
Outboundy includes unlimited team members on every plan and a built-in CRM so you can manage pipelines without bolting on another tool.
Is this something your team would find useful?
Product Knowledge
Perplexity Research
Revenue & ROI
$5,558 invested. $39,300/month generated.
Here's the full cost breakdown of everything we spent over 8 months, and the revenue those 1,000 customers generate every month.
Total investment over 8 months
Every cost included. Nothing hidden.
| Cost item | Details | Total |
|---|---|---|
| Domains | 38 domains @ ~$12/year each | $456 |
| Mailboxes | 55 avg mailboxes @ $4/mo x 8 months | $1,760 |
| Outboundy Pro | $49/month x 8 months | $392 |
| Lead sourcing | ~62,000 verified leads | $2,700 |
| Email verification | List cleaning and validation | $250 |
| Total investment | $5,558 |
Revenue split by plan
Pro plan drives 56% of MRR. Enterprise customers over-index despite smaller volume.
Starter
400
40% of customers
$6,000/mo
@ $15/month each
Pro
450
45% of customers
$22,050/mo
@ $49/month each
Enterprise
150
15% of customers
$11,250/mo
@ $75/month each
MRR contribution by plan
Pro accounts for 56% of monthly recurring revenue
$5,558
Total cost (8 months)
$39,300
Monthly recurring revenue
85x
Annualised ROI
Let's put this in perspective
We spent $5,558 total over 8 months. That includes every domain, every mailbox, every lead, and our own Outboundy subscription.
Those 1,000 customers now generate $39,300 every single month. That's $471,600 in annualised recurring revenue from less than $6K of total investment. The first month of MRR alone covers the entire 8-month spend 7x over.
Those 1,000 customers now generate $39,300 every single month. That's $471,600 in annualised recurring revenue from less than $6K of total investment. The first month of MRR alone covers the entire 8-month spend 7x over.
Month by month
8 months from first email to 1,000 customers
We started slow. 5 domains, 50 emails per day. By month 3, the data showed what was working and we scaled aggressively.
Cumulative paying customers over 8 months
Compound growth accelerated from month 4 as we optimised ICP targeting and sequence copy
Monthly email volume vs reply rate
Volume increased 10x while reply rate held steady, proving personalisation scales
What we learned
7 things we discovered using our own platform
After 310,000 emails and 8 months of running Outboundy campaigns, these are the lessons that made the biggest difference.
1
Individual research beats segment research every time
Emails that referenced what a prospect's specific company does got 3.2x more replies than emails that only referenced their industry or job title.
2
Timing signals are as important as personalisation
Prospects who had recent hiring activity, funding rounds, or tool changes replied at 2.1x the rate of cold contacts with no timing signal.
3
Under 80 words. No exceptions.
Our best-performing emails averaged 62 words. Every email over 120 words underperformed. Brevity forces you to say only what matters.
4
Step 2 should feel like a reply, not a follow-up
"Quick follow-up on my note below" outperformed every other step 2 opening by 30%. People treat it like a real conversation, not a sequence.
5
Product Knowledge eliminated the "what do you do?" reply
When AI knows your product deeply, every email naturally explains your value in the prospect's context. We almost never got "what is this?" replies.
6
5 steps is the sweet spot for SaaS
Steps 1-3 captured 88% of replies. Steps 4-5 added the remaining 12%. Beyond 5, diminishing returns weren't worth the reputation risk.
7
Personalisation scales. Templates don't.
We went from 50 to 1,800 emails per day and our reply rate stayed above 10% the entire time. That's only possible when every email is individually written.
Run the same playbook for your business
Everything we used is available on every Outboundy plan. AI research, Product Knowledge, Perplexity integration, built-in CRM. Start your 14-day free trial.
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