How to overcome complexities in podcast advertising through identity resolution

30-second summary:

The rise in popularity of podcasts has opened a new door for audio advertisers, but measurement and showcasing its role within attribution models remains complicated
One way to solve for complexitiess that come with podcast advertising is by identifying “who” is listening since understanding “where: and “when” remains a challenge.
As podcasts continue to soar in popularity, the medium is becoming a mainstay among brands as a core part of their omnichannel campaigns.
With the presumed continued growth for the podcast industry, it’s imperative for brands to have access to platforms that enable efficient spend and reliable measurement and attribution.

Podcast is quickly becoming 2020’s ‘news radio’ replacement. Listeners are spanning an age range never seen before by talk radio; and these new, open-minded users are hungry for audio content across every topic imaginable.
From news and celebrity gossip to sports, op-eds, dating, crime and food and wine– there’s a podcast for everyone.
This is fantastic for podcast publishers and hosts, and it’s also great for audio advertisers–but with the rise of a new platform of streaming content and embedding advertisements comes a new set of challenges that we’re only just scratching the surface of today.
When the ‘Serial’ podcast first hit the market in 2014 it unknowingly opened the door of opportunity for content creators as well as podcast distributors.
For so long, Apple iTunes has been the sole proprietor of nearly all of America’s podcast consumption, but with the rise to fame of ‘Serial’ came a new wave of audio.
Users and creators quickly realized the value of uploading podcasts to streaming platforms– where users had already converted the majority of their music listening to, from the aforementioned iTunes monopoly.
Spotify suddenly had a major stake in podcast listening and advertising. Over the last few years it’s grown its market share of podcast listens to 20%.
Podcast is part of an omnichannel advertising strategy
The rise of podcasts opened a new door for audio advertisers, who, for years, treated ads in podcasts like they would pre-roll; embedding pre, mid, and post ad spots formulaically across all content in hopes that users would stay tuned long enough to hear as many ads as possible.
Thankfully, ad placement within podcasts has begun to evolve– and along with it so has measurement and attribution of those ads. As technology takes hold on this rising media form, new challenges emerge for advertisers and marketers.
Namely –with so many channels folding into today’s digital media strategy, how does podcasting play a role in the consumer journey; and more importantly how can we measure and showcase its role within attribution models? It’s one thing to know people are listening– it’s another to know how to capture them in analytics.
With that, we turn our attention to one of the newest players in ad tech- podcast analytics platforms.
The sole intention of companies like Chartable, who measure over a third of today’s podcast downloads, is to provide marketers with tangible, reliable podcast data that can be used to fuel omni-channel media strategies.
It’s only natural that podcasts take on their own identity- as agencies have designated new planning teams to them and advertisers are crafting custom audio ads for them.
Now, the Chartables of the ecosystem can help explain how they’re all working together for more efficiency and better targeting.
Complications in ensuring ad relevance
Half of this battle lies in the complexities of iTunes vs. Spotify.
Traditionally, users would download podcasts from iTunes at home or at work while they had a solid internet connection, and then save the consumption of those podcasts for their commute home or the coming weekend, etc.
Ads would be embedded in these podcasts way before they hit local storage on your device– so the relevancy and alignment of those ads was, well, a crapshoot.
But now, progressive downloads and streaming podcasts allow for a more real-time placement of advertising and thus stronger contextual alignment to both the user and the subject of the podcast.
Great news, yes! But, that’s only solving for the relevancy of a single touchpoint for an advertiser to a consumer. How do you reconcile that with the rest of your digital media efforts?
Identifying podcast audiences across devices
Identity resolution, explained simply, is the ability to connect one digital ID to the rest of the devices and IDs owned by the same user; and take that a step further by connecting those devices and IDs to the other users/devices/IDs within the same household.
These user and household clusters form targetable and scalable audiences for advertisers. In addition, they provide a holistic view of one touchpoint to all potential touchpoints for attribution and measurement.
For podcast advertising, this is essential. Because the ‘when’ and ‘where’ is already such a challenge based on download vs. streaming podcasts; being able to solve for the ‘who’ is invaluable for marketers.
Knowing what other ads were delivered to the same user across channels and devices can help shape a podcast advertising strategy as well as justify podcasts as a means toward branding favorability and ultimately purchase decisions.
Platforms and brands can use identity resolution to declutter their data, leaving them with only the data they want in order to make connections between devices used for podcasting and other devices associated with the same individual and household.
As podcasts continue to grow in popularity among consumers, the medium is becoming a mainstay among brands as a core part of their omnichannel campaigns.
With this growth, it’s imperative for brands to have access to platforms that enable efficient spend and reliable measurement. Identity resolution will help solve these challenges, and ensure consumers can enjoy ad supported podcasts for years to come.
The post How to overcome complexities in podcast advertising through identity resolution appeared first on ClickZ.
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