Why should I run email marketing experiments?

Regular experiments help you improve campaign performance based on real subscriber behaviour instead of assumptions. Testing removes guesswork and gives you data-backed reasons for every decision.

How long should I run an email test?

Run tests until you have statistically significant results. The required sample size depends on your baseline conversion rate and the minimum improvement you want to detect. Avoid ending tests early just because one variant is temporarily ahead.

Should every campaign include an experiment?

Not necessarily, but building a culture of continuous testing leads to better long-term performance. Aim to test one element per campaign rather than overhauling everything at once.

What should I measure besides open rates?

Focus on clicks, conversions, revenue, unsubscribe rates, engagement over time and overall business outcomes. Open rates are useful but can be misleading due to Apple Mail Privacy Protection.

50 Email Marketing Experiments You Should Run This Year

Q: How many variables should I test at once?

Only test one major variable at a time whenever possible. Changing the subject line, CTA colour, send time, audience and offer in the same campaign makes it impossible to know what caused the result.

Most email marketers know they should test more.

The problem is not a lack of ideas. It is deciding what to test next.

Many teams end up changing random things every week without learning anything useful. Others stick with the same template for years because they are afraid of hurting performance.

The best-performing email programmes do not rely on luck. They build a culture of experimentation.

Here are 50 experiments worth running this year.

Before You Start

A good experiment answers one simple question:

Will changing one thing improve a meaningful business metric?

Avoid testing five things at once. If you change the subject line, CTA colour, send time, audience and offer in the same campaign, you will never know what actually caused the result.

Each experiment below includes what to test and what metric to watch.

Subject Line Experiments

1. Short vs long subject lines

Test subject lines around 25 characters against lines around 70 characters. Short subject lines work well for mobile previews, but longer lines sometimes convey enough value to earn the open. Track open rate as your primary metric.

2. Questions vs statements

Compare a question-based subject line against a direct statement. Questions can create curiosity gaps that drive opens. Statements work better when the value proposition is immediately clear. Let your data decide.

3. Numbers vs no numbers

Test subject lines with specific numbers against ones without. Compare "5 ways to improve open rates" against "Ways to improve open rates". Numbers tend to increase opens by setting clear expectations about what the reader will get.

4. Curiosity vs clarity

Curiosity-driven subject lines tease the content without revealing everything. Clarity-driven lines tell the reader exactly what is inside. Test both approaches to see which your audience prefers.

5. Personalisation in subject lines

Test subject lines using first name, company name, location, or no personalisation at all. Personalisation can increase open rates but only when used naturally. Overused personalisation feels gimmicky and can reduce trust.

6. Urgency wording

Test different urgency phrases such as "ends tonight", "last chance", "24 hours left" and "available now". Genuine urgency increases opens. False urgency erodes trust and should be avoided.

7. Benefit-led vs feature-led

Instead of describing what the email contains, describe what the reader will gain. Compare "Our July product update" against "Save 3 hours on your weekly reporting". The benefit-led approach almost always wins.

8. Brand name first vs offer first

Test leading with your company name versus leading with the offer. Established brands with high recognition may perform better leading with their name. Lesser-known brands often benefit from leading with the value.

9. Lowercase vs title case

Test all-lowercase subject lines against title case or sentence case. Lowercase can feel more conversational and personal. Title case can feel more authoritative. The right choice depends on your brand voice.

10. Emoji vs no emoji

Test a single relevant emoji against no emoji. Some audiences respond well to emojis in subject lines. Others ignore them or find them unprofessional. The only reliable way to know is to test with your specific subscribers.

Preview Text Experiments

11. Supporting vs repeating

Use preview text to extend the subject line with additional context. Do not simply repeat the subject line. The preview text is valuable secondary real estate that can significantly increase open rates.

12. Blank preview text

Test leaving the preview text empty. Some email clients display the first line of email content instead. This can create curiosity but also risks showing irrelevant or unhelpful text.

13. Call-to-action in preview text

Include a clear action statement in the preview text such as "Read the full report" or "See your results". A compelling CTA in the preview can drive opens even when the subject line alone would not.

14. Social proof in preview text

Include customer numbers or testimonials in the preview such as "Join 12,000 marketers who read this weekly". Social proof in the preview reinforces the value of opening.

15. Personalised preview text

Test dynamic preview content based on subscriber data. Personalised preview text for segments often outperforms generic copy because it feels more relevant.

