The Internet world is already almost perfect these days. Promises and guesses don´t count anymore; rather, everything is built on facts and results. How much did this campaign cost and how much did we earn? How many e-mails did we send and how many people read them, how many made a purchase? Almost anything can be measured. What we can’t measure is the increasing loyalty and the reader’s trust in you, your product or service. For now.

What can we learn from statistics?

E-mail campaign analytics improve every day. Today, using the right tools, you can find out who read your e-mail and when, if anything was clicked on, when and who logged out or why the message wasn’t delivered.

Much more information is starting to appear, such as: which mail provider is the recipient using, how long he read the e-mail before forwarding or printing, the location of the recipient at the time of reading.

We will analyse the most common statistical data and explain how to read it correctly.

How many e-mails was the campaign sent to?

If you are sending weekly or monthly, just watch your database grow. Notice how many new contacts you have and how many unsubscribed.

How many people read my e-mail?

Statistics of reading, the so-called “open-rate”, is the most popular information. But despite this, many people still can’t evaluate it properly. The number of readings indicates the percentage of people, who opened your message. Or let us say, it is a number of people, where it was possible determine if the e-mail was opened.

One of the reasons why it was not possible to determine if the e-mail was opened can be the security settings of particular browsers and mail clients. For example, if the user has blocked showing pictures, e-mail is marked as unread even though the recipient is now reading the e-mail, just without pictures. So generally, the result of a campaign are actually better than what you see in statistics.

Therefore, watch rather for the tendency over time. Compare the campaigns with one another. This will provide you with some good information about how your e-mail marketing and reactions from recipients are progressing in time and how the campaigns are doing comparing to one another.

How many people clicked on my links and which ones?

Another interesting finding is the number of clicks, the so-called click-rate. This gives very important information about whether your e-mail was beneficial, as the reader was willing to click on a link in the message. That’s the way to get to your web site for more information.

By the way, clicking on the link should be your main goal and purpose of most of your e-mails. To impress and get the recipient to your web site.

The percentage of clicks will provide you with the exact information about how many people clicked on an e-mail and got to your web site. You will find which links are the recipients clicking on. You will see how many clicks a particular link from your campaign received in a clear chart. This way you will see which article from a newsletter was the most interesting. If it is the third one for example, then it’s clear. E-mails have the same rules as browsers; what’s on the top counts.

Google Analytics for Monitoring

Experienced users can use another option. They can add a Google Analytics code to all links in e-mails. Then they can monitor e-mail as a source of access to websites and evaluate conversions and other information.

Were all of the messages delivered?

Another important information is analysis of a returned messages. It notifies you whena message isn’t delivered for whatever reason. For example: address is not up to date, recipient has a full mail box etc. This way, you can always have a clean database with valid e-mails. The system will mark invalid e-mail addresses by itself so you don´t send to them in future nor pay for them.

Did someone unsubscribe from my system?

Finally, you can work with log out statistics. They show all the recipients, who clicked on the “unsubscribe” button in your message. You can observe if there is an unusually large number of people unsubscribing from the campaign and ask yourself what may be the reason. When you detect the problem, avoid it in your future campaigns.

What outcome can you expect?

There is no exact number of average results you should be achieving. The numbers will vary according to the area of business and contact database. From what we have learned so far, there are a few conclusions we can share with you.

As a first example, let’s take a regular e-shop that standardly sends weekly e-mails with new offers. An average number of openings goes from 10% to 25%. The clicks of these campaigns are in the one-percent range.

In areas where there are more recipients interested in getting these e-mails, for example communal and free-time activity servers, the number of openings can grow up to 50%. When we add the cases in which the number of readings couldn’t be precisely counted, it is a really satisfying result.

Generally, it’s better not to focus on a particular number when reading statistics, but to compare results of each campaign. Or even better, take a look at your statistics of clicks and find which content is the most attractive to your readers.

Why does the number of opened e-mails decrease over time?

It’s perfectly normal that this happens with the first few campaigns. When the recipients receive your first e-mail, they are curious because they never received anything like that before. But after you send similar e-mails for a while, the factor of curiosity slowly vanishes. Or are the e-mails getting less and less interesting?

Note: If the numbers of opened e-mails seem to stay on the same level, they are still being seen by different people. Try it on yourself. You open a newsletter in August, but in September you won’t be interested in it anymore. However, your neighbour didn´t open it in August, because he was on vacation. He might read one in September, perhaps more of them and the number of opened e-mails stays the same, but the readers are different.

A/B testing

Testing is a very effective way to determine what is working and what people react to. It’s better to do this with a larger database containing at least 1,000 contacts, data is then more relevant.

The most common testing is that of a message subject. You create the same content, but use subject A for one part, and subject B for the other. Then you send a testing campaign to a 20% of your database. According to the results, you will send the more successful one to the rest of recipients.

You can test the e-mail content, headlines, calls to action etc., in the same way. A/B testing is not much different from the testing of web sites. 

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