Latest / The DTC Marketing Podcast with Fexingo: Direct-to-Consumer Brands, Shopify, and E-Commerce Growth / How DTC Brands Use Podcast Ad Attribution to Optimize Spend
Transcript
- Lucas: So we talk a lot on this show about DTC brands using podcast ads for growth. Episode seventy-three, episode seventy-nine. But one question keeps coming up from listeners: how do you actually know the ads are working? Luna: Right, because podcast ads don't have a click-through. You can't just look at a dashboard and see 'this many people clicked and bought.' Lucas: Exactly. And for a long time, the standard answer was promo codes. You give the host a unique code, listeners type it in at checkout, and you count the conversions. Simple, right? Luna: Simple in theory. But in practice, a lot of listeners don't use codes. Maybe they forget, maybe they don't care. So you're undercounting by a lot. Lucas: That's the big problem. One study I saw, from a podcast analytics firm called Chartable, found that promo code usage captures maybe ten to twenty percent of actual attributable conversions. The rest are what they call 'dark conversions' — people who heard the ad, searched for the brand later, and bought without a code. Luna: So what do you do? Just trust that the ad works and hope for the best? Lucas: No, you layer in other methods. The second one is vanity URLs. A dedicated URL like brand.com slash podcastname. You can track that more reliably than codes because it's just a click. But even then, some people will type the brand name directly into their browser. Luna: So you're still missing the direct-type-in traffic. Lucas: Right. The third method, and this is becoming more common in 2026, is the brand lift study. You run a survey with a control group and an exposed group. You ask things like 'Have you heard of Brand X?' or 'Are you likely to purchase?' And you measure the difference. Luna: That's the gold standard for a lot of big advertisers, but it's expensive. A proper lift study can cost fifty to a hundred thousand dollars. That's prohibitive for a small DTC brand just testing podcast ads. Lucas: It is. But there are newer options. Podcast ad networks like Acast, Megaphone, and Spotify’s ad platform now offer post-placement attribution using pixel-based tracking and panel data. They can tell you, 'Here's the lift in site visits, here's the lift in searches, here's the lift in conversions.' It's not perfect — it's modeled — but it's way better than a vanity URL alone. Luna: And it's more affordable. I've seen some of those network reports for brands spending as little as ten grand on a campaign. That's a game-changer for smaller players. Lucas: Totally. And the key is to use multiple methods together. You don't just rely on promo codes. You run a lift study for a subset of your audience. You use a vanity URL. You also look at organic search volume for your brand name during and after the campaign. That gives you a triangulated picture. Luna: I want to get into a real example. I was talking to the marketing director at a mattress startup — not naming names — but they spend about two hundred grand a quarter on podcast ads. They were using promo codes exclusively and seeing a cost per acquisition of about one hundred twenty dollars. Lucas: Ouch. That's high for a mattress. Luna: Yeah, it is. So they did a lift study with a third party for fifteen grand. And they found that the actual CPA, when you account for all attribution, was more like eighty-five dollars. So they were undercounting by about thirty percent. And their actual return was better than they thought. Lucas: That's a massive difference. And it changes how you allocate budget. If you think your CPA is one twenty, you might pull back on podcast ads. But if you know it's eighty-five, you double down. Luna: Exactly what they did. They increased spend and also started using network-provided attribution to optimize which shows they advertise on. They found that true crime podcasts had a much higher lift for their brand than comedy podcasts, even though the comedy ones had lower promo code redemption. Lucas: That makes sense. True crime listeners are often in a focused, attentive state. They're less likely to skip ads. Comedy listeners might be driving or doing dishes. The ad doesn't land as well. Luna: Right. But without the lift study, they'd have cut the true crime shows based on low promo code use. They'd have made the wrong decision. Lucas: So the lesson is: attribution is not one tool. It's a toolkit. And if you're a DTC brand spending any real money on podcast ads, you should be using at least two of these methods. Ideally three. Luna: And it's worth noting that podcast listening is shifting. More people are listening on smart speakers and in cars. That makes promo codes even harder to use because you can't type. So the need for better attribution is only growing. Lucas: Great point. And there's one more emerging method I want to mention: survey-based attribution at scale. Companies like Nielsen and Edison are running ongoing panels where they can tie podcast listening to purchase behavior. It's expensive but it's the most accurate. Luna: That's really for enterprise brands. But it's a sign of where the industry is going. More data, more precision. Lucas: And for smaller brands, the panel data from ad networks is a solid middle ground. You don't get perfect individual-level attribution, but you get directional data that helps you optimize. Luna: One thing I'd add: if you're going to use promo codes, make them memorable. Don't use a random string. Use something like 'MATTRESS' or 'SLEEP15'. That increases the redemption rate. Lucas: Common sense but often overlooked. And also, test different host-read styles. A host who sounds like they actually use the product will drive more conversions than a stiff ad read. Attribution can't fix a bad ad. Luna: That's the truth. You need good creative, good targeting, and then good measurement. All three have to work together. Lucas: If these marketing conversations have sparked something you've actually used in your own work — whether it's an attribution method, a creative approach, something we talked about — and you want to help us keep the show ad-free and independent, we do have a listener support page. It's buy me a coffee dot com slash fexingo. No pressure, but if it's added value for you, that's the place. Luna: Yeah, and we really appreciate it. It helps us keep doing deep dives like this one. Now, back to attribution — one thing I want to ask, Lucas: how do you account for the fact that podcast ads have a long tail? Someone might hear an ad today and buy three months later. Lucas: That's the hardest part. Most attribution models look at a short window — seven days, thirty days. But podcast ads often have a halo effect that lasts much longer. One solution is to use a multi-touch attribution model. Give partial credit to the podcast ad even if the final conversion happens later through a search ad or a direct visit. Luna: So you're saying don't look for a single conversion event. Look at the whole journey. Lucas: Exactly. And that's where lift studies shine again. They measure changes in brand perception and purchase intent over time, not just immediate clicks. So for a DTC brand with a longer sales cycle — say, a subscription service or a high-ticket item — a lift study is almost essential. Luna: And for a low-ticket impulse buy, like a snack box or a beauty product, promo codes and vanity URLs might be enough. You need to match the attribution method to the purchase cycle. Lucas: Right. There's no one-size-fits-all. But the brands that are winning in podcast advertising in 2026 are the ones that treat attribution as a discipline, not an afterthought. They budget for it. They test multiple methods. They iterate. Luna: And they share the data with the podcast hosts. Some hosts are very willing to adjust their ad read based on what's working. That's a partnership, not a transaction. Lucas: Great point. Attribution isn't just about measuring. It's about learning and improving. If you know that ads on a show about entrepreneurship drive twice the lift of ads on a general interest show, you shift your budget accordingly. You also give that host more creative freedom to make the ad better. Luna: So to summarize: use promo codes as a baseline, but layer in vanity URLs and network attribution data. If you have the budget, run a lift study at least once a year. And always, always look beyond the last click. Lucas: That's a great takeaway. And I'd add one more thing: don't be afraid to ask your podcast ad network for attribution data. Many brands don't realize it's available. Just ask. The worst they can say is no. Luna: And if they say no, maybe that's a signal to work with a different network. Attribution transparency is becoming a competitive differentiator for podcast ad platforms. Lucas: It really is. And as the medium continues to grow, the brands that measure well will be the ones that scale. The ones that don't will waste money and then declare podcast ads don't work. But the data shows they do — if you measure right. Luna: Alright, that's a good note to end on. Thanks for listening, and we'll be back next time with another deep dive.