Introduction:
Learn. Implement. Analyze. Yes, learn new hacks, implement them, or A/B test them and analyze the stats to take your email marketing game to the next level.
In this article, you’ll learn ‘how you can A/B test your email campaign in Klaviyo.’
Let’s dive in!
How to A/B test campaign emails
- Go to your email campaign option in Klaviyo.
- Create a campaign.
- Name your campaign.
- Select the lists or segments. Also, specify the list or segment if you want to exclude.
- Toggle on ‘Smart sending’ if you don’t want to send the email again within 16 hours. [You can change the smart sending time from 16 hours.]
- Under the ‘Tracking’ section, use the options below to track links in Google Analytics.
- Click “Continue to Content”
- Make sure you have put the subject line, preview text, sender email , sender name.
- Design your email campaign as usual.
- Save it.
- To create an A/B test, click “Create A/B Test.” This will automatically generate a second, identical variation of your campaign and take you to the Campaign A/B Test page.
- Name your email campaign both variations A and B so that you can later understand which variable you were testing in this email.
- Don’t edit anything in one variation, either A or B. Go to the other variation to edit ONLY ONE variable. For example, if you want to test emojis in the subject line, then only add an emoji to the subject line of one variation, keeping the other variation without any editing.
Content Test Settings:
Choose your winning metric from open rate, click rate or placed order rate. Recommended is to use click rate to analyze your email campaign performance.
But it depends on:
Test Size:
By default, both variations will be sent to 50% of your total recipients. You can customize this division by adjusting the slider on the division bar, as shown in the image below.
If you choose 100%, the campaign will send to everyone at the scheduled send time and you will
have the ability to send in the recipient’s local timezone.
Check the box ‘Track links separately in each variation’ to add variation letter as a UTM parameter labeled ‘variation’ to all links.
- Hit the ‘Continue to review’ button in the bottom right corner.
- Double-check the subject line, from/replies, content, unsubscribe link, tracking.
- Click the ‘Schedule or Send’ button in the bottom right corner.
- From there, you can either schedule your email campaign or send it right away.
How to analyze A/B testing of your email campaign in klaviyo?
♦ Go to your email campaign after It has been sent.
♦ Navigate to A/B test results next to ‘overview’ tab
Best practices to A/B test your email campaign:
- Subject Line Variations: Test different subject lines to see which ones have the highest open rates. You can experiment with various styles, such as personalized subject lines, questions, emojis, or urgency-driven subject lines. A/B testing subject lines can help you find what resonates best with your audience.
- Content Formatting: Test different email content formats. For example, try a text-only email versus an email with images and multimedia elements. You can also test long vs short email copy.
- Call-to-Action (CTA) Buttons: Experiment with the design, placement, and wording of your CTA buttons. Test different button colors, sizes, and positions within the email. Additionally, vary the language of your CTA text to see which phrases or incentives drive the most clicks.
- Send Time and Frequency: Test the timing and frequency of your email sends. Try sending emails at different times of the day or on different days of the week to determine when your audience is most responsive. You can also experiment with the frequency of your emails, such as sending weekly vs. bi-weekly or monthly.
- Social Proof and Reviews: Test the inclusion of social proof elements, such as customer reviews, ratings, or user-generated content, in your emails. Determine whether showcasing positive feedback or product recommendations increases click-through rates and conversions.
Hope you loved this article ‘How you can A/B test your email campaign in klaviyo’.
Wanna take your E-commerce business to next level with proven email marketing strategies? You’re just ONE step away. DM ‘Klaviyo consultation’ at info@alixemail.com or click here to schedule a meeting”
Don’t forget to subscribe our YouTube channel [Marketing Chamber ] for klaviyo tutorials. For Urdu/Hindi klaviyo tutorials click here. For English klaviyo tutorials click here.
FAQs:
1] How to A/B test email in email marketing flow in klaviyo?
- Click Preview and test from the template editor.
- Click Search for a profile and enter the email of a profile that includes the variable you’d like to add.
- Preview the message in Klaviyo’s previewer, or click Send Test to send a test to your inbox.
4] What is A/B testing in Klaviyo?
Answer: A/B testing in Klaviyo allows you to compare two or more variations of an email campaign to determine which one performs better based on specific metrics.
5] What elements can I A/B test in Klaviyo email campaigns?
Answer: You can test various elements, including subject lines, sender names, email content, images, CTAs, and sending times.
6] How do I set up an A/B test in Klaviyo?
Answer: In Klaviyo, you can set up an A/B test when creating an email campaign. Simply choose the A/B test option, select the elements to test, and define your test groups.
7] What metrics should I monitor during A/B testing?
Answer: Key metrics to monitor include open rates, click-through rates, conversion rates, and revenue generated. The metric you choose depends on your campaign goals.
8] How large should my A/B test groups be?
Answer: It’s recommended to have a statistically significant sample size, typically at least a few thousand recipients in each group, to ensure reliable results.
9] How do I interpret A/B test results in Klaviyo?
Answer: Look for statistically significant differences in metrics between the variations. The winning variation is the one with better performance in your chosen metric.
10] Can I test more than two variations in Klaviyo A/B tests?
Answer: Yes, you can test multiple variations, but keep in mind that larger tests may require larger sample sizes to achieve statistical significance.
