Duck Tales: The team and process behind DuckDuckGo’s customer support (Ep.46)

In this episode, Beah (Chief Product Officer) and John (Support) discuss our customer support process, why we read all tickets (good or bad), and how we actually use them to improve all aspects of the user experience.

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Beah: Hello, and welcome to Duck Tales, 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, or approach to AI. Today you’re gonna hear about how we do support at DuckDuckGo, and my guest is John. John, do you wanna introduce yourself briefly?

John: Yeah, for sure. Yep, I’m John. I work within our marketing and communications team. And for the past few years, my main goal has been managing and improving how our support operates for the DuckDuckGo subscription and beyond.

Beah: Sweet. So if you’ve used DuckDuckGo support, perhaps you’ve gotten a message from John or one of the other teammates who we’ll learn more about in this call or in this pod. So I’m Beah. If you haven’t met me, I’m on the product team at DuckDuckGo. All right, let’s jump in. I’m gonna ask John some questions and we’ll go from there. So tell me John, just to kind of set the scene, what sort of things do we provide customer support for?

John: A lot. The bulk of the support that we offer is through the DuckDuckGo subscription. So for us who handle support, it means handling things like billing questions, assisting with activation across multiple devices, questions about the plans that we offer, and more technical troubleshooting related things. The subscription can be bought a few different ways, each with its own different path to activation. So a good bit of the support that we offer is helping our users navigate these paths to get more comfortable with our subscription and its features. So some of our great front-end team members built a support form where most of our tickets run through. It was built to be kind of as self-service as possible, but a category is picked and depending on what the selection is, a potential solution gets surfaced. This way, plenty of users can get an answer without really needing to submit anything or wait for us to respond to them. But basically, our help pages kind of sit behind this and there’s links to that support form on every one of our subscription help pages. It’s the first stop for most of these tickets. We’ve been piloting an AI agent on a few help pages and I’m sure we’ll get into that as well.

Beah: So like if we don’t, if we can answer, if we can get people an article right then and there that answers their questions, that’s the best case scenario for everybody because they get an immediate answer, but if not, then we have a process to kind of hand it off to a human or an in-between, which is like AI assisted answers.

John: Exactly. That’s right.

Beah: And maybe I should say like before we had the subscription, which is the first paid product that DuckDuckGo offered, and the only one we offer, we didn’t really have a support team or support process. I mean, we had emails for different things, but like effectively we didn’t have to worry about customer support. And it was the introduction of the paid subscription that sort of like brought this problem to our doorstep and to you. Is that fair to say? Yeah, yeah.

John: Yes. Absolutely. Yeah. Yeah. Perfect.

Beah: Okay, cool. So tell me a little bit more about like how this all works like team-wise, who’s working on this, how have we structured that?

John: Absolutely. We have a small but mighty team. So when that subscription first launched, there were a few of us that kind of rotated handling these support tickets. After a few months, we streamlined it significantly to where I was the only one who was handling things, which probably seemed like it was unfeasible and it really was. Early last year, we brought on an awesome specialist as...

Beah: It, I mean it, it worked, you just didn’t sleep great.

John: Yes, yeah, it worked. It worked. But there was a lot that was dependent on me and it caused a lot of lead time for some people to get responses. It was a lot to manage basically. So we brought on an awesome specialist as we continued to grow. She’s been awesome in the organization and the optimization of our entire end-to-end process. She’s got more support experience than I do by far and is a great Swiss Army knife of skill sets. So with her help, we, along with dozens of other teammates throughout the organization, we kind of overhauled the whole support structure at DuckDuckGo. And then recently, earlier this year, we brought on two more support rockstars to kind of help shoulder the ticket load to ensure that our users aren’t waiting too long before getting a real human response. So they’ve been a great addition. They’ve been working fantastically. And they’ve added an additional support layer to the mix. But yeah.

Beah: Got it. And you, you, you mentioned like lots of other people. I mean, so there’s like the people who are actually writing the emails back. And then I think part of what you’re getting at, tell me if this is right, is like, you know, they are likely in many, not in all cases, but in some cases, like need to go talk to an engineer to understand what’s going on, or like a product manager or somebody else who’s been working on the product directly day in and day out and like they’re just kind of interfacing between like this huge, you know, pool of resources who know different things about DuckDuckGo.

John: Yes, yeah, and that, the whole concept of working out in the open really helps make that a lot easier. So we have engineers and developers that really plug in whenever a support signal points to the need to escalate for a better response that we don’t know or we can’t handle.

Beah: It has been for you.

John: So that direct line to the actual builders that are behind the scenes ensures that we go straight to the source and we don’t have to wade through multiple layers of people to get an answer that’s accurate.

Beah: Gotcha. Cool. So tell me, like, kind of riffing off of that, how does this fit into like our broader approach to customer feedback loops? Like we have this email support system, but we also like interface with users or get feedback from users like on social media or, you know, all these various ways, which I would say for context for listeners, like we really, we like really read that stuff and really pay attention to it. Like we’re pretty, I’d say we’re pretty obsessed in fact with understanding. Like if you’re sending us, if you’re a user and you’re sending us signals about your experience, like we are pretty hungry for that. So yeah, tell me about like the boundary, the interface boundary between like that kind of feed, those customer feedback loops and the support that you’re talking about.