Send Time Experiments

16. Morning vs afternoon

Test sending at 8am versus 2pm in the recipient's time zone. Your audience might engage better at unexpected times. Many B2B audiences open more during lunch hours while B2C audiences engage more in the evening.

17. Weekday vs weekend

Test sending on a Tuesday versus a Saturday. Weekend sends often perform well for B2C brands promoting leisure activities. B2B audiences typically engage more on weekdays.

18. Time zone optimisation

Send emails based on each subscriber's local time rather than your office time. Time zone optimisation can increase open rates by 5-10% compared to sending everyone at the same clock time.

19. Behaviour-based send times

Send emails when each individual subscriber is most likely to open based on their past behaviour. Some platforms can identify each subscriber's optimal send window and deliver accordingly.

20. Immediate vs delayed automation

Test whether triggering automated emails immediately after a behaviour outperforms a short delay. An abandoned cart email sent after 15 minutes sometimes outperforms one sent instantly, possibly because it feels less robotic.

Segmentation Experiments

21. Engaged vs inactive subscribers

Split your list into engaged (opened in the last 30 days) and inactive (no opens in 90 days). Send different campaigns to each group. Engaged subscribers deserve more frequent, value-rich content. Inactive subscribers need re-engagement or suppression.

22. New customers vs loyal customers

Send different email sequences to first-time purchasers versus repeat customers. New customers need education and trust-building. Loyal customers respond better to exclusive offers and loyalty rewards.

23. Geography-based content

Test segmenting by location and tailoring content to regional events, weather, or offers. Geography-based personalisation can significantly increase relevance for location-specific businesses.

24. Purchase history targeting

Recommend products based on what each subscriber has previously bought. Purchase history is one of the strongest predictors of future buying behaviour. Test it against generic product recommendations.

25. Website behaviour targeting

Target subscribers based on pages they have viewed on your website. Someone who viewed pricing pages needs different content than someone who viewed blog posts. Behavioural segmentation often outperforms demographic segmentation.

26. High-value customer exclusives

Test sending exclusive campaigns to your top 10% of customers by revenue. VIP treatment can increase loyalty and average order value without the risk of over-sending to less engaged subscribers.

27. Recent openers

Test giving subscribers who opened your last campaign early access to new content or products. Rewarding engagement reinforces the behaviour and can increase long-term loyalty.

28. Re-engagement timing

Test whether sending a re-engagement email after 60 days of inactivity outperforms waiting until 90 days. Earlier intervention often recovers more subscribers, but waiting longer risks the subscriber forgetting your brand entirely.

Email Design Experiments

29. Single column vs multi column

Test a single-column layout against a two-column layout. Single-column designs typically perform better on mobile because the content flows naturally. Multi-column layouts can work well on desktop but may break on smaller screens.

30. Image-heavy vs text-first

Compare an email with multiple images against one that relies primarily on text. Some audiences distrust image-heavy emails or have images disabled by default. Text-first emails often achieve higher click rates because the CTA is visible immediately.

31. CTA button colour

Test different button colours against your current choice. High-contrast buttons typically outperform low-contrast ones. The best colour depends on your brand palette and the surrounding email design.

32. CTA wording

Test different call-to-action phrases such as "Learn More", "Get Started", "View Report" and "Download Now". Action-oriented copy that tells the reader exactly what they will get tends to outperform generic button text.

33. CTA placement

Test placing the primary CTA above the fold, in the middle, and at the bottom of the email. The optimal placement depends on how much information the reader needs before they are ready to click.

34. Dark mode optimisation

Test whether your emails look correct in dark mode and whether an optimised dark mode version improves engagement. Over 30% of email users now read emails in dark mode. Unoptimised emails can become unreadable.

35. Animated GIFs

Test adding a subtle animated GIF against a static image. GIFs can increase engagement when used to demonstrate a product or process. They become distractions when they are decorative or autoplay with sound.

Copy Experiments

36. Short copy vs long copy

Test a brief email against a detailed version. Do not assume shorter always wins. Complex products or high-consideration purchases often benefit from more explanation. Quick promotions benefit from brevity.

37. Storytelling vs direct promotion

Lead with a customer story or case study instead of opening with a promotional offer. Stories build emotional connection and trust. Direct promotions work better when the audience already knows and trusts you.

