Google Ads Benchmarks
For United States Startups

Google Ads is one of the leading advertising platforms on US digital ad market. It shares the leadership with Facebook and Amazon.

Click Through Rate
[Average]

Conversion Rate
[Average]

Cost Per Acquisition
[Average]


Marginalia


Google Ads (formerly known as AdWords) is Google’s enormously successful Pay-Per-Click (PPC) advertising system. It is scalable, measurable, flexible. Furthermore, it brings rapid results and can convert better than organic traffic. However, usually, it should be avoided by early-stage startups.

First of all, Google Ads is generally not used to listen but to shout. And unfortunately, yelling louder (spending a lot of money on paid user acquisition) does not always mean people want to hear what you are saying. At this phases of your project (concept, MVP, launch, MVP), instead of spending money on advertising, the team should get out and actually talk with potential customers. In early stages, quality feedback can be just as effective as a few customers. In most cases it's better to focus on M/PF (Market/Product Fit) before coming to Google Ads.

Secondly, it's is not a bootstrapping tool for a lean startup. Google Ads is expensive, in terms of both cash and time. Use that money on building a great product instead. Innovation is cheaper than advertising.

Finally, if your early startup's co-founders don't have marketing background, in all likelihood, your website is not great at converting traffic to users at this stage. This means you’ll be paying much more per user via any paid acquisition channel.

How did I get those numbers? As I’ve been doing marketing since 2000 I’ve had a chance to accumulate big and small data from corporations, small ventures, own startups, open Google crawlers and API’s, white- and gray-hat marketing communities, helpful insights from colleagues. The final actual numbers for the metrics you see are the results of qualitative research. That means, first, I have an average (mean quantitative) values, and then manually match it with expert numbers (median qualitative). If both data fit - we’re good. If expert numbers go out - I adopt Bayes' law and Daniel Kahneman’s methods to balance the data.

Bear in mind, all those marketing benchmarks and startup metrics below relate to the United States market only. Though they can be applied to other T1 countries (US, UK, CA, AU, NZ), these metrics don’t represent traction benchmarks for startups and companies in T2 and T3 regional markets.


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