This week we’re featuring everything you need to know about Conversion Rate testing.
This metric is commonly used for testing as the higher your conversion rate, the more conversions you have once someone clicks on your ad. The biggest downside to conversion rate is that it doesn’t take into account how many clicks your ad actually receives.
What is Conversion Rate?
Conversion rate (CR) is simply the ratio of clicks to conversions.
How Conversion Rate is Calculated
Conversions rate is calculated by diving the number of conversions by your clicks:
CR = conversions/clicks
It is generally displayed as a percentage. Here are some examples:
In this case, ad 2 has the highest conversion rate and ad 1 has the lowest.
The Advantage of using CR as Your Testing Metric
There are two main reasons to use CR as your testing metric:
- Get the most conversions possible once you get the click
- When you are using ads to test landing pages
A common landing page testing method is to use two identical ads in an ad group with the exception of the destination URL. If you are testing landing pages, then ad 1 goes to landing page 1 and ad 2 goes to landing page 2.
If you are testing page templates, then you might duplicate this test across several ad group and use multi-ad group testing to aggregate the results across all of your ad groups by page template.
The other reason to use conversion rate as a testing metric is when you want the most conversions possible once someone clicks on your ad. We have to qualify this very carefully as conversion rate has an inherit weakness – it doesn’t care about the volume of clicks.
The Disadvantage of using Conversion Rate as Your Testing Metric
While conversion rate is great for landing page testing, it is not a good metric to use for increasing total conversions from your PPC ads since it doesn’t care about how often your ad is actually clicked (See inside the ad testing metrics CTR for more on click through rate). Consider these stats:
In every case, these ads all received the exact same impressions. Because CTR varies, so will the actual CPC and costs for each ad variation.
The ad with the absolute highest conversion rate is ad test 4 at a 36.36%. However, that ad only received a total of 4 conversions. The ad with the lowest conversion rate, test 5, received three times as many conversions at 12. Because ad 5 had such a high CTR, it received more traffic than the other ads and therefore, it had more opportunities to create conversions. So even though it’s the lowest conversion rate, it ends up with the most conversions.
When conducting ad tests, conversion rate is rarely, if ever, a good metric to use as your sole decision in deciding which ad is best for your PPC account. Conversion rate is a good metric to combine with CTR, which creates CPI (conversion per impression) which will be a featured metric later in this series.
For landing page tests, conversion rate is a good number as landing pages only care about the traffic that reaches the page; the page itself does not attract more or less clicks – it only cares about the user who actually reached your page.
When testing ads, you often want to create minimum data requirements for some of your metrics before you even examine if a test has achieved statistical significance.
These metrics will vary by your testing metric.
When considering conversion rate as your metric, there are three considerations to use:
With minimum data requirements; usually you want every ad in the test to reach the minimum data numbers before you examine the tests.
If you have an ad with a very low conversion rate, then it might take a long time for that test to hit minimum data since the ad rarely converts. Thus you usually don’t want to set a very high minimum data number on the number of conversions every ad must have before a test is valid. In an extreme scenario, you could have two ads with the same number of impressions but one ad has 50 conversions and the other one has 2. If you use a minimum threshold of 10; that test would not be concluded yet as not every ad has hit the minimum thresholds. Therefore, you might want to set your minimum conversions on the low side. Now, this is always tempered by how many conversions you do get a day within an ad group. If you are receiving 1000 a day, then you can use higher minimums, if you are receiving 10 a month, then you’ll want lower ones. However, don’t set incredibly high minimum conversions as it might take a long time to reach minimum data.
As clicks only happen when an ad actually receives clicks, this is also a minimum that you don’t want to set very high as a single low CTR ad can take a lot longer to achieve the minimum data necessary. Often with conversion rate testing, minimum clicks are not necessary to set at all. Please note, if you are testing landing pages, then you would want to set some threshold to ensure that each page did receive a minimum number of visits.
While you should have a low minimum conversions and you might not use clicks at all for minimum data; you want to make sure that you do have some minimum data set so that you don’t see test results before you are confident in the numbers – this is where setting minimum impressions is important.
As impressions are how often an ad is displayed, regardless of its actual clicks and conversions, you do want to make sure each ad had enough chances to attract clicks and conversions before you end a test. The impression metric is that chance for each ad to received clicks and impressions and thus you can dictate how quickly or slowly you achieve test results by setting minimum impressions.
If you have a very high volume ad group, you might set this metric at 1000 per ad. If you have medium volume ad groups, then you might be OK with each ad only receiving 300 – 500 impressions. If you are testing low volume ad groups; then it is usually best to use multi-ad group testing instead of A/B testing to ensure that your ad testing lines can meet your minimum impression requirements.
Combining Conversion Rate with Other Metrics
There are many times that you’ll use two different metrics to determine a winning ad. What usually happens is one metric is a filter that is used to remove ads that cannot hit a certain threshold (such as CPA or ROAS) and the second one is used to determine a winner.
The primary metric used in conjunction with conversion rate is click through rate. In this case, a new metric is created known as CPI (conversion per impression) and as that metric has its own set of advantages and disadvantages, then we’ll examine that metric with its own article.
Some people will first filter ads by CPA and throw out the ads that are above their target CPA and then pick the highest conversion rate among those that are left in order to maximize conversions at or under a specific target CPA. We don’t recommend this since conversion rate doesn’t care about volume (CTR) of clicks as it’s a simple ratio of clicks you do receive to conversions.
Conversion rate is a very important metric – I don’t want to discount its importance as a metric in ad testing. However, since conversion rate doesn’t care about the ratio of clicks at all, it is not a great metric to use for ad testing by itself. It is very good when combined with click through rate.
Where conversion rate is your go-to ad testing metric is when you are testing landing pages and not the ads. If your ads are identical and you are just testing landing pages; then conversion rate will be your primary metric in your testing.
Don’t discount conversion rate as a metric, but unless you are testing landing pages, do not use it as your sole metric for determining ad winners.
If you would like to easily see your Conversion Rates along with other testing metrics, take a look at what AdAlysis has to offer. You can easily see your Conversion Rates along with many other metrics to make quick determinations as to what ad really is the best one to use for your account to ensure that you are hitting your advertising goals.