May 12, 2023

Welcome to the world of testing in emails and newsletters.

๐Ÿ‘‹ Hello newsletter enthusiasts,

Welcome to our exciting journey into the world of testing, where we're about to cook up some email and newsletter marketing strategies!

Testing in email and newsletter marketing is like a chef experimenting with ingredients in a dish. Each ingredient represents a different element of your campaign: Subject lines, CTAs, images and copy. By conducting testing and optimizing these elements, you can create some pretty great email recipes.

But testing is not just a strategy; it's a mindset of continuous learning, exploration and data-driven decision-making.

So, let's get cooking and explore how testing can help you create an awesome email recipe!

๐Ÿพ As always, thank you for reading. Stay pawsome.

๐Ÿ”‘ Key takeaways

  • Donโ€™t forget about Apple Mail Privacy Protection (MPP): Apple MPP has a significant impact on metrics like Opens and Open Rates. It's important to consider this when analyzing the performance of your campaigns and focus on other metrics like Click-through Rates and conversions to evaluate their effectiveness.
  • Craft clear hypotheses: Formulating clear hypotheses is essential for guiding your tests and measuring their impact. Clearly define the specific differences you expect to observe and focus on meaningful changes that are relevant to your unique use case.
  • Analyze metrics: Dive deep into the data and analyze metrics such as Click-through Rates, Conversion rates and other relevant indicators. Look for patterns, trends, and insights that can provide valuable insights for optimizing your campaigns and making data-driven decisions.
  • Understand statistical significance: Statistical significance plays a crucial role in determining the reliability of your results. Remember that a result can be statistically significant without being practically significant, and vice versa. Consider both types of significance when interpreting your test results to ensure a comprehensive understanding.
  • Embrace data visualization: Visualizing your results can greatly enhance your understanding and help you spot trends, patterns, and outliers more easily. Utilize charts, graphs, and other visual representations to communicate your findings effectively, both to yourself and to others involved in your email and newsletter marketing efforts.
  • Iterate and refine: Once you've gained insights from your tests, it's important to put them into action. Implement the changes that have proven to be effective based on your analysis and closely monitor their impact on your desired metrics. Optimization is an ongoing process that requires continuous testing, refining, and experimenting with different variations to improve the performance of your campaigns over time.
  • Throughout your testing journey, it's vital to respect the privacy of your subscribers. Weโ€™ll deep dive on this in a future article.

โš ๏ธ Caution on Apple Mail Privacy Protection (MPP)

It's crucial to be aware of the impact of Apple MPP on your email and newsletter marketing efforts. MPP blocks tracking pixels in emails, making it difficult to accurately track Opens and calculate Open Rates.

Open Rates are a common metric used to measure performance in email and newsletter marketing, but they can be unreliable if they don't account for MPP.

That's why it's important to use other metrics, such as Click-through Rates and Conversions, to evaluate the effectiveness of your email campaigns.

Remember that the success of your email and newsletter marketing isn't determined by just one ingredient or one metric. It's the overall composition of your campaign, including factors like engagement, Click-through Rates, Conversions, and other relevant metrics, that provides a more accurate and comprehensive picture of your email marketing success.

By taking MPP into account and considering a range of metrics, you can gain a more holistic understanding of the performance of your email campaigns and make informed decisions to optimize your strategies.

๐Ÿค” What is a hypothesis, and how to form one

A hypothesis acts as your testing compass, directing your experiments by identifying the problem you want to solve or the behavior you aim to influence.


In hypothesis testing, we typically have both a null and an alternative hypothesis.

  • The null hypothesis assumes no significant difference. It represents the default or baseline assumption.
  • The alternative hypothesis suggests a meaningful difference. It represents what impact weโ€™re trying to detect.

This framework of having both null and alternative hypotheses provides a clear structure for testing and enables data-driven decision-making to optimize your email marketing campaigns.

For example, letโ€™s say you think that a more specific CTA like "Receive a free weekly email" could improve your newsletter's conversion rates compared to a more generic "Sign up" CTA.

