The Opera Browser Is Carving Out An Advertising Business Without Cookies

Browser company Opera often takes its cue from Mountain View.

So, when Google announced in July that it would no longer deprecate third-party cookies in Chrome, the decision could have had ripples all the way to Opera’s headquarters in Norway.

The Opera browser, which has 2.2% browser market share, according to Statcounter, is based on Chromium, which is the open-source code project that also powers Google’s Chrome (of course), Microsoft Edge, Brave and Samsung’s web browser, among others.

Like many other Chromium-based browsers, Opera doesn’t block third-party cookies by default. It’s up to users to block or allow cookies using the options in their settings.

“The developers follow the Chrome road map,” said Per Wetterdal, EVP of commercial for Opera Ads. “But we also follow the broader ecosystem and, even more so, our users, because the most important thing is for us to give them a choice.”

Even so, Opera Ads – the online ad platform Opera released in 2019 – doesn’t use third-party cookies for targeting. Opera monetizes its browser using other signals, including search intent and context.

“So, we are not impacted by Google’s decision,” Wetterdal said.

Since launching roughly five years ago, Opera Ads has introduced a self-serve option for its ad network, its own demand-side platform and a supply-side platform, which it calls Opera Audience Solutions. The SSP includes access to managed inventory across mobile, desktop, CTV, video and audio.

Wetterdal spoke with AdExchanger.

AdExchanger: Opera Ads has been growing, albeit from a smallish base. In 2021, your revenue was roughly $80 million for the full year. In Q3 of this year, you generated $76.8 million, which was more than 60% of Opera’s total revenue in the quarter. What are the main growth drivers?

PER WETTERDAL: Our strategy has been to scale our supply in a transparent and direct way. We have control over inventory at the source, which we package for our demand partners and segment using machine learning.

We have a lot of scaled performance advertisers and we’re seeing growth in verticals like travel and gaming. We’re also benefiting from the retail media trend.

Focusing on performance advertisers also helps us navigate through when the ecosystem experiences slowdowns. Brand budgets are usually what get pulled first, because they’re harder to measure.

When Opera added self-serve access a few years ago, the idea was to bring more demand from small and medium-sized businesses. But you’ve since pulled back on that and started focusing more on big advertisers. Why?

Scaled advertisers have always been a priority for us. We launched our ad manager in an attempt to also attract smaller advertisers by giving them an easy way to move some of the knobs themselves.

But we realized the knowledge gap was probably too big and that it was too hard for them to get it right on their own and see the performance they’d expect.

Also, most SMEs [small and medium-sized enterprises] need to focus on local. They need people looking for things like “restaurants near me,” and we aren’t really tapping into that type of traffic. Our inventory is more suited to capturing user intent and understanding context, which is better for advertisers looking for global reach, especially those seeking alternative channels beyond the usual suspects. We’re seeing success as a complement to the big platforms.

You mentioned intent and context. How does the targeting work?

As a browser, search demand has always been crucial for us, and search is high-intent by nature. We’ve been extending that into other parts of the browser journey and contexts beyond the initial point of research while still capturing the intent of the user.

For example, we rely on machine learning to look at the KPIs of a campaign, which are often performance-based, like some type of conversion event or a target CPA [cost per action]. Then we try to find an audience that can deliver on those campaign goals.

How does the machine learning aspect work?

Beyond looking at classic things, like demographics, we do interest scoring, which is a score of commercial intent, depending on what a user is looking for. Maybe it’s travel or maybe they’re in the market for shoes. Once we’ve captured users based on their intent, we can reach them on and off of our owned-and-operated properties thanks to machine learning.

When we do this with scaled budgets, we can rely more on machine learning, because the cohort is big enough for the machine to start to learn and do the job. Our biggest investment over the last year has been building a performance platform to support larger advertisers and scaling it up to more than 5 million QPS [queries per second].

Confession time: I’m not part of the 2.2% of people that use the Opera browser, but I did download it before our interview, and when I did, I was presented with an option during the setup process to turn on an ad blocker. How do you balance that feature with your advertising business?

That’s been an offering for a long time. We’re a third-party browser that doesn’t have its own ecosystem or operating system with free distribution. We have to fight for every user.

And so we focus on building features and utility into the browser, like adding AI, for example. Another of those features is an ad blocker, although it really is more of an ad filter for ads that detract from the user experience, like aggressive pop-ups.

We decided to offer it as a built-in feature, rather than making people download an extension that might be malicious. We see this as still being compatible with advertising, but it is a balancing act.

It’s about finding that sweet spot between protecting our users, protecting the user experience and allowing people to have access to free content.

This interview has been lightly edited and condensed.