38. Problem-first introductions

Open the email by describing the reader's pain point before presenting your solution. Problem-first copy resonates because the reader feels understood. Solution-first copy can feel premature if the reader has not acknowledged the problem.

39. Social proof placement

Test adding testimonials, reviews, or customer logos in different positions within the email. Social proof placed near the CTA often increases conversion rates more than social proof placed in the header or footer.

40. Single CTA vs multiple CTAs

Test an email with one primary CTA against one with three or four options. Fewer choices often lead to more clicks because the reader does not have to decide which action to take.

Automation Experiments

41. Welcome sequence length

Test a 3-email welcome sequence against a 5-email sequence. A longer sequence can build a stronger relationship before the first commercial ask. A shorter sequence respects the subscriber's attention. Measure conversion rate, not just open rate.

42. Abandoned cart timing

Test sending the first abandoned cart email after 1 hour versus 6 hours versus 24 hours. Earlier sends typically recover more sales, but the optimal timing depends on your customers' purchase cycle.

43. Win-back offer type

Test a discount-based win-back email against an educational content-based win-back email. Discounts re-activate price-sensitive subscribers. Educational content re-activates subscribers who need to be reminded of your value.

44. Cross-sell timing

Test sending a cross-sell email immediately after purchase against waiting one week. Immediate cross-sells capitalise on purchase momentum but can feel pushy. Delayed cross-sells feel more thoughtful but risk losing the customer's attention.

45. Milestone celebrations

Test sending milestone celebration emails for subscriber anniversaries or achievement milestones. Milestone emails often achieve high engagement because they feel personal and unexpected.

Deliverability Experiments

46. Plain text vs HTML

Test sending a plain text version of a campaign against your standard HTML template. Some audiences engage more with plain text emails because they feel more personal and less like marketing.

47. From name variations

Test different from names such as a personal name, a team name, and a company name. Personal from names often achieve higher open rates for newsletters and relationship-building emails. Company names work better for transactional and promotional emails.

48. Sending frequency

Test reducing your email frequency by half for a subset of subscribers. Many brands never test whether fewer emails would actually increase total revenue. Reduced frequency often leads to higher engagement per send and lower unsubscribe rates.

Reporting Experiments

49. Measure revenue instead of opens

Test evaluating campaign success based on attributed revenue rather than open rate or click rate. Open rates are useful as a diagnostic but revenue is the metric that actually matters. Campaigns with lower engagement sometimes drive more revenue.

50. Build a testing dashboard

The final experiment is for your team. Create a dashboard that tracks every test you run:

Test hypothesis
Variable tested
Audience segment
Results (before and after)
Statistical confidence
Next action

Over time you will build your own optimisation playbook instead of relying on generic best practices.

Which Metrics Matter

Every experiment should have a success metric defined before you launch.

Goal	Primary Metric
Improve subject lines	Open rate
Improve content	Click-through rate
Improve offers	Conversion rate
Improve lifecycle	Revenue per recipient
Improve engagement	Click-to-open rate
Improve list health	Unsubscribe rate
Improve deliverability	Inbox placement rate

Remember that improving one metric at the expense of another is not always a win. A higher open rate means little if conversions fall.

Common Testing Mistakes

Many experiments fail not because the idea was bad but because the process was flawed. Avoid these mistakes:

Testing multiple variables at the same time
Ending tests before reaching statistical significance
Using audiences that are too small for reliable results
Ignoring business outcomes in favour of vanity metrics
Copying another company's best practice without testing it on your audience
Never documenting results or sharing learnings with the team
Declaring a winner after a single campaign without repeating the test

Testing is about building knowledge over time, not chasing lucky results.

Small Experiments Compound

Most businesses send campaigns. Very few improve them systematically.

Imagine making just a 2% improvement every month. A 2% better open rate, a 2% better click rate, a 2% better conversion rate. Those small gains compound. Over 12 months, the cumulative impact on revenue is significant.

Better subject lines generate more opens. Better content generates more clicks. Better landing pages increase conversions. Better reporting reveals new opportunities.

Small experiments become significant business growth.

The Bottom Line

There is not one perfect email. There is not one perfect send time. There is not one perfect CTA.

There is only what works for your audience.

The only reliable way to discover that is through continuous experimentation. Do not ask what other marketers are doing. Ask what you have not tested yet. That is where the biggest opportunities usually are.