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Adam McNeil

VP of Marketing

Channel-surfing: Finding the Right Avenues of Growth

Podcast Attribution 101

Formerly the VP of Marketing at Füm, Adam now helps DTC brands scale through podcast advertising. On the side, he runs Canada’s biggest Kendama competition.

In This Article:

The unique landscape of Podcast Attribution

When it comes to advertising mediums, podcast advertising is both smartly stupid and stupidly smart.

It's also both digital and offline, and offline and digital. Some of what you can track is very clearly attributable to digital means, like a coupon code or a UTM or even pixel-based data. Contrastingly, some of it is not very attributable—think like a billboard or something else offline that is pushing awareness out there.

Meanwhile somewhere in the middle, there's ultimately a lack of attribution between what we can track and what we can't track.

Understanding the challenges in Podcast Attribution

When trying to track podcast attribution, so much could be attributable.

Your customer could’ve used the right coupon code, or

maybe a pixel picked them up, or

maybe they used the right UTM, or

maybe they found your business on Google, or

maybe they could have heard about your business on a podcast and checked it a little bit later, and then gone “Oh yeah, I did remember hearing about this on Orbit”.

There is so much to track in the world of podcast advertising, and businesses have employed a couple of different methods to do so.

Coupon codes

Coupon codes are a tactic used by businesses to entice customers to make a purchase by offering discounts or special deals. It's a win-win—customers save money, while businesses get to increase sales and customer loyalty. This allows businesses to potentially build long-standing relationships with customers and increase returning customer rates.

Not only that, it’s probably the easiest way for businesses to track attribution.

You can create unique coupon codes and assign them to specific podcasts. From there, every time a customer buys a product using a unique code, the sale can be recognized and tracked. This includes data such as customer ID, order value, and revenue for different time periods.

Limitations of coupon codes

Each digital form of attribution for podcast advertising has flaws.

Not everybody's going to remember the coupon code. There's also probably a competitive offer on your site that is probably the same (if not better) than the coupon code from a podcast.

Or what if they go to a site like Honey and it auto-imports a coupon for a podcast that has been leaked, and that overrides whatever coupon code they wanted to use with an equivalent or different offer?

So, coupon code attribution becomes complicated.

Additionally, you can only ever use one coupon code. What if I listen to four different podcasts and four different podcasts told me about this brand. How do I give attribution to all of them? I would want to share the weight but they all influenced me but I have to pick one with a coupon code. This limits how you attribute through coupon codes.

What to look out for when using coupon codes

So now you might be wondering what are the best practices we’d recommend when it comes to using coupon codes.

Firstly, strategize which podcasts you’d like to work with and the discounts you’d like to apply for each one. I would recommend working with podcasts that can not only drive you enough traffic, but the right traffic as well. It’s important to understand your audience and what they might be listening to. This would increase your likelihood of conversion.

I would also recommend that the coupon codes provided to each podcast are unique from one another. This would make it easier for you to accurately attribute your sales to not just podcasts as a whole, but to which podcast as well. This will keep you informed on which podcasts are working and worth the investment.

If you intend to invest a lot in coupon codes, your business could also consider investing in a coupon code service that can help you stay on top of everything.

Here are some best practices we’d recommend:

Firstly, keep codes simple and memorable. It is likely that you’ll have a number of podcasts involved to extend your reach. This means that the whole process can get messy. As such, simplicity and memorability are most important here to make it easy to keep tabs on your codes while making it easy for your customers to key in.

Podcasts are audio. What this might mean is that some consumers may not know how to spell what they heard and will try certain variations. As such, it is important to cater to that uncertainty. We recommend creating variations to try to account for the uncertainty, to keep the data accurate as much as possible. For example, if your brand’s name is “Fairing”, create variations like ‘Faring’ or ‘Fairin’ to accommodate misspellings.

We recommend using a third party application to help keep your attribution data clean. With external applications like PayPal Honey or services from corporations like Capital One, they muddy up your attribution. This makes it difficult for you to be accurate in your attribution as the data gets confusing. As such, applications like Clean.io serve to help prevent these problems from arising.

Finally, use a unique code for each creator. While it may be simpler to apply a general code for your campaigns, for example “SUMMER10”, this makes tracking a nightmare. It would make your tracking process simpler by segmenting your codes. Your brand could give each creator a unique code, segment by social media channel, and so on.

