A few weeks ago, I was running a Google Ads search campaign for a client, which on the surface, looked to be performing really well.
As what they offer is niche, the campaign is made up of mostly longtail, exact match keywords with a strong focus on intent, split across a few ad groups for even more granular targeting and tailored ad messaging.
However, when digging deeper into the data to find out which search terms were driving these conversions, I was shocked to see that a massive 80% of the ad spend for the campaign, and 90% of conversions, were categorised under ‘Other’ search terms.
Obviously, that’s not ideal. Clients want to know which search terms are driving the majority of traffic and conversions. And I found myself unable to answer this question.
What made the situation even worse was that the client went on to tell me that while there had been a lot of conversions, when tracking them through the funnel, it turned out they were low quality leads.
At this point, I reached out to Ginny Marvin, Google Ads Liason on X/Twitter.
Ginny stated that search terms that do not meet Google’s privacy thresholds are aggregated within the ‘Other’ search term category.
To be honest, I find it a bit hard to believe Google is doing this purely to respect user privacy, and instead, is to an extent, benefitting from a lack of transparency to spend an advertiser’s budget as it sees fit, as there are plenty of searches showing in the report with only one or two impressions.
Search term report privacy standards are nothing new – it’s been around since 2021, but this is the first time I’ve seen so much search term data being chucked in the ‘Other’ category. And I’ve found exact match keywords to be getting worse in terms of what ads are showing for when I can see the data in the search terms report.
By not allowing me to review the actual search terms bundled under ‘Other’, I have no idea whether they are irrelevant, and should be excluded. The client stating that the conversions are low quality suggests that the ads are showing for terms not aligned with their product.
Google has been pushing advertisers towards automation – including strategies like broad match keywords with smart bidding – which is fine if you’re a massive ecommerce site that has got money to burn. But this simply won’t work for smaller businesses with smaller budgets, or those which are dependent on more complex, long tail searches with specific intent.
Ginny suggested taking a look at the Search Terms Insights section of Google Ads to understand the themes and categories that were driving activity. However, most conversions were still grouped under ‘Uncategorised search terms’, and some of the search categories did not offer any useful insights, as they were just a single, generic word.
So where does this leave us?
Data privacy is important, and as we shift towards a future without third-party cookies, filling in the gaps is going to become increasingly difficult.
Google knows how valuable data is, and has been investing heavily in AI and machine learning to create models based on aggregated and predicted user behaviours. But it needs a lot of data to be able to do this effectively to begin with. How well this will work for smaller organisations with less data available is yet to be seen.
Ultimately, I feel that SMEs will be at a disadvantage, as they don’t have the budgets available to fritter away money on campaigns that they cannot learn much from, while also not being able to meet the data requirements to utilise machine learning.
