What is OTT Measurement?
For many years, advertisers have attempted to measure the effectiveness of their television ads, which is much easier said than done. MMM (media mix modeling) or “TV attribution” (analysis done by some MTA providers and agencies) are the primary methods marketers have used over the last few decades when attempting to measure the effectiveness of ads on traditional linear television.
The advent of OTT (Over the Top) has finally given marketers line of sight to user level measurement of ad effectiveness and access to very granular log level data. Log level data includes attributes such as: DMA, time of impression, device characteristics, etc.
What is OTT?
OTT, or Over the Top, is the term for video content that is delivered via connected television devices (think Roku, Amazon Fire TV, Apple TV, etc.) over a high speed broadband internet connection. OTT is a very appealing substitute for satellite or cable television because it can be more affordable and offer a much wider array of content offerings and personalization options.
There are many advantages for consumers as they can access a wide variety of videos, movies and television shows on demand, and on the device of their choice. All you need is a high speed internet connection and a smart TV.
The key advantage to a marketer is that OTT can be a very effective and measurable channel for building brand awareness and acquiring new customers through a wide variety of ad inventory.
How to Measure OTT?
There are several tactics that can be deployed to measure the effectiveness or incremental contribution of OTT advertising. They’re broken up into two categories: audience split tests and matched market tests.
Audience Split Tests:
- Counterfactual (Ghost Ads): In the ghost ads approach, the ad delivery systems within the OTT provider’s ad platform implements a version of what’s called the ghost ads framework to collect data about audiences who matched a campaign criteria but were not served an ad because of other constraints, like budgets and competitive bids, in the auction. These audiences are then placed into a control audience whose performance is reported alongside the audiences who were exposed to ads within a campaign. This allows marketers to read the lift of a campaign without actually selecting control audiences and executing a control treatment.
- PSA Ads (Public Service Announcement or charity ad): In the PSA approach the control group receives a placebo ad, which in this case is a charity or public service announcement. The goal is to not stimulate the control group with a brand message, but to present the placebo ad one time for tracking purposes. The conversion rates for the test group (exposed to brand ad) and the control group (not exposed) are observed over a tracking window (typically 30 days) and the difference in conversion rate for each group informs incrementality.
Matched Market Tests:
- A matched market test is the preferred method when a clean audience split test is not available. A handful of small markets are identified as representative of a large market (ex. California, New York). In these “test markets” the desired treatments are applied for each of the OTT providers in the test such as going dark in one or two media tactics for a set period of time. The results from the test are observed and the difference in performance metrics (like conversion rates, revenue per user) between the test and control are then interpreted to inform incrementality.