UTMs and vanity URLs

A UTM parameter is a small piece of code attached to the end of your URL to target and track specific campaigns. When someone clicks on a page with a UTM parameter, that information is sent back and segmented in Google Analytics for detailed tracking.

A vanity URL is a unique web address that is branded for marketing purposes. Vanity URLs are a type of custom URL that exists to help users remember and find a specific page of your website. Businesses will usually shorten the URL with the UTM Parameters into a vanity URL for simplicity.

These are great for tracking attribution. UTMs attribute value to each touchpoint or marketing channel. This helps businesses understand which elements and how much they are contributing to conversions, leads, or desired outcomes. This attribution data aids in optimizing marketing strategies, allocating resources effectively, and improving ROI.

Limitations of UTMs and vanity URLs

UTMs are fantastic.

However, very few people will actually go through the UTM URL that you've given them to go to. For example, take blissy.com/adamspodcast. That is a lot of work that you're asking a consumer who is generally speaking, looking for the path of least resistance.

What the customer is likely to do is just Google your brand and click on the first link. If you're lucky, they’ll remember the coupon code and they're going to go and order.

What UTMs do offer is insight into audience purchasing behavior on site. If visitors come through the URL you can kind of get a gauge of, is this audience converting at a higher rate than this other audience that comes from a different podcast. That's a good data set to pull, so it's still valuable.

However, there is inherently a very small sample size that will come through a UTM and give attribution to that methodology.

As if that’s not enough, some vanity URL tools or URL shorteners have been known to remove UTMs, making it difficult to trust this as a source that is 100% accurate.

What to look out for when using UTMs or vanity URLs

Be organized. When implementing such a strategy, it’s dependent on how detailed and elaborate you want your strategy to be. When using UTMs or vanity URLs, you can use them to track your marketing spanning the entire customer journey. What this means is that you are able to create them for any stage of your marketing. So, it’s important that you decide strategically what you wish to track.

The consistency of your naming conventions can also make or break your UTM strategy. Therefore, it’s super important you consider all of the possible descriptions within your various UTM parameters before you kick off your UTM process. Having just one inconsistent UTM parameter can wreck your data, making it more challenging for you to get a complete and accurate overview of how well your marketing is performing.

To make sure everyone is on the same page, documentation is key. This means creating a master spreadsheet of UTM parameters, with clear guidelines on what rules everyone needs to follow when creating custom campaign parameters.

Implementing the same structures in your UTMs will be critical to your data organization. This makes it easier to pull data for any reports you may need moving forward as everything is arranged systematically.

When adding UTM codes to URLs, links can get overly long. This is why you should use vanity URLs to hide your parameters or shorten the links while still getting the tracking data you need. Having links that are shorter and cleaner are more attractive to the eye, especially when placed on marketing materials, like flyers or direct mail.


A tracking pixel is an HTML code snippet which is loaded when a user visits a website or opens an email for example. It is useful for tracking user behavior and conversions on their site. With a tracking pixel, advertisers can acquire various data about their customers.

The data that can be acquired includes: the operating system used, type of client used (such as a browser or mail application), time the email was read or website was visited, activities on the website during a session (when using multiple tracking pixels), and their IP address.

Due to the nature of podcasts, the only data access point available is the user’s Internet Protocol (IP) address and the user-agent pairs. Pixel-based attribution hence involves finding the unique identifier of the listener, and matching that to a unique identifier of a purchaser.

A prefix on the other hand is a short URL added to a podcast's RSS feed. It captures the listener's IP and user agent before the episode downloads. This facilitates listener identification, matches them with purchasers despite the absence of online cookies, and enables attribution.

When a user visits a webpage or opens an email containing a tracking pixel, the pixel sends this data back to a server. These servers could be owned by an advertising company, a social media platform, or any organization interested in collecting data. Businesses will be able to access the data collected in the servers.

Pixel tracking provides your business with in-depth and accurate information that you can use. They allow you to follow users on all their devices, linking marketing efforts across your mobile ads and website.

Additionally, because they don’t rely on an individual’s browser, users can’t disable them. Pixels are useful for tracking conversions on your landing pages, partner sites, and even affiliate networks.

