Google Ads cost figures: a sources check

You’re planning a budget and need one number: what does a click cost with Google Ads in Germany? After ten minutes of research you have four answers. €1.32. Roughly €1 to €2. €1 to €3. €2.60. All four sit on German websites today, all four are framed as a cross-industry average for Germany, and behind none of the four is a study you could actually go and read.

This isn’t a dispute between statisticians. This number is the multiplier in every budget plan: click price times clicks needed equals ad budget, and the difference between €1.32 and €2.60 is the difference between a plan that works out and one that’s empty after six weeks.

So I sat down and read through these sites on 30 August 2026 and wrote down what stood next to each number. Every site is linked, so you can check everything yourself.

One thing I mean seriously up front: this is about numbers and sourcing, not about providers. I’m only describing what a page showed at the time I checked it. How those numbers came about, or what anyone intended by publishing them, I don’t know, and it isn’t necessary for the point either.

Four numbers for the same country

Start with the finding that jumps out at anyone who reads two guides back to back.

€1.32. braverytechnology.com writes: “The average Google Search CPC in Germany is €1.32 (as of Q1 2026). In Austria it’s €1.18, in Switzerland CHF 1.68.” The same figure appears on wirgesdigital.com: “The average click price (CPC) in Germany is €1.32 per click (Q1 2026).”

Roughly €1 to €2. selbststaendigkeit.de writes: “A rough guideline: the cross-industry average CPC in Google’s search network in Germany runs around €1 to €2.” This site at least names the uncertainty of its own figure in the same sentence, which is more than most do.

€1 to €3. galineo.com lists “€1-3” in a metrics box labelled “Average CPC DE”.

€2.60. adpoint.de states an “overall average across all industries” of €2.60 in search.

Between the two precise figures sits nearly a factor of two, for the identical question and the identical country. Between their timestamps sit roughly two years: only one of the four figures names a quarter at all, the €1.32 (Q1 2026). The €2.60 is, according to its own chart, from April 2024, and the two ranges carry no time period at all. Two of the figures are precise to the decimal point, which normally implies someone did a calculation. What was calculated isn’t stated on either page.

I’m deliberately not claiming any of these numbers is wrong. I can’t know that, and that’s exactly the problem. A number with no stated origin can be neither disproved nor confirmed. You can only believe it or not.

What’s actually behind “WordStream DACH benchmarks 2026”

The more interesting case isn’t the number with no source. It’s the number with a citation, because that one puts you at ease.

On adkontakt.com, the same citation appears eight times, worded identically each time: “WordStream DACH benchmarks 2026”. For example: “The average CPC in Germany in 2026 ranges from €0.30 in e-commerce to over €12 in legal services, as the WordStream DACH benchmarks 2026 show.” And elsewhere: “CPCs rose in 2025 across 87% of all industries (source: WordStream DACH benchmarks 2026).”

That sounds like exactly what the German market is missing: a named study with a regional scope. So I looked up what WordStream itself publishes.

WordStream belongs to LocaliQ, and the benchmark report sits at localiq.com (checked 30 August 2026), marked “Last Updated: June 1, 2026”. The report describes its data basis like this: “In partnership with WordStream by LocaliQ, we’ve dug into the data from thousands of our customers’ advertising campaigns across Google Ads and Microsoft Ads to create search advertising benchmarks for the top 20+ industries.”

What’s not in that description is any geography: no country, no region, no continent. “Germany”, “German”, “DACH”, “Europe”, “Austria”, and “Switzerland” don’t appear anywhere on the page, nor do “global” or “worldwide”. “USA” appears three times, every time as part of the publisher’s name, USA TODAY: twice in the navigation, once in the copyright notice at the bottom, never in a statement about the data. The stated average reads: “The average CPC for search advertising across all industries in 2026 is $5.42”, in dollars. Per industry, the page lists four figures: click price, click-through rate, conversion rate, and cost per lead.

Stated precisely: this page does not publish a DACH average. Whether LocaliQ can break the data down by country internally, I don’t know and I’m not claiming either way. I’m only noting that the citation, at the point where it’s publicly visible, carries no regional label at all.

And then the same name travels one step further. On wirgesdigital.com, the same name backs up an entirely different kind of claim: “And according to the WordStream DACH benchmarks 2026, advertisers without a clear strategy waste an average of 37 percent of their Google Ads budget.” A share of wasted budget isn’t among the four figures the LocaliQ page reports per industry.

€6.75: the same number, two meanings

The third case shows what happens to a number once it’s in circulation.

A table on adpoint.de lists an average search CPC of €6.75 for “legal and consulting”, next to finance at €5.60, health at €4.80, and the overall average of €2.60 already mentioned. As its source, the page cites: “the chart ‘CPC comparisons by industry’”, which sits on the same page. On origin, methodology, sample, or collection period, the whole page says nothing; “as of” appears on the page only inside the German word for “location”. The only timestamp anywhere belongs to the chart itself: “Average cost per click (CPC) in Google Ads in Germany (as of April 2024)”. The one dated figure on a page read as a current industry comparison is thus over two years old.

The same number appears on a second domain. corominas-consulting.de writes: “With average click prices of €6.75 to €18.50 for legal search terms, the legal market is among the most expensive advertising segments in Google Ads.” Here too, neither a publisher, a sample, nor a time period sits next to the number.

What’s notable isn’t that 6.75 shows up twice. It’s that the number changes meaning in the process: on one page it’s the average for an entire industry, on the other it’s the lower bound of a range that reaches up to €18.50.

