Impressions, clicks, CTR: these are all great metrics to have for a campaign overview. And that’s why they’re so popular among marketing teams. But are those enough? And do they really give your marketing team all the information they need to adjust your display advertising campaigns for success? The answer is no. In this article, you’re going to see why surface-level metrics aren’t enough, and which ones you need to keep track of.
While these metrics can give you a quick glance into whether something is going very wrong with your display advertising campaign (or tell you what’s going exceptionally right), relying only on this type of metrics hides a very possible danger: failing to see the real picture. This, in turn, can lead to reaching inaccurate conclusions, which can turn you towards the wrong campaign decisions.
But what are the specific problems marketing teams face when they only focus on basic metrics for their display advertising campaign?
Your display ads might be getting viewed, but are they really seen? Impression metrics don’t equal an ad being noticed or leaving a real impression on your audience. More than that, a clicked ad isn’t necessarily an ad that converts. If you have ever clicked an ad out of curiosity but never followed up with the product or service behind it, you will know that people can click on an ad for many reasons - not all of which lead to conversion. What these examples show is that basic metrics can give a distorted overview of your display advertising campaign, and can’t help in showing you the quality of your audience’s engagement.
Your team’s ads may be stunning - but that doesn’t guarantee they will resonate with all of your audience. Some ad components might be working incredibly well, while others might be driving people away - in the same ad creative! Do surface-level metrics help you understand which part of your creative works? The answer, unfortunately, is no. Which is why more advanced metrics need to be used when your team is looking into the parts of your display ads that didn’t work for your audience, in order to then be able to pivot when needed.
Imagine this: someone looks at your ad without in any way interacting with it. They go on about their day, but your brand has left an impression on them. Later on in the day, they google your product and interact with your website. When this happens, you need to know it. But surface level-metrics can’t reflect that audience behavior. You can see that person saw the ad by looking at impressions, and you can see an unrelated conversion. But the connection in between is completely missed.
Missing part of the user journey is a real danger when it comes to surface-level metrics. Some audience behaviors, like that in the example, aren’t fully reflected, and you miss important connections that your data can’t reflect. This distorts the bigger picture and stops your teams from understanding the impact of your display advertising campaign.
No ad campaign is perfect from the moment it’s created. Your team needs to be able to look at how your display ad campaign performs and optimize when necessary. And effective optimization can only happen when you have the right data and the means to fully interpret it. Surface-level metrics can tell you what is happening to your ad campaign, but they can’t tell you why. And it’s important your team understands the reasons behind your campaign’s behavior, so that they can make the most impactful changes they can.
It’s easy to panic over low impressions and make massive changes to your latest display advertising campaign. Or maybe you decide to optimize for low CPC to save on budget spend. But marketers need to take a step back and look at the reasons behind vanity metrics. The low impressions in your ad campaign might mean that your team has deployed a better targeting strategy this time around. Optimizing for low CPC, on the other hand, could lead to lower-quality leads - which instead of saving on your budget can derail your whole ad campaign.
Surface-level metrics can lead to poor campaign decisions, especially when it comes to marketing spend. Looking into more specialized KPIs can help you understand your display advertising campaign’s performance better, so that you can make more educated decisions.
In a world full of data, it’s easy to feel overwhelmed with the metric options. Align your display advertising strategy to what you’re trying to achieve, then translate those goals into clear, measurable objectives. Only then can you pinpoint which metrics truly matter.
Depending on the industry and your specific goals, the KPIs you choose might slightly vary. But when it comes to building a deep, meaningful understanding of your display advertising campaigns, some advanced metrics consistently stand out. These metrics don’t just tell you what’s happening. They help you understand why it’s happening, and how to react to it.
Let’s dive into the key advanced metrics that every marketing team should be tracking.
Time-in-View allows you to see how much time a person spent viewing your ad. This helps give you a clearer view of true engagement: instead of counting the people who barely glanced at your ad (as Impressions does), you can see how interested your audience actually is based on the time they spent on your display ads. With time-in-view, your team can get a better understanding of the quality of your ads and the impact they have on your audience.
As the name indicates, interaction rate is a metric that helps you understand how often your audience interacts with your ads. This metric gives you a more in-depth view of your display ad’s impact, since it essentially compares the number of interactions to the number of impressions. It’s calculated using a simple formula: dividing the number of interactions by the number of impressions. Interaction Rate can help your team determine which type of ad, visual, or copy, is more compelling to your audience. While absolute numbers don’t indicate much, a rate is a better tool for comparisons and can lead your teams to doing better ad adjustments.
Remember that issue with not capturing your customers’ whole journey? Post-view conversions solve this issue. This is the metric that shows you the conversions where the users had seen an impression but never clicked the ad. Post-view conversions give you a clear view of the user’s journey and help your teams understand the conversion path, so they can effectively optimize the ad campaign when something goes wrong.
Other than the clearly defined KPIs we’ve already looked into, you can use a combination of the more surface-level metrics in order to understand customer behavior and ad campaign performance on a deeper level. Let’s see how you can do that.
It’s very important to be aware of when your ads are starting to tire your audience instead of captivating them. Ad fatigue can show you the part of your audience that has reached that point. Monitoring its rise can indicate at what point your team needs to intervene so ad fatigue doesn’t become a problem to your display ad campaigns.
There are a few ways you can go about monitoring ad fatigue. The simplest one is to monitor CTR and ad frequency at the same time, and see how CTR behaves while ad frequency is rising. If your ad’s CTR is significantly dropping while your ad is appearing to a person more and more, this might indicate ad fatigue, and it’s time for your team to look into it.
Taglab has also come up with an ad fatigue formula, where an ad fatigue index shows you how likely it is for your audience to be suffering from ad fatigue. Ad fatigue is calculated by using Impressions, CTR, and conversion Rate.
Even though changes in brand perception and brand awareness are crucial, there’s no single KPI to track them with. This means you’ll have to get creative to calculate it.
A good way to get a sense of brand perception is to use Google Trends or Search Console to infer brand search interest over time. For that, you’ll need a control group: a pre-campaign segment to use as comparison. You then compare the rate increase (or decrease) in search interest during a campaign to the control segment. This comparison can be a rough indicator of how brand perception has changed due to your display advertising campaign.
Although this isn’t a standard metric, it’s good practice to keep track of time to publish. The process is simple: you set a timestamp for the beginning of your campaign creation, and one for the minute you go live. The period it takes to reach your go-live timestamp is your time to publish.
This metric might not give you data into the success your campaign has with your audience, but it still gives you important insights - this time on how quick production is in your team, helping you determine what changes and adjustments might be needed.
Measuring Time to Publish essentially provides you with a speed-to-market KPI which is important to all your campaigns, but especially vital in time-sensitive ad campaigns like flash sales or seasonal campaigns.
If you want to dive even deeper into which of your ad formats work the best, you can look into creating your own metric - for this blog post’s purposes, let’s call it engagement per format. Essentially, what you do is look at your clickthrough rates per ad format, which will show you whether there is a noteworthy difference among your format outputs. If so, your team can focus on the best performing ones.
For successful display advertising campaigns, you need to keep track of their performance - and that means more than surface-level metrics. Start with revisiting your campaign goals and calculate which metrics will show you how close you are to achieving your goals. Remember to take advantage of the various combinations of metrics, which can give you a better look into the hows and whys of your display advertising campaign. After you’ve interpreted your data, your team can adjust your campaign as needed, but also keep valuable learnings for future display advertising campaigns.
Interested in learning how to interpret advanced metric data to adjust your display advertising campaigns? Here's a quick guide on how to achieve that.