Data is one of the biggest —if not the biggest — drivers of successful marketing today.
But when it comes to OTT data, there’s an awful lot to weed through.
Don’t worry, we’ve got you — in this post, you’ll learn the types of data available for over-the- top (OTT) advertising, how they’re collected, and best practices for building data-driven OTT campaigns.
Download the full ebook here: Your Guide to CTV Data—How to Target and Optimize Campaigns
First things first: let’s get a handle on some OTT data definitions.
OTT data falls into three overarching buckets, and you’ve probably heard them before.
First-party data refers to the information you collect through your own sources, such as traffic from your website or responses from a survey you sent out to your own CRM contacts.
Second-party data includes the information you collect from someone else’s first-party data. This data is most often exchanged through direct partnerships between businesses. For example, a hotel booking website may collaborate with an airline company to mutually benefit from each other’s data sources.
Third-party data is information gathered from a data provider or aggregator. Usually, this data is consolidated through various means, including a variety of websites and platforms (more on this below!).
Third-party data aggregators collect information from consumers and work with advertisers to build targeting segments (while protecting consumer privacy and personal identifiable information, or PII).
Within the 1st, 2nd, and 3rd party umbrellas, there are a few more granular data classifications that help us get to know our audiences.
Primary demographics comprise the most general consumer characteristics. Primary data refers to the most basic traits used in demographic targeting: age, gender, income and education.
Advanced audience demographics include information that tells us about a consumer’s lifestyle, affinity, and propensity to buy. Advanced demo data is broken down into:
Event-based demographics comprise the specific behavioral or location-based actions of a consumer. These actions may relate to a consumer’s travels, purchases, viewership, and more:
Related content: What is OTT advertising? A Beginner’s Guide to Over the Top
So, there’s a ton of data that can inform your OTT targeting and help you to optimize your campaigns — but who collects it all?
When it comes to first-party data, the answer is obvious: you do. Many brands are turning to customer data platforms (CDPs) to bring together all of their owned data in a single location and use it to create a more complete view of each customer.
The partners you choose to work with collect their own first-party data, which becomes your second-party data. Sharing this data between partners in a privacy-compliant way can get a little tricky — many businesses look to data clean rooms and private identity clouds for this sort of sharing.
Third-party OTT data is a different ballgame.
There are a few major third-party data vendors in the OTT space. Marketers partner with these aggregators to bolster targeting and optimize campaign performance.
Examples of data vendors include Experian, LiveRamp, Acxiom, Epsilon, and TransUnion.
All of this OTT data plays an important role throughout your streaming video advertising campaigns.
Although advertisers approach the space in vastly different ways, there are a few best practices you should always follow when it comes to OTT targeting, forecasting, optimization, etc.
Many advertisers focus on targeting specific programs (e.g. House of the Dragon, Handmaid’s Tale), publishers (e.g. Discovery, National Geographic), or platforms (e.g. Hulu, Prime Video, Disney+) — but they should be targeting audiences instead.
Addressable advertising allows you to deliver ads at the household level to maximize contextual relevance. Instead of saying, “I want to place an ad during Hoarders on Discovery,” focus on which kinds of people will be most susceptible to your messaging, such as “women, ages 35-55, who are in the market for organizational products.”
When it comes to planning OTT, you should lean on digital forecasting tools to determine the size of your target audience and what ad inventory is available to reach this audience. The best forecasting tools integrate 1st, 2nd, and 3rd party data to beef up the base of information you’re building your campaign on.
Say you want to run a campaign targeting females between the ages of 25 and 54 who live in Texas and exercise multiple times a week.
Plug those attributes into a suitable forecasting tool to determine how many people fit the bill. Then use the tool to cross-reference that segment with available OTT inventory. Use the output data to weigh the feasibility and cost-effectiveness of executing your campaign.
Related content: Planning an OTT Campaign? Traditional Ad Tech is Failing You
The ability to use data to optimize campaigns is one of the most valuable aspects of OTT advertising. At its simplest, you can optimize your results by looking at top performing ad placements, then weighting delivery more heavily toward those placements.
You can optimize campaigns based on metrics like KPIs, completed views, budget relative to impressions, and more. Many companies have dashboards that allow you to gauge performance in real time, allowing you to make updates to your campaign at any point during the flight.
Running live ad experiments within a wide audience pool (with a large sample size) allows you to understand and connect audience variables across the entire bidstream. Insights from this OTT data allow you to optimize your targeting and bidding based on real-world outcomes.
This process can help you differentiate your campaign strategy from competitors, increase campaign efficiency, and uncover targeting insights for future campaigns.
Many marketers take a “set it and forget it” approach to audience targeting because that’s how ad campaigns were traditionally run.
But when you’re running experiments throughout your campaign, you need to be able to act on those outcomes.
The best ad tech platforms let you fine-tune campaigns in-flight to continually adjust the audience segments you’re reaching based on ongoing performance. Advanced technologies like machine learning and AI help you save time, increase the accuracy of your targeting, and automatically save key learnings to optimize your future campaigns.
Retargeting ads across devices and media types helps augment campaign frequency and keep your message top of mind for your audiences. The tactic creates more consumer touchpoints, which means higher conversion rates and more behavioral data to integrate into your optimization efforts.
If you want to determine the effectiveness of your campaign and the return on your ad spend, you need to track and attribute campaign conversions. Innovations in smart TV device technology allow you to measure OTT performance digitally — and beyond impressions.
If you’re trying to understand more direct business metrics, such as web traffic or in-store visits, consider the measurement strategies like:
As audience data becomes more and more valuable in OTT, marketers must be more cognizant of what types of data they use, how they use this data, and why they use it.
MadHive’s literally built for this, and here’s how:
This combination of data flexibility, real-time insights, and privacy/fraud protection provides you and your buyers the depth, scale, speed, and security you need to reach campaign goals.
Learn more about planning, executing, and measuring out-of-this-world OTT campaigns with MadHive. Check out our OTT platform today.