Limitations of pixels

For pixel-based attribution, you eliminate some of the flaws presented by the previous methods. Not only that, you add in a layer of multitouch attribution where you can see the different shows that someone listens to and funnels in through.

However, pixel-based attribution is only accurate to about 50%. That is because they can only accurately attribute to household IPs. For example with your network at home, if your customer is listening to a podcast at home and orders something advertised on it, there’s a pretty good confidence that the person was a real podcast listener that converted.

Truth of the matter is that 50% of people aren't listening to podcasts at home. They're listening to them on the road, in their office building, or simply in places where the IP signals get really muddy and the attribution gets messy.

Due to that, we can't trust 50% of the data there. So again, we're modeling some data off of household IPs.

What to look out for when using pixels

You’re going to need to keep track of the pixels on your site, and test if they’re firing on occasion. Pixels can sometimes be blocked by cookie consent banners, ad blockers or other privacy-focused tools on a customer’s browser.

All pixel attribution is third party, so it’s good to ask regulatory questions. What’s your modeling methodology? Are you IAB certified? How widely accepted by publishers is your pixel?

Post-purchase surveys

A post-purchase survey (PPS) is simply one or more questions shown to a customer immediately after they’ve bought a product on your site.

This is critical as this tiny window of time is a giant window of opportunity where your customers are most willing to answer your survey questions. PPSs help you close the gap between what is attributable and what isn’t.

PPSs act as a bit of a filter for the other 3 methodologies. The three are able to help businesses create a baseline and is what we were able to accurately attribute. On the other hand, PPSs create the high end that enable businesses to see what is told by the customer on what is actually coming through.

How we use PPS to monitor attribution

At ADOPTER Media, we gather our PPS responses and take that as a macro set of data for our clients. We would see that for a brand, for example Blissy, they may get 25% of their respondents on a 50% response rate saying that they heard about them from a podcast.

With that, we would be able to use that as a macro-indicator to say that podcasts as a medium are generating close to 25% of overall revenue with 50% confidence based on the response rate.

However, when we look at all of our digital tracking means, we might observe that only 12% of new customer revenue comes through podcast-attributed methodology.

As a result, we now have a gap between our data points. That would show that there is nearly one person for every person that has been picked up through direct attribution, that is not picked up through attribution.

As such, we can see that for this example, there was generally a 2X lift (also known as a multiplier) as the numbers don’t match. If you’re interested in learning more about the multiplier, Fairing has a great free-to-use Podcast Multiplier Calculator to help you assess the effectiveness of your podcast campaigns.

So we use post purchase surveys to validate the macro impact of podcasting, especially when there's so many issues that are tied to every individual form of attribution.

Limitations of Post-purchase surveys

PPSs are not without their limitations either.

Due to the nature of a PPS, response rates won’t be that high as many may choose to opt out or skip through the surveys. As such, response rates tend to sit around 40 to 50% on average. This could affect the reliability of the data as your sample size might not be big enough to make a justifiable assumption. This is another reason why these surveys are conducted post-purchase, and not a long time after the initial point of purchase.

It’s also possible for customers to remember their attribution incorrectly. With the many marketing channels businesses have now, it is easy for your customers to forget how they heard about you exactly. As the survey data is reliant on accurate answers from your customers, this affects the validity of the survey data and is something to take into account.

What to look out for in a PPS provider

These are some things I would recommend to look out for when looking for a PPS provider.

Get one that gets you a higher response rate. While it may appear that every PPS is identical, some providers can get you a higher response rate. The industry average sits around 40%, but some providers can get you up to 60% or more. This might be due to the simplicity of the way that questions are delivered to the consumer.

The additional feature of adding another option where people can write in and fill in the blank is also a big plus. These allow us to ask consumers “what is your favorite” or “what podcast did you hear about us on”, and these features really help. Rather than having a multiple choice set list of answers you can offer open field questions. Some surveys don't allow for that or don't make that easy to do.

It should also give you additional detail for you to better understand your data. One such example would be being able to click in to see the order and being able to take me right to the Shopify order page and tell me if this person used a code or not.

They might’ve said they heard about you on a podcast like Morbid, but they didn't use Morbid's code. In that case, that's a really good piece of data to look at and go, you know what, boom, boom, this is great evidence to say, not everybody uses coupon codes when told to use a coupon code or offered a coupon code.

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