For example:

  • Null hypothesis: There is no significant difference in the conversion rates between using the more specific CTA "Receive a free weekly email" and the more generic CTA "Sign up" in your newsletter.
  • Alternative hypothesis: Using the more specific CTA "Receive a free weekly email" will result in a 5% higher conversion rates compared to using the more generic CTA "Sign up" in your newsletter.

It's worth noting that setting a specific percentage in the alternative hypothesis is not necessary for all cases. Focus on defining a meaningful difference unique to your use case. This ensures that the alternative hypothesis captures the impact you expect to observe.

Once you have formulated your hypotheses, it's time to put them to the test!

Now that you've formulated your hypotheses, it's time to design and conduct experiments to verify your assumptions.

Statistical analysis will then help interpret the results and determine whether the evidence supports the rejection or acceptance of the null hypothesis in favor of the alternative hypothesis.

๐Ÿงฎ Statistical significance

Statistical significance plays a role in hypothesis testing by determining if the observed results are statistically meaningful. It ensures that the conclusions drawn from the experiment are based on solid evidence rather than randomness.

While different teams and organizations may vary in their approaches to testing and experiments, understanding statistical significance instills confidence that any updates, changes or conclusions are supported by reliable evidence rather than randomness.

In statistical analysis, it's also important to recognize that a result can be statistically significant without being practically significant.


Statistical significance helps establish the reliability of the results, while practical significance assesses the real-world implications and whether the observed effect is meaningful in a practical context.

For example:

  • Statistical significance: Let's say you conducted an A/B test to compare two different subject lines for your email campaign. After analyzing the results, you find that Subject Line A generated a 2% higher Open Rate compared to Subject Line B, and the difference is statistically significant. This means that the observed difference in Open Rates is unlikely to have occurred by randomness. It provides evidence that Subject Line A has a higher impact on Open Rates than Subject Line B.
  • Practical significance: Continuing from the previous example, although Subject Line A showed a statistically significant higher Open Rate, the practical significance may depend on the overall context and goals of your campaign. If the 2% difference in Open Rates doesn't result in a substantial increase in Click-through Rates or Conversions, it may not have a significant practical impact on the campaign's success. In this case, even though there is statistical significance, the practical significance may be limited.

To make informed decisions, it's important to consider both statistical and practical significance. By doing so, you ensure a comprehensive understanding of the impact and relevance of your findings.

๐Ÿงช Testing methodologies

There are several common testing methodologies in email and newsletter marketing that can help you gather insights and optimize your campaigns:

  • A/B testing: A/B testing involves creating two different versions of an email with only one element (such as the subject line or the call-to-action) being different between the two versions.
  • Multivariate testing: Multivariate testing involves testing multiple elements of an email at the same time. For example, you might test two different subject lines, two different images and two different calls-to-action, creating eight different versions of the email. Multivariate testing can be more complex than A/B testing, but it allows you to test more elements at once and potentially find more optimal combinations.

Regardless of the testing methodology you choose, having a clear hypothesis and understanding statistical significance are crucial for accurately measuring the impact of your tests and making data-driven decisions for your email and newsletter marketing campaigns.

๐Ÿ” Analyzing the results

We wonโ€™t go into testing tools just yetโ€ฆ but letโ€™s say:

Yay! You have an experiment up and running!


Now it's time to dive into the data and analyze the results.

Look for patterns and trends and draw meaningful conclusions. By analyzing the data, you can gain valuable insights that guide your decision-making and optimization efforts in your email and newsletter marketing campaigns.

During the analysis phase, pay attention to metrics such as Click-through rates, Conversion rates and other relevant indicators. Look for statistically significant differences between the variations you tested and consider the practical significance of these differences in terms of achieving your campaign goals.

While concepts like statistical power, confidence intervals and p-values provide deeper analysis, you can start by using calculators or other tools to help understand your findings. They can help you understand the significance of your findings and provide a foundation for further exploration.

Pro tip: Take note of any interesting trends or outcomes that emerge from the data. This will help you refine your strategies and build upon your learnings in future experiments.

๐Ÿ“Š Embracing Data Visualization

But don't get lost in the numbers!


