How can you create a strong email testing plan?

This is the most important part of a testing plan. Without objectives, it's like taking a road trip without a destination. The decisions you make here will dictate decisions to be made in the subsequent steps of this process. Defining objectives will allow you to identify the KPIs associated with meeting those objectives, which allows you to identify the variables to be tested to affect those KPIs, and then develop a hypotheses around how to achieve desired results.

Email is awesome, but doesn't function in a silo. You have to understand how all of the parts of your funnel work together and the role that email plays in that funnel. More specifically, you need to know which role each email or automation plays. Only then can you identify what KPIs you want to track and what indicators of success are really important. You might look for clicks, calls booked, replies, or even just open rates. But you need to see big picture first.

Além de ter um objetivo claro, também é importante priorizar. Da mesma forma que alterar muitas variáveis atrapalham a confiabilidade dos resultados, ter muitos objetivos também pode tornar difícil sua análise.

You can test everything in email marketing, but you shouldn't. Prioritize tests through two factors: 1?? Level of Effort (LOE) How much time will be required to launch the test? Start with low, medium, and high effort based on: ?? # of hours needed to deploy the test ?? hard cost, if any, to deploy the test. 2?? Impact What is the predicted business impact of the test? Start with low, medium, and high impact based the below: ?? Low = impacts email campaign metrics (opens, clicks) ?? Medium = impacts email program metrics (subscriber acquisition, retention) ?? High = impacts business metrics (revenue, profits, customer retention) ?? Prioritize Low LOE, High Impact tests immediately. Everything else can come later.

At the beginning of any testing process, you need to understand what your business is trying to get more off now if you are trying to get higher open rates when you know you need to improve and do testing on your subject lines. If it’s a case where you need to improve the amount of people clicking through on your emails when you know you need to improve the content in your emails itself, it’s all about understanding what part of the whole process isn’t working the way you want it to work and then testing different strategies and different messaging in those parts to get a better result.

A/B Testing is great for small changes or smaller parts of your email. Testing different subject lines, CTAs, images, etc are great for A/B testing and can be done within the same campaign or flow email. Multivariate testing works best when you keep track of the different styles of emails that you use and look for patterns or trends. If you notice that your audience responds best to a certain style, you can start learning on that more and more. Avoid multivariate testing within a single email. The results often aren't statistically significant and are difficult to parse out what really made the difference.

For flows that are doing well, I like to find the lowest common denominator (worst metric, relatively speaking) and A/B test relentlessly until we raise it. For flows that need drastic overhauls, multi-variate testing works better. In this case, consider building an entirely new version as a separate branch and sending half the traffic down that branch.

Choose your testing method: -> A/B Testing: —Segment your audience. —Send two versions with one variable changed. — Measure engagement for effectiveness. -> Multivariate Testing: — Test multiple variables simultaneously. — Analyze impact on engagement. -> Segmentation Testing: — Divide audience based on demographics or behavior. — Tailor emails for relevance. —Measure engagement for optimization. -> Controlled Experiments: — Establish control group. — Test different versions. — Compare results for effectiveness. -> User Testing: — Recruit participants for feedback. — Gather insights for improvements.

A/B testing sounds complex (especially to small business owners) but it really doesn't have to be. It can simply be testing two subject lines. Unless you chose to manage it manually, once you've set it up the platform (usually) tests and then automatically sends the remainder of emails using the winning subject line.

I have always found that A/B testing is the best way to test an email strategy, as you can get the results quite quickly and understand what improved and what made your campaigns worse. And data is power so once you understand this, you can literally scale your campaigns up quite quickly.

It's important to keep your objectives in mind here. Develop a hypothesis on how to improve a specific KPI, then identify the variables associated with that KPI. For example, if you want to improve open rates, test different subject lines. Personalization vs. no personalization. Emojis vs. not using emojis. Etc. If you want to improve CTR, an example might be testing different CTAs. A button vs. a hyperlink, different button colors, different button text, etc.

The challenge with selecting variables is ALSO finding a way to track results for the long term. For example - most businesses simply write 2 or 3 different subject lines and call that A/B testing. The better way to do this is to categorize your subject lines into groups (for example we have 14 different categories) and when we are testing subject lines, we indicate what type of subject line is being used. This way we're collecting real actionable data over the long term on which type of subject line our subscribers respond to the best. So not only select your variables - but choose how you're going to track and implement those results as well.

Choose variables that directly impact your testing objectives. For A/B testing, focus on single elements like subject lines, images, or button colors. In multivariate testing, consider various combinations of elements such as headline, body content, and CTA. Ensure the variables you select are relevant to your goals, allowing you to pinpoint effective changes for better email performance.