John: Yeah, so it’s a big circle. So essentially, the support piece to me, from what I’ve seen, I feel like I’ve been in every aspect of support, internal and external, that we offer. And this support for the subscription that we do is truly one of the most honest and raw feedback channels that we have. Most of the time, people write in when there’s a problem. Like, you’re not going to be contacting support to be like, hey, great job. Each ticket gets categorized in those categories.

Beah: Though feel free to.

John: Yeah, you’re more than welcome to, yes.

Beah: Yeah.

John: But we don’t even, we don’t handle things that are just a subscription, we handle any and all questions that come in, which I might get, we might get a deluge of tickets with me saying that. But, that said, we get a really wide range of feedback. It’s truthful. It’s unsanitized. It’s anonymous. So one thing that I’ve insisted upon since we launched this is really reading that rougher stuff on purpose. So I thrive on reading through our negative feedback. A good bit of it relates not just to the poor experience with the support team that happened from time to time, but also their experiences with the products that we offer. So both halves of those go to those who can action them. When we see things, multiple complaints about a specific piece of the product, we’ll let the people know who could actually work to fix it. So actions like these help drive rewrites to our help pages that might seem confusing. Clear responses to our users in the future. Updates on our products, bug fixes.

Beah: That is a problem that would not be using my C.

John: And this was also the catalyst to including suggested solutions on our help, our subscription support form. So sometimes when you select something, you’ll see a suggested solution that bumps you to a help page where you can clear things faster, like we mentioned prior. But yeah, things like social media posts. If you’re on Reddit and you see a response from someone that’s like, hey, it’s John at DuckDuckGo. That’s me. And app store reviews, those get watched by our team and others. And then they’re routed to us when they’re support related. So it ensures that those feedback loops are all connecting together.

Beah: Nice. All right. So tell me a little bit, like, as our support function has grown and needed to scale as the subscription has grown, like what changes have you had to make?

John: Yeah, absolutely. So for a little bit of inside baseball, in late 2022, DuckDuckGo acquired the company that I co-founded, bringing my friend and I on board to help build out the personal information removal piece of the subscription. But one of the things that drew DuckDuckGo to our company of Removaly was our stellar customer support. And that was something I really wanted to ingrain in this subscription. So early on, I made sure to take a leadership role in building that out, which starting from zero is pretty... It was pretty fun to go from zero to where we are now. But at first it was really, really bare bones. We actually just ran it through an Outlook email. I personally replied to over 15,000 emails in the first year and a half that the subscription existed. Recently we switched over to Zendesk to help kind of manage a growing user base and get analytics and things that we could use to help improve. So between that switch and the addition of these other fantastic support team members, it’s really allowed me to step back and focus on the more operational aspects of how we support our users, but I still try to sometimes get into the weeds.

Beah: Yeah. That’s the basic problem to be for.

John: And we use those Zendesk analytics to inform continued growth for support and ensures that we scale effectively in parallel with the subscription and even.

Beah: Nice. Fifteen thousand. That’s pretty good, John.

John: Yeah.

Beah: All right, what are some of the main challenges of this system?

John: Privacy. Privacy is, while it’s fantastic here, it can be the bane of existence for support.

Beah: Yeah.

John: We don’t hold any information about our users by design, so we troubleshoot with a lot less context than most companies have. It helps make us better at asking questions and writing clear documentation, but it’s a real constraint, honestly. There’s also the consistent balancing act between speed, self-service, and satisfaction. And in many cases, we get to pick two of those, which negatively affect the third. So every improvement that helps people find answers faster, we have to weigh it against the experience of the person who still needs a human to respond to them. We watch that side really closely. So for the many, fast can never mean worse for the few right now. Of course, there’s also the typical ordinary difficult stuff. We don’t close down support over the weekends. So we cover seven days a week with a really small team. We have volume spikes frequently when we launch new areas, when we introduce new features, when we go viral on social media, when we start large-scale advertising initiatives like we did a couple weeks ago. We’ve got multiple billing platforms that have different financial processes and platforms we build on shipping really quickly that we have to absorb to make sure that we’re not giving incorrect or outdated information. But despite this, our really small but mighty team has managed to continue operating at a really high level of customer satisfaction. So that’s pretty sweet.

Beah: Nice. So you’ve touched on using AI once or twice. Tell me a little bit more about how you think about the role of AI in customer support. Yeah.

John: Yeah, so first I was really hesitant. I mean, I’ve seen and I’ve witnessed firsthand with other companies that I’ve interacted with that AI can be great and helps with scaling, but it could also like really frustrate people when they know that they’re chatting with someone that’s not going to be able to help them. It’s a bot. So we’ve done so.

Beah: Yeah. Yeah, I kind of forgot. I’d kinda forgotten about those early conversations, but you’re, you’re bringing it back. I think I remember being like, like I know what side John’s on.

