RPI (Revenue per Impression), sometimes called profit per impression (PPI) is a good testing metric to use for ecommerce accounts or accounts with variable checkout amounts.
The difference between RPI or PPI isn’t in the metric calculations within your PPC account. The difference has to do with how you are passing data to your AdWords account and if you are using ROAS or ROI in your data, which we’ve previously covered.
In this article, instead of constantly saying revenue/profit per impression (depending on how you are passing data) – we’re going to be consistent and just use RPI and revenue. However, if you are taking out the cost of goods (or don’t have any hard costs) before you pass your revenue data to AdWords; then you can substitute the word profit instead of revenue throughout this article.
RPI (revenue per impression) is a metric that shows you the ratio between your impressions and the amount of money you make. This is very similar to conversion per impression (CPI) with the exception that we are adding actual revenue into the equation and not just using conversion data.
When you consider ad testing, which combination is better?
- A high CTR and a low conversion rate
- Lots of people click on your ads, so your page gets a lot of visibility, but not many of those users turn into customers
- A low CTR and a high conversion rate
- Not many people click on your ads, but of those that do, many of them convert
- A high conversion rate, but the average order is low
- A low conversion rate, but the average order is high
It’s impossible to say which is better since that information relies on three different metrics: CTR, Conversion Rate, Revenue (or RPS – revenue per sale).
When to use Conversions instead of Revenue
When you have variable checkout amounts, instead of using conversions, using revenue gives you a more accurate picture of how much money you are making and lets you accurately determine ROAS and Conv. Value/Cost. For items that are consistently sold – this is the best metric in most cases to use as its your actual sales data.
There is a time when using CPI or plain conversion data is better than using revenue in your testing and management: when you have random outlier sales that skew the data drastically and are not repeatable.
For example, an early ecommerce client of ours makes about 300 sales a month. Their average sale is roughly $500. However, of those 300 sales, roughly 10-20 of them are for orders that are over $10,000. Month over month – they get 10-20 high value orders that are much higher than almost any other sale on their site. The ads and keywords that bring in these sales are never the same month over month. The fact they will get a sale from a keyword or ad is predictable; however, the amount from the sale is unpredictable. Therefore, using revenue for bidding or ad testing metrics is a bad idea since the data one month will not be consistent with the data the following month. However, since the fact they will get a sale is predictable, just not the revenue from the sale, they are best off to use CPI (conversion per impression) in their ad testing and bid management.
Another exception is when you want the most customers possible regardless of their checkout amounts. For instance, if you are trying to build a customer base then you would be happier with 1000 sales at $10 ($10,000 in revenue) than 500 sales at $30 ($15,000 in revenue). This is also an exception case and not the common management for most companies.
Outside of those edge case scenarios, if you are in ecommerce or have variable checkout amounts (such as a hosting company, domain name, or even consulting packages), then using your actual revenue allows you to maximize your ad testing towards higher revenue and not just conversions.
We should understand that measuring revenue and what you are actually making is more important to most companies than just measuring conversions. As your ads can affect average order value, upsales, cross sales, etc – you want to measure how much ads are actually making you and not just how many conversions they are bringing to your PPC account.
The question for most people is: why should we measure from the impression?
Why Measure From the Impression?
If you think about it, every time your ad is displayed – you have a chance of a conversion. You picked a keyword. Someone searched for your keyword. At this point in time there’s a chance of a conversion. The user must both click on your ad and then convert to receive the actual conversion; but measuring from the impression shows you the total conversions and revenue possible.
How RPI is Calculated
RPI is calculated by dividing total impressions by the total revenue.
RPI = revenue / impressions
It is generally displayed as a currency type. Here are some examples:
|Ad||Impressions||Conversions||Revenue||Average Sale Amount||RPI|
To make this an easy illustration, we used the exact same number of impressions for every ad. Rarely is this the case. However, since we used the same impressions, the highest revenue (ad 4) is the highest RPI (0.84).
This ad is not the highest ratio of conversions (ad 3) or the highest average sale amount (ad 5). Ad 4 is the highest revenue per impression – meaning when ad 4 is displayed, you make more money than any other ad.
If your focus is to maximize your revenue, then you would want to use ad 4 as your winner.
The Advantage of using RPI as Your Testing Metric
The main reason to use RPI is when you want the most revenue possible. As this metric takes into account both CTR and actual revenue, it’s a simple metric that will show you which ad will lead to the most total revenue possible.
Working with RPI
There are times that when you examine the full metrics behind various ads, you might not always pick the highest CPI winners. This usually happens for a few reasons.
- You are struggling with Quality Score and you want to pick a high CTR ad if it leads to similar total conversions in order to raise QS
- In general, the higher the CTR, the higher your quality score will be
- You have a hard cap on how low your ROAS can be and therefore, you have to pick an ad that is over your target ROAS
Let’s take a look at a full chart of data and then examine how we’d pick the various winners (click the chart to see a larger version).
If we just want the most conversions possible; then ad 3 is our clear winner. It receives 15 conversions for every 10,000 impressions. If our goal is the most conversions – this is our winner. However, it has a lower ROAS and RPI than some other ads.
If our goal is ROAS; then ad 1 is our winner. It’s also our highest converting ad. However, it has a low CTR and thus is going to have a poorer quality score than some of the other ads. It has a lower RPI and makes less money than some other ads. This is why ROAS is a good metric for bid management, but rarely for ad testing.
If we want the most revenue possible, then ad 4 is our clear winner. It’s the highest revenue and highest RPI (because the impressions are equal among all the ads).
A common way to also use RPI, since it doesn’t care about ROAS, is to use ROAS as a filter. For instance, you might have a goal of 500% ROAS. Therefore, any ads underneath that ROAS target can’t be a winner and you eliminate them. Among the ads that are left, the highest RPI would be your winner. If your goal was a 600% ROAS, then you’d eliminate ad 4 and of the ads left, ad 1 becomes the winner since it has the highest RPI among ads with at least a 600% ROAS.
Using Our Data to Conduct our Next Ad Tests
You don’t want to throw away your data for all the losers. You always want to examine it to find other ideas to test. For instance, our highest converting ads are 6 and 1, and even ad 3 is higher than the highest RPI ad. Therefore, we’d want to take a look at those ads to see what in them is bringing in better qualified clicks.
We’d want to take a look at ad 5 as it has the highest average order value and see why. Does it have different cross sale or upsell items on the landing page or what about it is affecting average order value.
Ad 2 is a clear conversion rate loser. What about it is bringing in such terrible clicks for us? We’d want to make note of that ad and its idea as a warning in the future that the idea or promotion for that ad doesn’t work well.
Once we’ve examined the data, then we can pause all the losers and create a new ad to test against the winning ad.
When Not to use RPI
The main time not to use RPI is when average order value isn’t a consideration. In those cases, you can rely on CPI as your main testing metric.
Revenue or profit per impression is one of the best ad testing metrics you can use since it is a simple number that lets you see which ad will lead to the absolute most revenue.
The largest downside of RPI testing is that it doesn’t look at account or ad level ROAS goals and if your revenue can vary widely across orders then it can get skewed by outliers. If you have hard ROAS targets, then you can use ROAS as a filter to remove ads that are below your targets and then pick your highest RPI ad as your winner; so many companies should use both ROAS and RPI testing metrics to choose their winners.
The other issue with RPI is that it relies on consistent data. If your orders are highly inconsistent or you have random outlier orders, then CPI may be a better testing metric for you.