In my experience with email marketing, I've learned that choosing the right variables to test is crucial. For instance, tweaking the subject line can massively boost open rates, but it's also important to consider the preheader text and the 'from' name for their impact on credibility. When I conduct A/B tests, I focus on changing one element at a time to clearly see what works. For multivariate tests, I limit the number of combinations to keep the results understandable and actionable.

Focus on One: Test one variable at a time for clarity—subject lines, from names, CTAs. It simplifies analysis. Mix It Up: Experiment with different elements—design, timing, copy—to see varied impacts on engagement and conversions. Measure Impact: Understand how each change affects outcomes. A catchy subject might boost opens, while a trusted sender name builds credibility. Prioritize: Start with what could have the biggest impact based on your goals, and test strategically from there.

This is essential for multivariate testing as your email provider will do this automatically for A/B testing. As you test different styles of emails or different combinations within an email, make sure you are focusing on the same segment as you send campaigns. You'll probably find that segments within your list respond differently to various message styles and formats.

Let's stop the ??. Most marketers talk about segmentation but when you audit what's going on under the hood it's a lot of the same "Engaged 90d" or "Purchased last 30 days". That's not segmentation - that's child's play. The better approach is to identify which customers exhibit similar behaviors not just those who are opening or clicking on emails. The next step there is to curate content that aligns with each segment and focus on guiding your customers through their journey. Segmentation and a fundamental understanding of customer behavior helps you communicate with your customers...not at them.

This is probably the place where your test design will be most impacted based on what you want to learn or what your main driving KPI is. This may also be limited for you based on tools at your disposal. For example you may want to try testing different email templates against each other per predefined audience group, or create multiple templates and use an AI driven audience segmentation tool to create micro-segments, allowing the "black box" to determine who gets what email based on how your main KPIs are affected.

Customizing an email for different user personas can improve results. I've found that when writing an email with the various individual segments in mind, that small variations in language and call-to-action perform better. Consider segmenting on past email engagement and purchase history.

Segment your audience based on factors related to your testing objectives. Consider demographics, past behavior, or preferences. For example, if you're testing subject lines, segment by demographics to see if different groups respond differently. Tailor your segmentation strategy to align with the variables being tested, allowing you to gather insights specific to different audience segments.

Again, be sure to keep your objectives in mind here! Were you able to affect the specific KPI you were testing? Did your hypothesis prove to be correct? Did you collect enough data to get significant results? Another aspect of this is determining how long you should run the test. This is usually dictated by a number of emails sent rather than a set amount of time. If you're sending 1 email per week, you'll need to run the test for a longer amount of time than if you're sending an email every day.

After you have done the testing process, it’s so good to analyse what works and what doesn’t work when she started doing that. You’ll be able to scale any campaign future a lot easier because you know exactly what works for your brand and what does not.

Before you begin your testing, decide which metrics matter to you post and set some trackable goals. Doing this will ensure you don't lose sight of what is most important - it's easy to get distracted and lose track of what your initial goals were

Supplement quantitative metrics with qualitative feedback through surveys and user interviews. Talk to real subscribers about why certain campaigns did or did not resonate. This can reveal psychological and emotional factors that click rates alone may not show. The learnings can inform not just email optimization but wider customer research.

Analyzing your results and drawing conclusions is indeed crucial in email marketing. By measuring metrics like open rate, click-through rate, and conversion rate, you can identify what works best and apply those learnings to future campaigns. Statistical tests can help you determine if the differences between groups are significant. This iterative process of testing, analyzing, and optimizing can greatly improve your email marketing strategy over time.

In summary, creating a strong email testing plan involves defining clear objectives, selecting the appropriate testing method, identifying variables to test, segmenting the audience, and analyzing the results. By following these steps, marketers can optimize their email marketing strategy, improve engagement, and achieve their campaign goals effectively.

Know what you're testing. Don't just test two similar subject lines because you want to test; you won't see any difference. Rather, try testing Question vs. Statement subject lines, long vs. short, with vs. without emojis, etc. This way, you'll see what actually works for you.

Use RICE scoring to define the priority of experiments. Looking at Reach, Impact, Confidence and Effort to clearly show which experiments you should prioritise first.

Creating a strong email testing plan is all about defining goals, segmenting your audience, and continuously testing various elements. Use testing tools, optimize for multiple devices, and pay attention to scheduling. Analyse results and make consistent improvements for effective email marketing.

Give yourself time. Testing content might take months to actually gather results that matter. If you want to test out a variable, give yourself enough time to see that variable act in different scenarios, different formats, different moments of your business, or you will end up with unclear results that might even be misleading for your business.