Here's a simple strategy to A/B test your cold emails if you don't have enough data to achieve statistical significance.

1. A/B testing
cold emails
(without a statistically-significant sample size)

2. You’re sending out cold emails in
small batches (less than 100/day).
Are you A/B testing your cold emails
& subject lines?

3. If not, start now!
“But Steli, how can you get
statistically-significant results
with such a small sample size?”

4. Well, you don’t, but you can get
something better:
relevant, valuable insights
that’ll help you write
more effective cold emails!

5. Here’s how:
1. Send out your cold emails.
2. Look at your metrics (open rate &
response rate).
3. Segment recipients into 3 buckets:

6. Prospects who
A) didn’t open your email.
B) did open but not respond.
C)responded.
4. CALL THEM AND ASK WHY!

7. Yeah, pick up the phone!
Not to sell, but to learn!
Ask them WHY?

8. C) “Why did you respond? I’m sure you
get a ton of unsolicited emails that
just go into trash. Why did you
respond to this?”

9. B) What made you open the email in
the first place, but then not
respond?

10. C) Why did you chose to not open the
email?

11. Speaking with prospects will give you
more insights faster at this stage
than any fancy data-driven analytics
magic will.

12. Low volume, high quality insights.
That’s how you learn about your
market at that stage.

13. PICK! UP! THE! PHONE! AND LISTEN TO
YOUR PROSPECTS
Learn more:
http://blog.close.io/ab-testing-cold-emails