In the field of email marketing where data is wealth, regularly reviewing your analytics is a must. Thanks to advanced email marketing software today because you can pull out all kinds of data you need to monitor and improve your performance.
If you want to know whether your subject lines are persuasive or not, check open rate. If you want to see how your CTA is doing, check clickthrough rate. You can even perform an A/B testing to compare two versions of your email.
But using marketing data analytics effectively isn’t just about looking at the numbers and percentages. It’s about how you make sense of the data to fuel your email marketing campaign. If data is wealth, then you should be using your wealth wisely. Otherwise, it will go to waste and you will end up with a poor performance.
One methodological way to analyze your data is by following Avinash Kaushik’s Trinity, which introduces behavior analysis, outcome analysis, and experience analysis. With this approach to making sense of your analytics, it’s easier to arrive at actionable insights from the right metrics to meet your objectives.
As an email marketer, you want to know how customers interact with your email campaigns.
Through behavioral analysis, you will find answers to questions like: How many contacts from your email list are opening your email? Which CTA attracts the most number of clicks? Where are your most profitable contacts located? What time of the day do you get the most number of engagement?
These kinds of data is essential to improve your subject lines, CTAs, customer segmentation, and timing, among others. Data used for behavioral analysis is also the easiest data to pull out, which could be a reason why it’s the most popular analysis to email marketers.
However, you cannot just rely on these data to make informed decisions about your email marketing strategy. You need deeper insights, and that brings us to our next type of analysis…
The name says it all. Outcome analysis looks at the metrics that tell you whether you reached your desired result or not.
Since businesses have different models and objectives, the data you will be monitoring may vary depending on the end goal of the email marketing campaign. For instance, an online store may use average order value and total online sales for its outcome analysis, while B2B company may check on the number of inquiries, leads and closed deals from email marketing.
Insights from outcome analysis are important because it allows you to determine how much revenue your email marketing is giving you.
This one is a much higher level of analysis and requires more effort to generate data. In exchange, it gives more helpful insights.
With experience analysis, you will determine why customers do the things that they do. It gives the reasons behind the what, which you get from previous analyses.
It tells you why customers are unsubscribing from your emails, why there are emails that work while others are underperforming, why conversion is lower in your previous email campaigns and so on.
While its insightful, generating data for experience analysis is not a walk in the park. It’s only possible by performing A/B testing, surveys, and lab tests, among others.
As email marketers, it’s necessary that we keep on looking for ways to improve our strategies and boost our performance. With proper data analysis, you can adjust your email campaigns to help you in customer segmentation and personalization, among others. Indeed, data analytics can save us!
Kimberly Maceda is a Content Writer for ActiveTrail. She comes up with brilliant content about email marketing and marketing automation to keep customers updated with the trends. For Kimmy, it’s Bring Your Dog to Work Day almost every day.