Embrace data visualization. Use charts, graphs and visual representations to communicate your findings effectively.

Whether it's a line graph showing the trend in Open Rates over time or a bar chart comparing the performance of different CTA copy variations, visuals can convey information in a concise and engaging manner.

With data visualization, you can turn numbers into compelling visuals that tell a story and convey insights at a glance.

๐Ÿ”„ Iterating and refining

Once you've analyzed and visualized your results, it's time to iterate and refine.

Implement the changes that have shown to be effective based on your analysis and closely monitor their impact on your desired metrics.

Remember, optimization is an ongoing process that requires continuous testing, refining and experimenting with different variations to improve the performance of your campaigns over time.

Continuously track the performance metrics and gather data to assess the effectiveness of the changes you have made.

Each iteration presents new opportunities to uncover insights and improve the performance of your email and newsletter marketing campaigns.

As you iterate and refine your strategies, keep track of the changes you implement and the results they generate. This allows you to learn from each iteration and build upon your successes. Whether you use a dedicated tool, a spreadsheet, or any other method, maintaining a documentation of your tests and their outcomes helps you track progress and make informed decisions for future optimizations.

๐Ÿ’ผ Putting it into practice

Now that you're equipped with knowledge about testing strategies, statistical significance, and data analysis, it's time to put your learnings into practice.


Here are some variables you can experiment with in your email campaigns:

  • Subject lines: Test different aspects such as length, tone, emojis, personalization and other variables to see which ones generate the most Opens and Clicks. Keep in mind the impact of Apple MPP on Open rates and consider focusing on metrics like Click-through rates and Conversions instead. You can read more about Apple MPP's impact on Open Rates here.
  • Side note: While some Email Service Providers (ESPs) offer subject line testing capabilities, where they send out your email newsletter with two subject lines and select a "winner," it's important to be aware that this method may not always be the most reliable. You can find a more in-depth analysis of this approach in our article here.
  • Email copy: Experiment with different messaging, voice, formatting and other variables to discover what resonates best with your audience and generates the highest engagement. Craft compelling and personalized copy that speaks directly to your subscribers' needs and interests.
  • Call-to-action (CTA): Test various elements of your CTAs, including text, placement, color and other variables, to identify which combinations drive the most Clicks and Conversions. Optimize your CTAs to create a sense of urgency or highlight the value proposition of your offer.
  • Images: Try out different images, placement options, and sizes to determine which ones capture the most attention, drive engagement and result in higher conversions. Visual elements can have a significant impact on the overall effectiveness of your email campaigns.

By monitoring and analyzing these metrics, you can gain insights into the effectiveness of your testing variations and make data-driven decisions to optimize your email and newsletter marketing strategies.

๐Ÿง  Growth mindset

Not every test will yield the desired results, and that's okay!

Embrace those moments as learning opportunities.

Analyze the data, identify the factors that didn't work as expected and adapt your approach accordingly.

Testing is a journey of continuous improvement, and each step, whether successful or not, brings you closer to success.

Embrace a growth mindset, learn from your experiments, and let each iteration be a stepping stone toward achieving better results.

๐ŸŽ‰ Celebrate the wins

Yay! When your tests produce positive results, itโ€™s time to celebrate your victories. Throw some confetti, dance around and give yourself a high-five!

Celebrating wins creates a culture of innovation. It's a reminder of what you can achieve when you push boundaries and strive for excellence.


So, raise a metaphorical toast to the power of testing and optimization!

Whether it's a sparkling soda or a cup of coffee, savor the moment and let the positive results, no matter how big or small, inspire you to keep pushing forward.

Want us to deep dive on a newsletter? Or maybe feature your newsletter in an upcoming newsletter? Email us.

๐ŸŽพ Fetchworthy Finds

๐Ÿถ Pawsitive vibes

๐Ÿ’Œ Thanks for joining the pack of newsletter enthusiasts! Keep on reading, writing and sharing your newsletters with the world.

And an extra special shoutout to those who have been sharing their feedback with us โ€” thank you!

๐ŸŽ‰ Have a great weekend!

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