John: Yeah, I fought it a lot. But we’re working on it. We’re trying things out. So we piloted kind of a privacy preserving AI agent through Zendesk on a couple of our support pages. And it was built to only answer from our own help page content. It handled some real volume. But we’ve had to kind of be honest with ourselves about the results. They’ve been OK. But there’s a lot of nuance involved in the questions that people are asking us. So we’re still ideating on it. We’re tweaking it. We’re refining it more. But that’s something where instead of shipping quickly, we want to make sure we move slowly and do things the right way. And then AI and the customer support space in general is really touchy, as I mentioned. It’s got to reduce the user effort without touching the quality of the answers or negatively affecting the privacy that our users expect from us.

Beah: Yeah.

John: So we tool that to configure conservatively for privacy. Help content is really kept as consistent as possible. And we’ve used AI a bit to kind of make sure that we are keeping our help pages the latest and greatest.

Beah: Okay.

John: Internally, we use our own AI tools where they really actually will help. But we still make sure that a human owns every reply that goes out that’s not specifically driven through that AI agent.

Beah: Yeah, that’s interesting. I was thinking about like, I mean, I feel like for us to give everybody the information they need quickly, it’s kind of a no-brainer that we should be experimenting with getting AI help on that. It feels like it, it could be quite, quite powerful, but I think right now I’m on a very frustrating customer support thread with, I’m guessing, mostly AI driven responses for like a piece of furniture I purchased.

John: Mm-hmm.

Beah: And it’s responsive, like it’s sending me a lot of emails, but they’re just like such fluff, you know? Like it doesn’t have any good answers. It’s not really taking my like email all that seriously. It’s just kind of holding me off, you know? And like every time I get an email, and it’s like, and it’s also like super apologetic. It’s like, like we’re so sorry. That must be so frustrating. And it like, by the like third message like that, I’m like, what? This is like so disingenuous.

John: Exactly. Yeah. Yeah. Yes.

Beah: Like, and I’m like, are you just AI? Like I think you’re just AI, right? And yeah, it’s, it’s tricky. But I do, but I mean like I, yeah, I want a response fast and I want it to be meaningful and in theory, like there should be a good application of AI to do that.

John: Agree. Yeah, it’s really critical to find a good balance of that. So you’re not providing a really fast service that’s not answering the question effectively or that’s providing that fluff that’s making people like, obvious that maybe this company doesn’t care about me as much as I thought if they’re not willing to have someone on the other end actually having this back and forth.

Beah: Yeah. There’s also like a little bit of a sense of, I guess like worst case scenario, like deception, you know? Like I’m like, are you, are you a robot pretending to be a human? Like that’s weird. I d, that’s just weird.

John: Exactly. Yep. Exactly. Yes. Yeah. So I’m slowly coming around, but I’m still pretty dubious about it in its, in its current state. So.

Beah: Yeah. Yeah, nice. All right. Well, to be continued, maybe, yeah, we can do a V2 version of this episode a year from now and see if, see what kind of progress you guys have made.

John: Yeah.

Beah: But let’s close on a more positive note. What aspect of our support, our customer support are you most proud of, John?

John: Man, honestly, I feel like we’ve been able to keep or improve our set-by-ourselves quality bar while we’ve continued to scale. So we’ve been able to survive that increase in volume without negatively affecting the quality of service that we offer. At Removaly, I mentioned my co-founder Kyle and I, we did the customer support. It was a two man crew and we did live chat and it was difficult. But that closeness to our users shaped how I wanted that quality bar to be reflected at DuckDuckGo, which, it’s not easy pivoting from a very small startup to one of the most visited sites on the internet. Three plus years and a lot of growth later, every ticket here still gets a specific human answer. Negative feedback gets read by people who can actually drive the change to the products that people are saying that they’re having issues with.

Beah: But I won’t make that. Yeah.

John: And our support is consistently having a seat at the table in product decisions. We’re actually being listened to when it comes to like, well, what do our users actually think about this? Are we getting feedback? What do you guys recommend? So right now our support team is four people. But we’re a small team whose effectiveness is so strong that honestly I’d really put it up against support organizations with entire support structures 10 times the size of ours. And I think we’d be able to beat them.

Beah: Yeah.

John: So being able to keep that quality bar despite scaling quickly and rapidly over the course of the past few years has been wonderful to see.

Beah: Nice. Well yeah, I mean, DuckDuckGo I think has like some DNA in a time when we weren’t one of the most visited sites on the internet and were like, Gabriel was, you know, personally super focused on, you know, talking directly to, to customers, to users, and I think we still have a lot of that DNA. I mean, we need to on the one hand find ways to make it scale, but I think sometimes like caring inordinately about an e, a single angry individual can be a really powerful tool for improvement and motivation. And yeah, so thank, thanks John for like all the work that you and the team do on that front and also to listeners who provide us with feedback. Thank you guys. I, we really try to make good use of your time.

John: Absolutely, yeah. Thanks for having me, Beah.

Beah: All right, later.

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