In this episode, Cristina (SVP, Marketing) and Chuck (Front‑end) discuss private marketing at DuckDuckGo, from making decisions with less data to the role of privacy engineers in marketing projects.

Disclaimers: (1) The audio, video (above), and transcript (below) are unedited and may contain minor inaccuracies or transcription errors. (2) This website is operated by Substack. This is their privacy policy.

Cristina: Hi, and welcome to DuckTales, where we go behind the scenes at DuckDuckGo and discuss the stories, technology, and people that help build privacy tools for everyone. In each episode, you’ll hear from employees about our vision, product updates, engineering approach to AI, or how we operate as a company. Today, we’re going to chat about how most companies collect a ton of information through their marketing activities and how DuckDuckGo, given our privacy policy of we don’t track you, do things like attribution very differently.

I’m Cristina, I’m on the marketing team, and today I’ll be interviewing Chuck. Chuck, you wear a lot of different hats. Can you introduce yourself and some of what you work on?

Chuck: Sure. ⁓ I am technically on the front end team and work on the front end of our search projects, our products, and our subscription products. ⁓ But I ultimately do whatever I need to do to get the job done, which is kind of our DuckDuckGo ethos. I do some product management, some data science, back end engineering. I work with the marketers. It’s fun. ⁓ And I need access. So getting to where lots of them is.

Cristina: Hahaha. Fair enough. Well, thank you. So much like our product philosophy, privacy is core to the ethos of our marketing. There are so many common practices we don’t do, identifying and targeting individual users, retargeting, using behavioral data, using third party cookies and pixels, the list goes on. And we’ve also declined working with a lot of vendors because they don’t meet our privacy standards. As a consumer, that’s something I really appreciate.

But frankly, as a marketer, it makes the job very hard. But it’s getting a bit easier thanks to work from people like Chuck, which is why I was so excited to talk to you today. So Chuck, when you first started working with the marketing team, what was your reaction to our limitations and what we were hoping to achieve?

Chuck: Honestly, I was a little shocked. ⁓ There’s a pretty well-understood playbook for how marketing in a space like this should look. A playbook of tactics and tools that are well-understood. And every company will do it differently, and every brand and product will have their own personality. But we pretty much use none of those tools.

Cristina: Yeah, can you help people understand what the industry norms are for marketing attribution and data and how we do it differently?

Chuck: So when you visit your favorite social media site and it’s trying to decide how to fill the ad slot in your feed, the ad platform will take what it knows about you as a person, your search history, who you follow, and what it knows about your situation, like where you are and who you’re with, and line it up with their ad inventory. They’ll do some very complex math to determine the perfect ad to show you that will maximize profits for the platform and the advertiser. So the more better data they have about you, the better they can target the ads and the more money they can make.

I know that’s something you’ve talked about with Peter on a previous episode, that the financial incentive for the trackers that are ubiquitous online is data that feeds the machine that helps them make more money off of your ad space. That entire ecosystem just flies in the face of our privacy principles. In fact, some of our apps will block those trackers to keep your browsing private. So when we advertise, we refuse to use those tools like you just listed that are common in digital marketing, like retargeting or reporting different types of conversions after the ad click. ⁓ just to protect the privacy of our users. Instead, we’ll collect limited data only when there’s a very clear and urgent rationale for it. And when we do, we’re transparent about what we collect and how we use it. And we’re possibly most important. We’re really careful never to let those logs link two different events to the same person. That’s really difficult to do. ⁓ We have a really fantastic privacy engineering team that reviews every project and their implementation to make sure that the work we’re doing is aligning with our principles.

I’ve also gotten really comfortable making decisions with just the imperfect or incomplete data, trying to identify the solutions that meet 80 % of the business needs without, with 20 % of like the potential input.

Cristina: Yeah, it feels like a lot less than 20 % of what’s actually available to us. Well, yeah. So thank you for unpacking that. That’s a helpful foundation. Can you go a bit deeper and talk about what that looks like in practice at DuckDuckGo?

Chuck: Yeah. That’s probably fair.

Yeah, so we largely ⁓ don’t work with other vendors ⁓ in the marketing space and rely on the tools we own and build ourselves instead. That makes sure that we aren’t incidentally feeding the machine with our own users’ data, which is really easy to do if you’re not careful. ⁓ We have a couple of tools in our toolbox, too. We’ll do as much summarization and analysis of data locally before we ever send it back. So rather than saying that a user of our browser searches

15 times in a day and ⁓ sending 15 different events for those searches, we’ll send a periodic report that will say they searched 15 times during that day. We’ll reduce the precision of those signals even further. So instead of saying that that person made 15 searches, we’ll say they’re a medium volume search user. And then when we do our analysis on an ad campaign, we’ll look at the summaries of the data rather than the raw data ⁓ so that we’re looking across our users rather than the individual humans.

And if it comes down to it, we are willing to redact data that might be too identifying for a person, whether it might contain PII or if it looks too unique and may be able to be traceable back to a person, we’d rather delete it and not use it than jeopardize that person’s privacy.

Cristina: Well, thank you for ⁓ sharing how our ethos really comes to life there. And I’d love for you to touch on one of your claims to fame at DuckDuckGo, which is creating a better, more privacy-respecting system that we call Origin. Can you talk about how you got the idea and how you brought it to life?

Chuck: Yeah, so we were struggling to run small scale campaigns that test new ad platforms or creatives. ⁓ With the tools that we have, the only way that we could do that without jeopardizing user privacy is to run big, broad, expensive, scaled campaigns. But we’re a small company. We want to move nimbly. And that made it really difficult for us to quickly validate our direction and make sure that we were dedicating our resources in the right time or in the right place. So I spent some time with our marketing leaders, including you, Cristina. ⁓

trying to understand the norms and the challenges they were facing, the tools that weren’t in their toolbox. And I brought that to the privacy team. ⁓ We worked backwards, starting with user privacy as a first principle to the business goals and landed on a solution that kind of looks like this. ⁓ You see an ad and you click on it for DuckDuckGo and you install our app from it. When that app first runs, we will send one signal that says that you installed the app from that ad in that location.

And then once a day, we’ll build a summary of those signals that give us pretty coarse insights that say, you know, we had 10 users install our app from that ad on that ad platform on that day. Then we’ll line that data up with other information that the ad platform gives us, like how many impressions there were of the ad and how many times it was clicked and how much that cost us. And that’ll give us some high level insights we can use to start making decisions, like how much it costs us to ⁓ per install from that ad. There’s nothing groundbreaking here technologically.

It’s actually intentionally very simple and that helps us maintain the privacy properties because we have a high elevation view of everything that’s happening. We never share data outside of DuckDuckGo, so we aren’t feeding that machine. There are never person level insights. We’re looking at broad signals across our audiences. There’s no risk of PII and we’re only collecting the data that we need to make those decisions, nothing more. But it still lets our marketing team make informed decisions while working quickly and doing their jobs well.

Cristina: Well, thank you. ⁓ More importantly, thank you for the months and months of work you did on that. ⁓ You say it’s nothing revolutionary, but actually, I think it’s a pretty novel approach. We don’t know of any other companies using technology like this. Typically, they use the entire suite of tools available to them. ⁓ But hopefully, one day, it won’t feel like such a novel