Measuring incremental impressions, clicks and conversions for Paid Search (Methodology + Google Sheet Template)
Measuring incremental impressions, clicks and conversions for Paid Search (Methodology + Google Sheet Template)
Paid Search has a risk of “cannibalising” Organic Search. I cover how to measure incrementality for this strategy. (Includes Google Sheet Template)
What is incrementality and why it matters for your CAC
Incrementality measures the additional outcomes—be it sessions, conversions, or other metrics—that result from a specific marketing strategy. They’re the outcomes that wouldn’t have happened if a user or lead hadn’t been reached by your marketing campaign.
Measuring incrementality is necessary to understand your true CAC. Google Ads might say your CAC is $10, but if half of those users would have converted anyway, then that’s not quite right, is it? If you’re interested in reading more about incrementality, head to this article.
Paid Brand Search: the biggest risk to the “cannibalisation” of Organic Search
The value of Paid Brand Search beyond brand protection
We’re defining Paid Brand Search as Search ads you serve on your brand terms. We also include in this definition permutations of the brand name (e.g. “shopify pricing”, “shopify dropshipping”, “shopify v square”) and typos (e.g. “shopifi”).
There are a few reasons companies will choose to serve ads on their own keywords, among them:
Brand Protection: The most common reasoning is to avoid competitors from bidding on their brand terms. And this is a risk with considerable consequences. An existing user could churn to a competitor (that maybe they hadn’t even heard of previously) or a lead in consideration change could pick a different brand.
Landing Page: In paid ads, you control the copy and the destination URL. This can be very valuable if a custom user journey (e.g. taking users to the pricing page or a targeted prisoner page) drives a higher conversion rate. This is leveraged with frequency by brands, since users searching for brand terms are usually lower down the funnel. Shopify, for example, takes users to their Free Trial page on their paid ad.
Cheap CAC: Let’s be honest, a lot of agencies and paid media professionals out there run Paid Brand Search as a way to decrease their blended CAC and hit their targets. Paid Brand Search reaches users close to conversion and it’s easy for traditional click attribution to measure. Win/win (except for the actual advertiser).
A net negative strategy, but how much net negative?
There’s a risk in not running Paid Brand Search and, in certain cases, it can even drive customer value. But because a lot of brands usually rank #1 organically for their brand name, it leads paid search results to compete directly with organic results.
For example, if Shopify wasn’t running Paid Brand Search, they’d still rank #1 with their homepage. The second and third results are Shopify’s: it’s their official social media accounts.
That’s why Paid Brand Search is generally a “net negative strategy:” its incremental conversions (additional outcomes) are lower than its attributed conversions (as reported on the ad platform and/or website analytics).
That’s why Paid Brand Search is generally a “net negative strategy:” its incremental conversions (additional outcomes) are lower than its attributed conversions (as reported on the ad platform and/or website analytics).
In order to define how much budget to allocate to Paid Brand Search and the target / ceiling CAC we’re willing to spend, we must first measure the strategy’s incremental results.
The different methodologies for measuring incrementality
Incremental clicks: calculating the difference between high spending and low spending periods
Google has previously conducted and shared a study on how to calculate “Incremental Ad Clicks” (IAC). The methodology consists of:
Increasing or decreasing Paid Brand Search during a certain period.
Comparing clicks from organic search terms (via Google Search Console) and paid search (Google Ads) from the high and low spending periods.
You can download the PDF of the study which contains the statistical model right here on my Drive.
Incremental conversions: using blackout regions or Marketing Mix Modeling (MMM)
Calculating incremental clicks and impressions is a lot more straightforward than calculating incremental conversions. But with just the former, you can’t measure the impact of:
Competitors could be driving clicks away, but are they succeeding at converting “my” leads? At what scale?
What’s the impact the custom user journey has on the conversion rate? Does the lift offset the cost?
There are multiple methodologies for calculating incremental conversions. These methodologies can measure the incrementality of both Paid Brand Search and other marketing strategies (e.g. OOH, social ads, etc).
Running ads only in a certain location, for example in a list of Zip Codes or in a specific country. Meta’s Geolift open source model calculates incremental conversions in this manner.
Using an open source Marketing Mix Model (MMM). Google launched Meridian this year and Meta’s Robyn is one of the leaders in the field.
For both the options above, you will likely need support from your data team. An out-of-box solution can be:
Singing up to an MMM tool. There are multiple providers out there. I’m on the advisory board of Paramark.
Visualising incremental impressions and clicks with Google Sheet Template
I recently had a client where I grew their (attributed) Paid Search conversions by 10x but we were seeing no uplift on their bottom line.
When I compared data from Google Search Console and Google Ads, I could see it as clear as day. Most of the clicks that were now being attributed to Paid Search were coming on the back from Organic Search.
I created a Google Sheet Template that visualises both Organic and Paid impressions and clicks in one trend line. All you need to do is make a copy, follow the instructions and paste in your own data.
Needing to up your paid media performance?
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I also work as an independent marketing consultant, helping brands like WeTransfer and Microsoft improve business results with data. Head to my website and reach out if you want to talk measurement projects.