Study the Email Campaign Analytics before Selecting a New ESP

Analyzing an email marketing campaign statistics is not a rocket science and you necessarily do not have to hold a marketing degree to understand the data and the figures. Today, email marketing offers detailed results of the executed campaign. The analysis will help you increase the ROI and attract more customers to the product or service you offer. One of the major reasons for analysis is the choice of ESP because without monitoring and keeping a vigilant eye on the campaign, you cannot understand the effectiveness and the impact it has managed to create. Therefore, before deciding to switch the ESP, carefully study and understand the post-campaign results.


From where to start?

There is a plethora of parameters on which the selection criteria of an ESP depend. From the analysis you can search for the following before choosing a new ESP.

  1. Make a comparison of the performance of the different mailing list.
  2. Compare the open rates against the volumes of email you have triggered
  3. Compare the spam rate of the current campaign with the previous campaign.
  4. Select the subject line, which delivers the best result and receives the maximum clicks or open rates.
  5. Understand the time during which the open rates are higher (morning, afternoon, evening or night)

Understand these statistics and compare the goals you have in mind, before selecting an ESP.

Share the statistics

Share the result of the analysis with everyone in the organization and get their useful insights on the same. It is essential to share the critical statistics with the colleagues as it will help correct the gray areas and make improvement for the future email marketing campaign.

A fair comparison will lead the way

Before you share the analytics with the ESP, ensure that oranges and oranges are compared when it comes to numbers. Do not exaggerate or give wrong statistics to the ESP as they are old and established in the email marketing world. Moreover, different ESP uses different terms for statistics. For example, open rates for your ESP might mean the open rates compared to the volume of emails being sent and for another ESP open rate would mean the number of unique customers opening the email. Therefore, a fair comparison is extremely necessary.