How to do podcast attribution the right way

You get both online and offline signals. The key is how you marry that information together.

When testing podcast advertising, having an attribution strategy is probably the most important thing you need to nail down.  If you don’t have a solid attribution strategy for how you will measure lower-funnel performance in podcasts, everything else you are doing is a waste of time.  

With that being said, if you do know how to read all of the signals you get from podcast advertising, you can have a plethora of data points to prove the value of the channel and the importance it provides in your media mix.  

In this article, we’ll break down all of the attribution options in podcasts and how you can marry them together to develop an attribution plan you can feel confident in.

#1 –Direct Attribution

This is the easy stuff. The stuff you have the most control over.  For each podcast we run on, we create a vanity URL (i.e. and a corresponding promo code that the podcast will suggest for you.  You want to use the same promo code that other brands on the show use, so it increases the likelihood of a consumer remembering the podcast.  

Vanity URLs have several benefits.  First, if a consumer actually takes the time to type in, they are very high-intent and typically convert at an exceptionally high rate.  With that being said, we see anywhere from 5-30% of conversions come from this route, the lower end of the range being brands with minimal to no offer (i.e. Insurance companies who can’t offer a discount), while the higher end of the range may just drive to a URL with no promo code, but put an exceptional offer on the URL leading more people to actually to go the URL. We then pull this information from GA4, Shopify, and/or a brand’s order management system to establish the direct sales we’re seeing for each podcast.  


#2 – Post-Purchase Survey

If a brand doesn’t have a post-purchase survey, during our kick off process we strongly encourage they consider signing up for one, not just for our channels but for the zero-party data it provides for your entire marketing mix.  Fairing and KnoCommerce are the two companies we come across most often.  

For brands that do have a post-purchase survey, we recommend adding “Podcasts” to the survey.  If you can add a secondary question, you can include a question like “Which podcast?” with all of the podcasts you are running on. We often find “Other” capturing a lot of response too, with many people typing in the name of the host or podcast that they heard us on.  

Next comes the fun part. We need two key metrics from the post-purchase survey:

#1 - The number of people who responded with our channel (i.e. Podcasts).

#2 - The percent of people who respond to the post-purchase survey.

#2 is critical because most surveys aren’t required for consumers to respond to so many brands hover in the 30-35% range on average.  

As an example:

If 100 people respond to a post-purchase “How did you hear about us?” question with “Podcasts”, and the survey has a 50% response rate, we double the 100 responses to get to 200 total conversions that were driven by podcasts.  

Now at this point we can get into the merits of full attribution versus partial attribution because the person likely was impacted by other channels like search or social on their conversion journey, but if I had the solution to multi-touch attribution advertising I wouldn’t be writing this article right now, I’d be on my private island somewhere, so we’ll save that discussion for another day.

Want to share your thoughts or pick the brain of the author of this piece? Email Eric Smith at

#3 – Podscribe

Last but certainly not least is Podscribe.  We work with them on almost every one of the dozens of podcast brands we work with because their data is extremely valuable.  

How Podscribe works is their attribution technology is on the majority of the top 2,000 podcasts that an advertiser would consider partnering with, and they require you getting their basic tag implemented on their site (FYI – If you are on Shopify it’s incredibly easy) so they can see Bob Jones downloaded a podcast at IP address 123 and then Bob Jones came to a brand’s site and purchased at IP address 123.  

The challenge comes in for what’s called Noisy IP addresses.  What if Bob is in an office?  At a Starbucks?  What if he downloads a podcast on his way to work but purchases the product at home?

All of these variables mean Podscribe will never track 100%of people cleanly, but similar to the post-purchase survey methodology outlined above, if they track 50% of people cleanly they will model the last 50%assuming they acted the way the first 50% did. If they track 30% of people cleanly they will model the last 70% of assuming they acted the way the first 30% did. You get the idea.  

If you’ve ever done connected TV advertising, the attribution methodology is often very similar.

Podscribe also provides a ton of other value, like tracking impressions so we know if we need a makegood from a podcast and allowing us to export a ton of valuable information like Order IDs so a brand can look up sales in their system and verify the sales a podcast drove for their own due diligence.  

(Before I move out of this section, shout out to the team at Podscribe.  They are responsive, kind, and wonderful to work with.).  


#4 – Marrying It All Together

Once you’ve got all of the above in place, you can start your podcast journey.  The key will be to use all of the data points side-by-side for a gut check of the data.  If the post-purchase survey is showing 200purchases from podcasts, but Podscribe is showing 2,000 purchases, the truth is probably somewhere in between.  

As a brand starts to scale and they graduate to larger podcasts, we’ll even do lift analyses because we often hear from brands “Woah my Amazon sales were double what they typically are.  That must be because Podcast XYZ dropped today”.  Because podcasts can only see direct attribution on a brand’s website, companies with a meaningful presence on other platforms like Amazon won’t be able to see the full picture, but they will see signals like this that show podcasts affect other channels.    

Attribution in podcasts is far from perfect, but it’s come along, long way, and it has a lot more attribution than other offline channels like package inserts and direct mail. The key is knowing how to connect all the data points together and constantly validating all three data sources to evaluate the success of a podcast and if it is hitting your lower-funnel goals.  

Eric Smith is the SVP of Growth at Incremental Media.  Want to share your thoughts or pick the brain of the author of this piece?  Email Eric Smith at

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