Measuring the effectiveness of ad campaigns has always been a challenging task for marketers.
More often than not, we will see marketers trying to back up the campaign performance using metrics, that are readily shown in Google Analytics, such as page views, sessions, time spent, bounce rate, etc.
Sadly, many of those metrics are what we would call, vanity metrics. They are nothing more than a distraction, and are usually non-actionable.
Today, we are going to cover the top 5 metrics you need to know for measurement of ad campaign effectiveness.
1. CTR (Click Through Rate)
- One of the most commonly used metrics, but often misunderstood
- Click through rate is usually low (1-2%), as most users have developed tendencies to ignore ad banners, etc
- High click through rate (>5%) should be investigated for possible fraudulent activities (eg. click farm)
- Shows the attractiveness of the ad itself (higher CTR, higher the attractiveness)
Marketers should not freak out over low CTR or over-celebrate unverified high CTR.
Over time, users have grown to ignore ads shown to them. Therefore, it is perfectly normal to have an ad displayed 100 times, where the users only bother to look at it 25% of the time. And among those who have viewed the ad, an even lower number of users will be actually interested in the offerings.
Always check the data for fraudulent activities (eg. High volume of traffics from India when the campaign is targeted at Singaporeans). Remove the fraudulent data and we will have a more accurate CTR showing the ad performance.
- Shows the effectiveness of a campaign in generating awareness
- Unless the campaign is solely focused on generating awareness, this metric should not be used to judge the overall effectiveness of ad campaign
User/Session count can give us a good gauge on how effective our campaign is at generating awareness. Usually, we expect a spike in user/session count when an ad campaign has been started.
For ad campaigns that are solely focused on generating awareness (eg. startup companies, new products/services, etc), user/session count can be one of the core metric we look at.
But for ad campaigns that expect users to carry out an action (eg. subscription, purchase, form-filling, etc), user/session count will not be as relevant. Higher user count doesn’t guarantee higher sales number.
3. Bounce Rate on Landing Page
- Only useful for landing page that captures user interactions on the page itself
- The lower the bounce rate (as compared to historical bounce rate), the better
- Shows the attractiveness of product/service
A bounce happens when an user lands on the page and left (on the page itself) without interacting with the page.
Therefore, for bounce rate to be calculated effectively, user interactions on the website should be tracked accordingly.
An user can be interacting with the page by clicking a CTA or playing a video. But if those actions were not tracked, the analytics tool will consider him/her leaving the page as a bounce, as the analytics tool did not detect any user interaction.
Bounce rate should be compared with our own historical bounce rate data, simply because, there’s no such thing as a benchmark.
A single-page website that is content heavy can expect a high bounce rate, since users are able to consume all the contents on that single page and not interact with it.
Whereas for an e-commerce website, we should be expecting a low bounce rate as users are expected to browse for products.
4. Conversion Rate
- The most important metric. The higher the better.
- Especially useful for ad campaigns that expect an user to do something
- Shows the overall attractiveness of product/service and site effectivness
Conversion is what we expect users to do after coming through our ad campaigns. It can be making a purchase, subscribing to a newsletter, filling up form, or even playing a video.
Conversion rate will tell us, among all the users who came to our site through the ad campaign, how many of them actually carry out the action we want them to?
If sales is important for us (awareness not so much), then conversion should be the first metric we look at. The other metrics are just there to help us determine what went well or wrong.
There are many possible causes for a low conversion rate:
- Product/Service not attractive to user
- Users having trouble reaching the end goal
- Technical glitch on website (eg. missing button, validation error, etc)
- Unclear instruction to reach end goal
- User fatigue (eg. too much effort required to complete a survey)
5. Cost Per Action
- The amount of money spent to get an user to do something we want
- Include all the cost starting from displaying the ad to user > getting user to land on website > getting user to perform a task
- Shows the overall effectiveness of ad campaign + attractiveness of product/service + site effectiveness
We want to lower the cost per action as much as we can. In order to do so, there are a few areas we can optimize:
- Effectiveness of ad campaign
- Attractiveness of product/service
- Website UI/UX
- Website functionality
- Customer journey to complete an action
Ultimately, we want to make sure the cost incurred for an action is lower than the amount we receive for it.
Determining the effectiveness of an ad campaign will never be easy, as there are so many moving parts and considerations we have to take note of. We not only need a ton of experience, but we must be able to think logically and also understand the ever-changing consumer behavior (both online and offline).
The first step we can take is to start abandoning non-actionable vanity metrics (as much as they are easy and beautiful to present) and start looking at the right metrics given the right circumstances.