How that happened, I don’t know. What I do know is how easily a shift like this occurs: a table row is an average, and in someone’s own running text that quietly turns into a “from”, because it feels more cautious. For you as a reader, though, the difference is substantial: an average and a minimum are two entirely different things. If you’re budgeting with €6.75, it makes an enormous difference whether half your clicks land above it, or all of them do.

Whether one site copied from the other, I don’t know and don’t claim. Both could have drawn independently on the same original value. Only, which value that was, neither page says.

How a number becomes a source

The mechanism behind this is unspectacular, and that’s exactly why it works so reliably.

Step one: a page publishes a number with no stated origin. Not secretly, usually just because nobody expects a footnote in a how-to article.

Step two: the number becomes citable, because it’s sitting somewhere. On wirgesdigital.com you can read this step happening in plain text today. Above its industry breakdown it says: “The following ranges come from a combination of the WordStream DACH benchmarks 2026, the Adkontakt industry analysis 2026, and Google’s own auction data.” The same two benchmark sources are named again in the sources block at the end. So a page that backs its own figures with “WordStream DACH benchmarks 2026” has itself become the named source for another page.

Step three: the chain becomes unreadable. braverytechnology.com runs a “Sources” block at the bottom with seven entries: the Alphabet Q4 2025 annual report, WordStream Google Ads benchmarks 2026, Search Engine Land, eMarketer, Google Ads Help, Optmyzr, and BVDW. Only, no single figure is tied to a single entry. The country figures for Germany, Austria, and Switzerland sit in the running text; the sources list sits as a block below. Anyone wanting to know exactly where the €1.32 comes from can’t determine that from this page.

A sources block at the bottom of the page is popular for exactly this reason: it looks like evidence and costs nothing in terms of actually attributing anything.

On selbststaendigkeit.de you can see both directions side by side. The page uses inline markers and has a section titled “Sources and references”. Two of the three entries are complete: Google Ads Help on the ad auction and on daily budgets, each with a support.google.com address. The third entry, the one behind the CPC ranges, reads: “Google Ads industry benchmarks 2026, typical CPC ranges by industry (Germany); figures vary regionally and seasonally.” No publisher, no address. So of three source citations, two are traceable to the original page; the third, the one behind the cost figures, ends at a name.

At the end of this chain sits a number that gets cited everywhere and starts nowhere.

And what I couldn’t verify

An honest sources check also has to say where it hit a dead end itself.

In a lot of discussions about German click prices, a Statista dataset on cost-per-click by industry in Germany comes up. I never got to see it on 30 August 2026: the page kept redirecting me to a login and back to the start, without ever showing the dataset. So I haven’t seen it and can’t say anything about its contents.

What I can say: the dataset’s title in the search result reads “Google Ads - Cost per Click by Industry 2021 | Statista”, so the year 2021 sits in the title. That detail comes from the search result, not from the page itself. Anyone wanting to rely on it needs to open it themselves.

That leaves the finding at this point more modest than it first stood in my notes. That’s the right kind of rigour: what I couldn’t verify, I don’t cite as evidence.

Five questions for any cost figure

The practical part. These five questions apply to any cost figure you come across, mine included. They don’t need expertise, just the willingness to look briefly.

1. Over what period was this measured? A click price with no collection period isn’t a measurement. Google Ads auctions shift significantly by season; a figure from the run-up to Christmas doesn’t describe February. If no period is stated, you don’t even know if the number is from this year.

2. How large is the sample, and what does it consist of? Ten accounts or ten thousand campaigns is a massive difference, and “accounts” and “campaigns” aren’t the same thing either. Without this detail, you can’t judge whether an industry row rests on a single advertiser.

3. How was it calculated? A simple average across industries and a cost-weighted average across clicks produce different results from the same raw data. On top of that: were paused campaigns excluded? Is there a minimum click threshold before an industry is even reported? Without these rules, the number isn’t reproducible.

4. When was the number last checked? Not when the article was published, but when the data was collected. A 2026 article can easily carry 2021 values, and the year in the title says nothing about that.

5. Can I get to the raw data? A downloadable table, a change log, a stable address. If the answer is no, the number isn’t a dataset, it’s a claim with a decimal point.

And the rule of thumb: if three or more of these five questions go unanswered, the number is a ballpark, not a figure to calculate with. It can tell you an order of magnitude. You shouldn’t build a budget on it, not without treating the first few weeks as what they actually are: the real measurement.

My own numbers are a sample too

The honest conclusion has to apply to my own numbers, or this article would be exactly what it criticises.

The click prices I publish come from a small number of accounts I manage myself. That’s a sample, and a biased one: these are actively optimised accounts, not a random sample of the German market. Behind some industry rows there are one or two advertisers. The real market average is probably higher than my figures, because a well-run account buys more cheaply than a neglected one. And it’s a single measurement point, not a time series: “click prices rose by X percent” is a claim I can’t back up today.

The difference to the numbers above isn’t that my sample is better. The difference is that everything sits right next to it: period, number of accounts, number of clicks, calculation rule, minimum threshold per industry, collection date. You can not only read my numbers, you can put them in context, and if the sample is too small for you, reject it with reason. That’s exactly what those details are there for.

The dataset with methodology, change log, and download sits at Dataset: Google Ads click prices DACH (in German).

If you need a starting figure for a budget plan: the account-data analysis is in the report Google Ads click prices 2026, the industry breakdown is at what Google Ads costs, and the broader view across all channels is at what advertising costs. The cost hub by industry sits at Google Ads costs (in German).

And if you come across a number somewhere and can’t get answers to three of these five questions: that’s not a minor detail you leave to the experts. That’s the difference between calculating and guessing.