We are accustomed to measure the results of the marketing actions we carry out to levels that in certain cases are close to paranoia and yet in the campaigns of mailings we usually settle for knowing the number of subscribers that are sent and the rate of opening Or visualization thereof.

To remain in such a poor report is a mistake, since the medium allows to analyze many other additional metrics that are also more reliable than the openings since these, if we think coldly, do not allow us to know the real success of a campaign since we can Have opened many subscribers but not necessarily to read our offer or message. Maybe it was to delete it 2 seconds later!

Let’s see what data we must analyze (we show them in order, before sending, while sending and after sending):

QUALITY AND QUANTITY OF OUR SUBSCRIBERS

Whether it is a BBDD generated with own resources, or facilitated by suppliers of co-registries, leads, etc. The first information we need to know is who will we send our bulletins to? and how close or remote is your profile to our target audience based on our offer or message? We are not going to go into this topic too much because there are many different variables and cases, but you have to be clear to analyze the results if the BBDD that we will use is well segmented or not.

To give an example, if we send an offer of alloy wheels super molonas to tune our car and we have a 10% of requests for information can be considered:

A- A success if we have sent the bulletin to a horizontal and generalist BBDD.

B- A failure if we were supposed to send to a vertical and segmented BBDD of tunning fans registered in specialized forums.

As we see, the result being the same in both cases, the consideration of whether it has been good or bad varies. It is the job of the marketing manager who will coordinate the campaign to analyze and decide if it can consider success or failure based on previous experiences, initial expectations, etc.

As for the amount of the BBDD a couple of aspects to evaluate, the first if it increases or decreases the number of subscribers (it will indicate the evolution of our list, and the interest of our subscribers) and the second, if it is a BBDD of Third parties, to ensure that the volume corresponds to the real size of the market we are targeting, contrasting it with solvent sources.

For example, if someone offers us a DBD of computer distributors in Spain of 500,000 records, bearing in mind that the Ministry of Industry indicates that the number of companies in this sector is about 30,000 because it is clear that something does not fit, or have many Mails repeated in each company of positions without power of decision, or many old mails that no longer exist or really is not well segmented.

NUMBER OF MAILS REBATTED OR FAILED

We put this parameter the second although it could be thought that is a data to analyze after the shipment. In fact if we use a system of sending that as www.mailrelay.com allows to analyze our BBDD comparing it with a registry of failed mails already localized, we must take advantage of it and to check the percentage of bounces before sending to have a feedback of the quality of the same . Starting from a 10% of failed mails indicates that the BBDD is not well updated, it may be old or worse to have invented mails. It will also be advisable to check the bounces after the shipments to know possible problems that have occurred at the infrastructure level or to know the new ones detected.

SPEED AND SHIPPING STATUS

If we need the campaign to come out within a certain time, for example from 10 am to 12 a.m. or before a date, we will have to make sure that the mail provider is able to launch it with sufficient speed and without being blocked. It will be interesting also to be able to check in real time that the shipment is going out, to see openings, rebounds, clicks, etc. This is an excellent method to locate possible problems and to be able to correct them in time at the moment avoiding the horrible feedback of the day after:? … ups as there was a problem and in the end did not leave the shipment ?.

RATIO OF OPENING AND VISUALIZATION

As we have already commented before eye with this data that has trick. It is the most used to verify the success of a campaign but in reality given that we can not know if they open us to read our offer with fervor or to send us to the moment to the trash we must combine it with other metrics. Also technically not 100% reliable, many mail clients block the tracking images that allow this parameter to be obtained.

If it will be useful as a warning to locate possible problems once we have already made several submissions. If we normally have a ratio of 25% of openings and in our last newsletter we have 5% something has happened that needs to be reviewed. It will also allow us to check the effectiveness to encourage the opening of different issues of bulletin under equal conditions, but we insist, be careful to rely solely on this parameter to give an opinion or report on whether the campaign has succeeded or not.

CLICK RATIO :

This one is 100% reliable and therefore we must pay close attention. In equal conditions we will have to compare the clicks that have received each newsletter to know if the variation of designs, offers, etc., have improved the results regarding other shipments.

Given the importance and usefulness of this metric it will be very interesting to encourage it by trying to orient our designs of newsletters to which the receiver should click in some point of the same to carry out the action that we want to obtain, be it a sale, a communication, an invitation to an event , etc.

CONVERSION RATIO

Once the readers see our newsletter, and click on the links, they will be taken to landing pages (landing page in English) where they will have to take some action, either to buy a product, to register in our site, to leave a comment etc.

It will be critical to know what percentage of the total number of subscribers to which the newsletter has been sent and the total number of those who have clicked finally perform the action to be able to compare it with the different modifications we make to improve it and increase the total conversions since In the end this will be the only data that really indicates if we have achieved the target marked.

INDIRECT CONVERSIONS

We must not forget to control the conversions, purchases or answers that we are going to obtain thanks to the bulletin but not by the official channels. For example, there may be subscribers who do not take the required action directly by the newsletter link, but rather enter our website, telephone, etc. Putting systems to get these metrics and adding them to the total conversions will be useful to have more reliable data on the impact, effectiveness and real costs of email marketing action.

COST OF CLICKS AND CONVERSIONS

Finally the data that interests to be able to say if a campaign has been profitable and to compare it with other means and actions.

SPAM NOTIFICATIONS AND UNWANTED MAIL

If we have a provider like mailrelay.com that has agreements signed with major ISP providers like hotmail, gmail, etc we can have a report that subscribers click on spam. It will be useful to check if our design and offer is attractive to subscribers or to verify the actual quality of a BBDD.

DEVICE AND OPENING CLIENT

Knowing if the newsletter opens with smartphones or with certain mail clients will allow us to make customized designs for groups segmented within our BBDD.

GEOGRAPHIC LOCATION OF SUBSCRIBERS

This metric can be linked to that of the conversion ratio, and we will know in which locations our campaign is being more profitable. Also interesting for possible local deals.

EXAMPLE OF STATISTICS SYSTEM

In the following link , in the statistics section, we can see an example of an email marketing statistics engine with all the necessary metrics: openings, clicks, location, opening device, mail client, etc.

CONCLUSION

It is clear that email marketing allows us to have a multitude of useful data well beyond the mere number of newsletters. Finally, indicate that, like all metrics, this data should be used to help make decisions, to detect possible previous problems, campaign strategy planning and possible technical modifications or newsletter design. If this analysis and subsequent action we will simply have a nice report with many color charts.