We Sent 118,781 Cold Emails to Distressed Homeowners. Here's Every Number.
Most cold email advice for real estate investors is written by people selling software or selling a coaching product. We run actual email marketing campaigns. This is the full dataset from multiple real estate acquisition companies we manage, including the numbers that make us look bad.
The short version: 116,244 homeowners contacted produced 593 replies, 161 qualified opportunities, and $1,396,000 in pipeline. Our reply rate was 0.51%, which is roughly one sixth of the benchmark the cold email industry tells you to hit. Both of those sentences are true at the same time, and understanding why is the whole point of this page.
The raw numbers
| Metric | Result |
|---|---|
| Emails sent | 118,781 |
| Homeowners contacted | 116,244 |
| Unique opens | 45,779 (39.4%) |
| Unique replies | 593 (0.51%) |
| Bounces | 4,862 (4.09%) |
| Qualified opportunities | 161 |
| Pipeline value | $1,396,000 |
| Campaigns | 34 |
Derived figures that matter more than the percentages:
| Metric | Result |
|---|---|
| Homeowners contacted per opportunity | 722 |
| Emails sent per opportunity | 738 |
| Replies per opportunity | 3.7 |
| Opportunities per 10,000 contacted | 13.9 |
| Pipeline per 10,000 contacted | $120,092 |
| Average opportunity value | $8,671 |
What is a good reply rate for cold email to motivated sellers?
Well under 1%. Ours was 0.51% across 116,244 contacts. If you are being told to expect 3% or more, you are reading B2B cold email advice that does not transfer.
The 3% benchmark comes from business-to-business outreach: work inboxes, decision makers who expect vendor email, and a recipient whose job involves evaluating offers. Motivated seller outreach is none of that. You are emailing a personal Gmail or Yahoo account belonging to someone dealing with a foreclosure, a probate, or a divorce. They did not ask to hear from you, and replying to a stranger about their house is a much higher bar than replying to a stranger about software.
We flag campaigns internally at 3% reply because that is where scaling makes sense. Almost nothing clears it. The campaigns that produce deals mostly sit under 1.5%, and they still produce deals, because 722 contacts to create one $8,671 opportunity is good math when contacts are cheap.
If you take one thing from this page: most companies optimize for reply rate, but track contacts per opportunity. It is the only number that connects your list spend to your pipeline.
What actually kills cold email accounts: bounce rate
When we started running these campaigns, our bounce rates were bad. Some lists came in at 15% to 20%, which is an unsustainable rate for any sending domain. We assumed the problem was our copy or our send cadence. It wasn't. It was the data.
We were buying seller lists from vendors who did not verify what they sold us. A real share of every list turned out to be invalid: addresses that had never existed, mailboxes closed for years, and a smaller but more dangerous group of known spam-trap and abuse-complaint addresses that damage a sending domain the moment you touch them. None of that is visible until you send to it, and by the time it shows up in your bounce rate, the damage is already on the domain.
That is what forced a change into our process. Every list we send now runs through email verification with ZeroBounce before a single contact is loaded into a campaign. On the accounts where that step has been in place the longest, bounce rates have come down to under 1%. Our blended portfolio bounce rate still sits at 4.09%, above the 3% ceiling we hold ourselves to, because that number mixes in older lists and newer accounts that haven't fully cycled onto the verified process yet. It is coming down, not going up, and the accounts furthest along are the proof the fix works.
There's a second lesson underneath the first: sender reputation is shared across a campaign, not owned by it. In one account, two poorly-verified campaigns pushed over 2,000 bounces through the same sending addresses a healthy, high-performing campaign depended on. The damage doesn't stay contained to the campaign that caused it.
Run every list through verification before upload. It is the single highest-return step in the entire process, and it happens before you write a word.
Open rates varied from 24% to 47% across accounts running the same playbook
Same copy framework. Same sequence structure. Same team. The spread across the six accounts:
| Account | Open rate |
|---|---|
| A | 47.3% |
| B | 43.7% |
| C | 38.4% |
| D | 36.8% |
| E | 24.5% |
| F | 24.5% |
That variance is not creative. It is infrastructure: domain age, warmup quality, how many campaigns share a sending pool, daily volume per inbox, and whether the email carries tracking pixels and HTML.
On one account we disabled open tracking entirely and switched to plain text, on the theory that the tracking pixel and HTML wrapper were themselves spam signals. That account now has no open data at all, deliberately. We judge it on bounce rate and replies. If your open rate is collapsing, the fix is upstream of the words.
We deliberately cut our sending volume
Between August 1 and 15 we sent 10,226 emails across six accounts, a fraction of our earlier pace. That was on purpose. Several accounts got throttled after deliverability flags, one had four campaigns paused to concentrate a shared daily capacity, and one had its entire tracking configuration changed mid-flight.
The instinct when results dip is to send more. In our experience that is backwards. Volume on a damaged sending reputation produces bounces, which produces more damage. Cutting volume, verifying lists, and consolidating campaigns is slower and works.
What we would do differently
- Verify every list before upload, without exception. Our 4.09% bounce rate is entirely self-inflicted and entirely preventable.
- Run fewer campaigns per sending pool. One account had 11 campaigns splitting a 300-per-day capacity across two domains. Every campaign starved, and none reached a sample size worth judging.
- Stop judging campaigns on opens. Apple Mail Privacy Protection inflates opens, and tracking pixels may hurt the deliverability they are measuring. Bounce and reply are harder to fake.
- Wait for 1,000 contacts before believing anything. Our best-looking campaign showed a 7.37% reply rate at 95 contacts. At 393 contacts it was 2.80%. The early number was noise, and acting on it would have meant scaling the wrong thing.
Frequently asked questions
What reply rate should real estate investors expect from cold email?
Under 1% for outreach to distressed homeowners. Our portfolio ran 0.51% across 116,244 contacts. The 3% figure common in cold email advice comes from B2B outreach to work inboxes and does not transfer to homeowner outreach.
How many cold emails does it take to generate one deal opportunity?
In our data, 722 contacted homeowners per qualified opportunity, or about 738 emails sent. The average opportunity was worth $8,671.
What is an acceptable bounce rate for cold email?
Below 3%. Above that, sending domains start taking reputation damage that better copy cannot repair. Our portfolio averaged 4.09%, which we consider a failure and trace to unverified lists.
Does cold email work for motivated seller lead generation?
Yes, but not through the metrics most people track. 116,244 contacts produced $1,396,000 in pipeline, at a reply rate that looks like failure by conventional benchmarks.
Why is my open rate dropping on cold email campaigns?
Almost always infrastructure rather than subject lines: domain warmup, volume per inbox, too many campaigns sharing a sending pool, or tracking pixels and HTML triggering filters. Fix deliverability before rewriting copy.
Methodology
All figures pulled directly from the Instantly API across active client workspaces, covering 34 campaigns. Open and reply rates are unique counts divided by unique contacts. Bounce rate is bounces divided by emails sent. Opportunities and pipeline values are as marked in each client's own workspace. Individual client accounts are anonymized and not identified by name.
Reporting window: these are campaign-lifetime cumulative totals as of the pull date (August 15, 2026), not a single month. Campaigns started at different times.
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