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The email marketing performance indicators

Del: 16/02/2007


How can we understand that our advertising efforts via email are giving the rightful returns or if a small change can obtain a bit (or a lot) more? Here is some information so as to better understand what to read in a statistic.


First Episode

There are several points of view.
The performance indicators of a single mailing, the indicators of a group of mailings (trend) and those relating to a single user (or to a homogeneous cluster of users). Today we will deal with the indicators of a single mailing.

From one mailing (be it DEM or newsletter), properly traced you can obtain a lot of information:
* The delivery rate
* The email opening rate
* The re-opening rate
* The click-through rate
* The unsubscribe rate
* The “viralization” rate
* and properly provide the "landing" website (which means the destination of the links of the email) with tools
* The "conversion" rate

Let’s see what they mean and how important they are

The delivery rate (or seen in reverse order the bounce rate) represents the percentage of mail that has been delivered compared with the mail that has been sent out.
Deliverability problems aside this indicator tells us how “clean” our database is.
If the emails collected are recent, and if subscription procedures provide for the double opt-in, the delivery rate should be very high, vice versa it could be lower if the emails are not so recent or if, for example, they were collected with paper forms.
It is very important that the database always be kept clean with smart logics. This is so because the more the database is dirty the more probabilities there are for the emails sent to be filtered by anti-spam systems).

The opening rate represents one of the most discussed indicators. It tells us how many emails have been opened compared with the ones that have been sent (or compared with the ones that have been delivered, in this case the values rise).
For opened or "read" we mean the visualisation even in the email preview window.
You must give this fact attention because it is underestimated since the systems of email marketing are able to intercept only the emails that are visualized with the image loading.
The underestimation varies from newsletter to newsletter, from database to database. Therefore, the absolute value is not “so” important, but with the variations (which we hope positive), we will be able to impress in our advertising communication.

What makes the opening rate increase or decrease?
*Having the same database available*, it is mainly the mail from (being the sender) and the subject of the email, to a smaller extent also the day and time of the week in which it is sent.
The more the mail-from is known, the more chances there are for the mail to be opened.
It is an interesting fact in the A/B testing to see the responsiveness of a database to the subject change, or changing the point of view, the responsiveness of two different clusters to the same subject.
Basically, the opening rate of a newsletter in time always tends to decrease.

The Re-opening Rate, instead, measures, the quantities of the openings per person.
This indicator can make you understand if the mail was seen on “one-shot” or if it was so interesting to be opened again.

The Click-through Rate represents the most immediate indicator of responsiveness or success of an e-mail.
This rate can be calculated compared with the e-mails sent, compared with those delivered, or compared with the e-mails opened and, therefore, it can have different values among them. The click-through rate varies not only from the function of the content quality and the graphics form but also from the editorial structure.
The higher the click-through rate is (excluding the clicks on the unsubscribe links) the more likely we will have hit the centre of the target.
Pay attention not to calculate within this rate the clicks to the unsubscribe link :-)

The unsubscribe rate tells us how many people wanted to be unsubscribed from a list, normally this is a “stable” rate, due to the normal database rotation. This indicator is a litmus paper of the bad mailings.
If the mail is of particularly low quality, it is very easy for the unsubscribe rate to increase.
Vice versa, if the mail is particularly “good” most likely the addressee will forward it to other users.
If this activity is measured, the rate of "viralization" becomes a good indicator of the quality of the message sent.

All these measurements (with the exception in part of the last) are carried out on the "e-mail" tool.

For the conversion rate, we indicate the calculation of the mailing return working for an action that the user does outside the same mailing.
You usually refer to the purchase or to a registration or to a request for information or to the downloading of a document.
Providing the landing page with tools (usually with a JavaScript), it is possible to monitor this conversion rate and report the single actions (registration, downloading, purchase) to the campaign (and even to the user) that has carried out the purchase ( even if he/she should register under a different address).

Therefore, these are the main indicators that can make us understand how well a mailing is working.

It is fundamental, making comparisons with the other dispatching works, to keep the same comparison data, that is, if you compare the percentages of the clicks it is best to compare them with the open mail.
This way there is a “normalized” datum.
Suppose there are 2 identical dispatching works in the performances, for example:

Mail sent: 1.000
Mail delivered: 900 (90% of deliveries)
Mail opened (users that have opened at least once): 500 (50% of openings compared with the mail sent or 55% of openings compared with the ones delivered)
Mail clicked (users that have clicked at least once): 100 (10% clicks compared with the mail sent, 11% compared with delivered mail, 20% compared with the opened mail)

One user says: I have 10% of clicks and the other says he has 20% … both are telling the truth.
They are simply 2 different ways of representing the same phenomenon.

In the next episodes, closer examinations will be made so as to analyse the trends and one’s own positioning compared with the average sector results.

                             Massimo Fubini
                             AD Tomato Interactive srl
        
                     ContactLab

 
 

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