Are you looking to make your brand campaigns on Google Ads more efficient?
As a European fintech business, we have used Google Ads as an acquisition lever. Initially, we found success with Google’s target impression share for brand campaigns.
However, in 2023, with profitability as our focus, we challenged the status quo. Our hypothesis was to lower CPCs without sacrificing traffic and conversions.
This article explores PPC campaign inefficiencies and recommends a restructuring strategy. It aims to inspire vital changes to improve efficiency and reinvest savings in new business acquisition.
Challenging the status quo
All queries are not created equal. Moreover, not all keywords cost the same or have the same performance.
Google has been pushing more reach and less control for a few years.
If you activate broad match, it tends to immediately find the competition and position your generic keywords on their brand queries.
If you are doing it to others, chances are that they are doing it to you. Under my assumption, Performance Max will follow the same path.
This has some overall negative effects on brand campaigns:
- Using smart bidding without a CPC max can catch your important brand traffic because we all know Google can put nerve-racking CPCs for any query.
- Just having participants in the auctions increases the winner’s CPC, even if it was highly unlikely that the competitor’s business would have won the click.
- Target impression share on campaign with mixed match types can push CPCs beyond belief because a phrase match can deliver to relatively irrelevant queries, while hitting its objective of 100% impression on all keywords.
Identifying a ‘non-existent’ problem
In search, we can predict our performance when things are stable, but we do not know what will happen after any change.
We needed a mix of two things to bring this project to life: data and faith. Data is the easiest to find, faith is not.
People love to pretend that search can be scientific. Still, when you drop your numbers into a statistical model, most of the time, it cannot take into all the exogenous and endogenous factors impacting an account.
Nevertheless, we shouldn’t be stuck in the inertia due to data dependency. Sometimes you must be bold.
Conducting the analysis and proposing the project
Our team extracted all the brand keywords by week with all the typical KPIs (i.e., impressions, clicks, cost, conversions) and competitive metrics (impression share, overall top of page and first position) click share.
Creating all the necessary calculations and re-calculations in Excel, enabling use to segment the data however we wanted.
CPC = Cost / Clicks
CTR = Clicks / Impressions
CVR = Conversions / Clicks
CPA = Cost / Conversions
Impression share metrics are a little trickier because they are already averages that need to be transformed into brut calculations before being recalculated in a pivot table.
By convention, we multiply impression share metrics by impressions then divide the calculation by impressions once the pivot table is created.
We immediately recognized two categories of keywords.
- Low CPC and low CPA (CPCs relatively high for a brand campaign)
- High CPC and high CPA (CPCs close to generic campaigns)
Both had 99% on all impression share metrics. We noticed that the second category had a performance CPA closer to generic keywords than the first.
This gave us hope that could improve overall ROI. However, we were not able to estimate the ROI increase. We rounded up all the necessary decision-makers, are made our case.
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Proposed solution: Splitting the campaigns into two and providing a relevant strategy.
We decided to split the two categories into two campaigns. This would enable us to optimize CPCs on the better-performing category while transforming the second category into a performance campaign using a conversion objective smart bidding.
Not wanting to ruin all the historical data, we kept the first category in the same campaign, while creating a new campaign for the second category.
We kept the target impression on the first category; however, we did reduce it to 95% and setup a Max CPC. On the second category, we used the average 30-day CPA for the initial setup and created a single campaign portfolio tCPA strategy with a max CPC.
Improving ROI and while saving thousands
Results were immediate. Our CPCs in the first category dropped by -73%. We did not lose and competitive metrics except for 1 or 2 percentage points (which have remained in the above 95% range since the change).
For some reason, Google was making us pay more than we should have paid otherwise, even with the same target impression share strategy. The second category also saw improvements.
Our CPCs dropped by -31%. However, we did lose about 7 percentage points in the click share. This was predictable because we aim to drive conversions on this campaign and not clicks at all costs.
Google must have stopped positioning on some audience’s search queries. For the second category, we often use the bid strategy simulator to measure the cost of incremental conversions.
We are currently set at a comfortable level, although Google does estimate that for a mind-blowing tCPA we could generate 2-3 more conversions. Our returns would soon be falling off a cliff if we were to capture all the traffic.
Lower CPCs, higher conversions on Google Ads
This has already enabled us to increase our new business acquisition budget directly. Think about spending 75% less on your brand keywords a week, a month, or a year.
Depending on the size of your business the savings could be astronomical. We amust now get ready for the new world, where brand queries are no longer our safe place.
We must learn to use smart bidding to our advantage, but also stay critical about what is happening to search across the board.
As PPC marketers, we must remain loyal to our job, improve performance by any means necessary, no matter the company, the client, the platform, or the so-called best practices.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.
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