© 2019 by Digital Marketing Hub  

    • Wirya Hassan

    How To Measure The Success Of An Email Campaign

    Email campaigns are used increasingly by more and more organizations as an important channel within the online marketing strategy. The fact that the use of e-mail as a marketing

    channel can bring great successes, is something that I will not argue in this article.


    However, a common question is: what is that success? And how can we measure whether an email campaign is successful?


    You see more cases and results appear in the market. Think of enthusiastic LinkedIn posts or cases, with full enthusiasm:


    The e-mail campaign achieved an open rate of 60%!


    You often do not read further substantiation if this really contributed to your organization and marketing objectives. That is why in this article I present a number of tips and steps

    on how you can really know and test whether your e-mail marketing is successful.


    Step 1. Think both before and afterwards what you want to achieve


    The success of e-mail marketing is often connected to well-known terms such as COR (Open rate), CTR (Click through rate) or CTO (Clicks / Opens). Comparisons are then made with benchmark averages, but what does this exactly say?


    Of course you know as an e-mail marketer that an open rate of 60% is not bad if your goal is for people to see a certain message. It can be an indicator, although it is still difficult to determine whether people will click immediately in the email after opening. So it's all about your set goal and whether you achieve it.


    It is much more important to always think about your goals beforehand. So ask yourself: why am I going to do this campaign? Or why am I going to send this e-mail? A number of

    examples of e-mail campaigns that you can prepare in advance are:


    • I want to achieve more sales in my online store

    • I want people to read the underlying article or page on the website

    • I want my existing customers to repeat purchases

    • I want to create more engagement


    It may sound like an open door, but it is very important to map out these objectives in advance and also to be thoughtful of the choice for your email strategy and campaign.

    Step 2. Make your goals measurable


    Cries like: "We want to create more engagement" or "We want people to repeat purchases more often by e-mail" are in my eyes sometimes meaningless. I often notice that not

    enough thought is given to:


    1. How you will make this happen.

    2. How you will make this measurable.


    Consider carefully whether and how you can make the objectives measurable. A commonly used method is to define them 'SMART'. Is the target too broad or difficult to measure?

    Then try to divide your objective into smaller sub-goals!


    With SMART goals, try to realize that you know what you want to achieve with your e-mail campaign, in which way, in which timeframe.


    Take as an example the stated objectives from step 1, you can define this in a different way. You can then better check afterwards how you scored and compare your goals.


    Below are four examples.


    "I want to generate more sales in my online shop."


    "Within three months the turnover, obtained directly from an e-mail campaign, must be at least 30% higher than it is now."


    "I want people to read the underlying article or page on the website."


    "From the specific e-mail campaign, at least 30% of the email list must remain on article X of the website for at least 1:30 minute."


    Step 3. Work out your measurement plan


    If you have defined your goals measurably, you will consider in the next step how you will actually do that measurement. In some cases this will be very simple for objectives, for example:


    We want to ensure that at least 10,000 people click through the e-mail on the article, who remain on the website for more than 2 minutes.


    With the above objective you must therefore ensure that you can recognize in the website analytics which people come from the e-mail and that you can map this.


    A common method for this is adding UTM tags. These are collected in, for example, Google Analytics . This allows you to chart reasonably black and white (with some basic

    analytics skills) whether you have achieved your e-mail objective.


    You can also work out much more complicated measurement plans. An example that I have seen a number of times recently is:


    We want the repeat purchases to increase by 20% by sending e-mail campaigns.

    In many cases, people assume that an e-mail campaign is successful if, after launching the campaign, sales figures increase.


    A/B testing

    But this is a bit more complex. On the one hand because you can never simply attribute the sales success to one specific campaign. You do not know whether someone who makes a

    purchase from an e-mail did not make this purchase anyway. A good method to test this is the well-known A/B test, but how do you implement it? Below are a few sub-steps

    that you can use to map this process.


    (In the example below, for convenience, I assume that you have an e-mail address for all people who have made purchases and that these people also have an opt-in.)


    The above is of course only an example. But usually the best way to measure real effect is by using a control group. There are so many factors that can cause an effect, that you can never fully say with certainty that increases in sales or visits are directly attributable to a specific email campaign.


    Questions that can be taken as a guideline for yourself:


    • Are there any other events / events that may have caused this?

    • Does the period in the year (month or season) affect the results?

    • Could this result also occur if I had not done an email campaign?


    Of course, a control group does not always have to be 50%. This can also be only a few percent in the case of processes that have been tested well, if it is only a representative group that relates to the test group.


    The size of a control group is therefore not necessarily fixed. It is important, however, that the proportions and distributions within both the test group and the control group are equal, whereby the risk of coincidence is also excluded.


    Step 4. Make sure you have a quick and clear overview of your figures


    If steps 1 to 3 are properly mapped out to an organization, you often see that the actual measurement or analysis is not done or only happens much later. For example, if an

    organization wants to see the results retrospectively at the end of the quarter or a year. A data analyst is working at that moment and all sorts of analyses are carried out.


    Often the results come as mustard after the meal and at that time (e-mail) marketers have moved on and been working on new campaigns for a long time.


    Ideally, you want to map this naturally and at the appropriate moment, so that you can immediately get insights into your email campaign. Several software programs for email automation already offer nice statistics for this.


    But you also want to map your direct conversion and other figures.


    Real time dashboard

    A nice way to do this is to link everything in a real time dashboard. Here you link your KPIs directly. In this way, the dashboard quickly shows which parts or e-mails are performing well and which are not, so that you can adjust and make interim adjustments.


    Initially, you may be a bit busier with setting up the right links, but afterwards your data analyst does not have to do extensive analysis. And more importantly, you can

    make direct adjustments! Examples of tools that can be used for this are Klipfolio, Tableau or Qliq sense.


    Step 5. Evaluate, adjust and learn!


    If you have an accurate overview of the real results in the meantime, it is nice to be able to process them quickly and make adjustments.


    In the future, this will probably become more and more self-learning, with algorithms immediately recognizing where adjustments are needed and making adjustments.

    Until that time you just want to see as quickly and clearly as possible (step 4) where optimizations are possible, so that you can implement them.


    Always make sure that you leave a part of the target group in the old situation. With this control group you can test whether the optimization really has an effect.


    If your campaign is already over and your results are well mapped, then you can of course still use this data. Make sure you have a clear picture of the plus and minus points

    of the campaign based on your results and learn about it for your next campaign!


    All tips in a row


    1. Think carefully beforehand and define what you really want to achieve with an e-mail campaign.


    2. Provide good comparative material, in most cases this will be a control group.


    3. Look beyond basic e-mail statistics! Your real goal must be leading, the e-mail statistics are just a means to reach your goal.


    4. Make sure that your data infrastructure is well integrated, so that you can be sure that your real results are quickly visible together and in real-time.


    5. If possible, make interim adjustments to ongoing campaigns based on your (interim) results.


    Successful email campaigns always depend on a good marketer.


    Many e-mail marketers will probably think when reading this article: "That's all nice and nice to be able to see the results, but everything falls and stands in a good

    campaign".


    I completely agree with this! In this article, I have completely ignored essential parts of good e-mail campaigns such as content, segmentation and personalization. These are

    of course requirements to achieve good results!


    You can only know if and how you have achieved these results if you have a good understanding of them. In my view, the market here is sometimes inadequate, hopefully these steps provide a good footing.


    Good luck!