#170 - Should We Still Test?

<p><span style="font-weight: 400;">Can you run an A/B test if you have a few hundred prospects in a campaign?</span></p> <p><span style="font-weight: 400;">Ask any data scientist or savvy marketer, and they’ll tell you “no”. Why? You need lots of data to have confidence that you’re actually picking the real winner.</span></p> <p><span style="font-weight: 400;">So what’s a cold emailer to do?</span></p> <p><span style="font-weight: 400;">In this episode, we explore this question and leave you with a reliable process for testing low-volume email campaigns using qualitative feedback, inbound data and a few other testing hacks you can use, right now.</span></p> <p><span style="font-weight: 400;">Enjoy!</span></p> <p><strong>HERE’S‌ ‌WHAT‌ ‌WE‌ ‌COVER‌ ‌IN‌ ‌THIS‌ ‌EPISODE:</strong></p> <ul> <li style="font-weight: 400;"><span style="font-weight: 400;">Why we need testing</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">In what cases testing results are super valuable to drive your business decisions </span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">How and when to do A/B testing</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">How to increase deliverability with testing</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">When to kill a variation</span></li> </ul> <p><span style="font-weight: 400;">Now that you've heard our views on cold email testing, make sure you always keep a copy of every experiment you ran along with stats, so you can bring new team members up to speed on what worked and what didn’t.</span></p> <p><span style="font-weight: 400;">Happy testing!</span></p> <p><span style="font-weight: 400;">Jeremy and Jack</span></p>