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Split. Test. Analyze. Optimize.

Create click-worthy campaigns & eliminate guesswork with A/B testing. Experiment
to identify the best-performing variant and optimize your campaign performance.
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Why Should You A/B Test?
Why should we a/b test
What Can You A/B Test?

Experiment with 2 different sender email addresses/domains to determine which has higher email deliverability and open rates

Allows you to test different elements of sender names or identities. For eg: brand names, first names, last names, etc., can be used to identify the variant with higher open rates and click-through rates

Play around with the length of the subject line/ keywords/ the tone of the subject line to identify the one with a higher engagement and open rate

Compare different variations of the display content that appears before opening an email to determine the variants that resonate better and attract’s higher open rates

Test out two versions of the email’s main body and elements like images, text, and call-to-action to identify which combination performs best, leading to higher conversion rates

A/B Testing in 5 Simple Steps

Create variants A and B

Create two variants of subject lines, preview texts, sender names, and email content
to compare and test


Set up the winning metric

Choose a metric that determines the success of your campaign - open rate/ click rate/ no. of orders or the total revenue


Fix the size of your test group

Configure the size of your test group and schedule the emails. Test group size can vary between 10-50% of your email list


Send the winning variant to the remaining recipients

The winning variant is identified and sent to the remaining recipients on your email list


Access detailed performance reports

Track your campaign progress with detailed analytics and performance reports

Stay Ahead with Data-Driven Insights
Identify areas of improvement and opportunities for growth by tracking your customer behavior and identifying trends. Get detailed reports on the performance of each variant across metrics such as email deliverability, open rate, click-through rate, revenue generated, etc., to make data-driven decisions