The basis of the comprehensive analysis is the ability to analyze how users act after seeing the ad when you create a display ad campaign, even if they don’t click on it. The so-called post-view analysis allows you to evaluate the display effect of ad campaigns. Today we will describe how to do it and what is the use of it using examples of case studies of digital agency newage.
What’s important to understand is that display marketing is not an approach that expects direct action. Unlike search advertising, in the display marketing approach, we reach out to a “cold customer” who might be not interested in the marketed product at all at the moment of the ad campaign. Our task is to create the demand. You need to realize that the demand may appear not directly after the display and even not after a click on it, but after some time, and that time may be different for each separate case.
Such an effect can be evaluated with post-view analysis. The method of comprehensive analysis allows you to do that because it includes not only post-click actions but also post-view actions as well as display marketing data (audience reach, target audience, frequency, etc.).
At the moment, the post-view analysis can be done based on cookies-matching (linking to the user’s browser). Moreover, now there is a possibility to analyze the campaign’s results through user-ID matching, accounting for the multiplatform effect. The user could see the ad on a smartphone and then make a purchase on a laptop under the same Google account, for example, and now we are able to track that and come to the right conclusions.
By doing only a post-click analysis, you’ll lose a great amount of data that affects the results of the campaign significantly.
While analyzing the data of comprehensive analysis, we can find the answers to the questions of great importance when it comes to planning and placing display ad campaigns:
- What’s the optimal frequency for the campaign?
- Which creative is effective and which is not?
- How often do you need to show the ad to users, how long do they remember it?
- Which platforms/targeting work and which don’t?
- After seeing the display ad, which channel the user takes to find the client’s website: search, direct, ads, etc?
By answering these questions, we’ll be able to multiply the ad campaigns’ success. Let’s take a look at the practical case studies for each of the questions.
When we have the data on frequency, the number of users reached, the channels used by them to come back, and how much each contact costs to us, we are able to answer the question of the optimal frequency for a campaign. In the first example, we can see that it’s important for the brand to implement “loud” campaigns, whereas in the second one, the frequency of over 4 per week, is already less than optimal:
Quite often, the advertiser wants to know which video or creative worked better. Some try to evaluate that by CTR, but this is essentially wrong. Using the data from the comprehensive analysis, we were able to easily show in numbers which banner attracted a bigger audience to the client’s website and with which conversion. We were also able to timely find out that the video, which was used in the TV campaign simultaneously with that, doesn’t have the results so outstanding that it’s worth overpaying. The hypothesis was that the user had already seen the video on TV, and it was enough to show the banner to remind them of the ad campaign. However, in this case, we were able to optimize the client’s ad campaign by more than 30%.
You can stop guessing which of the banners will work better: it’s enough to launch a pre-test, receive the statistics and leave the one that has better results.
How often do you need to show the ad to users?
This is how the users react to your ad during an exact period of time:
When you have this data, you can make the conclusions about when the users forget about your ad and when it’s worth it to show it again.
Optimizing your platforms and targeting
Of course, not all platforms and targeting work, of course, you can trust the “description” of the targeting and believe the seller, however, according to our experience, it doesn’t always work, and you need to check dutifully which platforms, targeting and audience segments do work. You will be very surprised by the fact-based results.
It’s greatly important to remember: there aren’t any platforms or targeting that work for everyone. You need to analyze and check the data in each separate case.
Optimizing by the channels
What is also important to remember is that the display ad only creates the demand – the performance campaigns should be able to meet it. To evaluate that and build an attribution map, it’s essential to download the data on users reaching the website after seeing the display ad and which contact chain is the most effective.
To conclude, the first and foremost thing – it is important to check the post-view data when you analyze display campaigns. With this data, you will be able to answer many significant questions when planning and optimizing ad campaigns. Earlier you needed expensive focus groups and field research to answer those questions, but now it’s possible to receive these analytics on a live campaign and check your hypotheses and settings effectively.