As a marketer, your task is to collect and analyze email marketing data to better understand your audience’s desires and needs, enabling you to tailor campaigns more effectively.

However, the data that appears on your dashboard may not always convey the message you expect.

For instance, you might observe thousands of clicks on your emails and immediately assume that it’s your top-performing email.

But would you still consider it successful if it had an extremely low click-through rate (CTR) and resulted in people unsubscribing from your email list?

Obtaining email marketing data isn’t always as straightforward as looking at your analytics tool’s default dashboard settings; in fact, this information can often be misleading.

Let’s explore a few mistakes in email marketing data analysis that you should avoid.

Neglecting to Examine a Statistically Significant Timeframe:

Many businesses experience fluctuations in lead volume throughout the week or month and analyzing data for just a few days typically fails to provide an accurate reflection of long-term return on investment (ROI).

Suppose your objective is to generate an average of 100 qualified leads per month.

You could achieve this by receiving 10 leads in one week and 30 leads in each of the following three weeks. Very few businesses observe the same number of leads every single day or week.

If you were to assess projected performance based solely on the initial week, you might conclude that lead volume is unusually low.

However, the overall account still reaches the goal of 100 leads per month, with future weeks showing an increase in volume.

Understandably, many business owners and CMOs closely monitor the numbers on a daily or weekly basis.

Marketers should provide a broader context to alleviate concerns when daily results are down, but monthly sales are up.

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Focus on What Subscribers Do After Opening, Not Just the Open Rate:

Let’s imagine you send a promotional email to thousand subscribers every week on the same day and time.

While your average open rate stands at 12%, you made changes to your email content in the first week of April and observed that 20% of your subscribers opened it.

Does this mean the email is better? Not necessarily.

It all comes down to your goals. Ask yourself the following questions:

1) Why am I sending these emails in the first place?

2) What do I hope to achieve with them?

3) If I don’t meet my goals with these emails, can they still be considered successful?

Chances are your ultimate objective is to generate sales and revenue from your email marketing campaigns.

If that’s the case, a different set of metrics determines whether your campaign is successful or not.

Failure to Consider Seasonality:

When considering timeframes, it’s crucial to keep seasonality factors in mind.

An e-commerce business is likely to experience its highest sales period around Black Friday, whereas a B2B business may observe a decrease in lead volume during the holidays.

Examining email campaign data from previous years can be beneficial to understanding which months typically have the highest and lowest volumes.

You should incorporate data from Google Analytics and other platforms, as well as overall backend sales and lead data.

Final Thoughts:

Data analysis plays a vital role in the realm of business, as it offers valuable insights into business performance and identifies areas that require improvement.

Nevertheless, it is important to acknowledge that errors in data analysis can be both common and expensive.

To mitigate these risks, it is advisable to adhere to the best practices provided in this context. By doing so, you can elevate the quality of your reporting and derive actionable insights from your data.

These insights will help you improve your email marketing campaigns and increase your revenue.