Measurement and currency are some of the hottest terms in TV right now as the tug-of-war battle between panels and ACR continues to take center stage. (ACR is a technology built into smart TVs that is used to identify and verify what is actually playing on the device). But in the year ahead, it’s not about crowning a winner, it’s about leveraging them together.
To take a deeper look at the current state of TV measurement, esteemed industry analyst Alan Wolk sat down with Adam Helfgott, CEO at Madhive, the streaming TV advertising infrastructure that powers campaigns for brands, agencies, and local broadcasters such as Fox, Scripps, and TEGNA.
ALAN WOLK (AW): How has TV measurement transformed over the past years?
ADAM HELFGOTT (AH): Nielsen panels have been the reigning champion of measurement since the early days of TV, bringing scale of 10,000 to 40,000 households and setting the industry standard. But the digital TV revolution resulted in the fragmentation of delivery methods, and ACR data emerged as the leading contender to de-throne Nielsen.
The problem is that ACR data is limiting. It only measures what’s being watched on TV, not who is sitting on the couch watching. Knowing which household members saw a show or ad is a major hurdle for both advertisers and programmers. The industry mostly relies on probabilistic extrapolations. So, if there is an NFL game on and a 55-year-old male is in the house, it is probable that he is the one watching.
This is TV’s current culture clash in a nutshell. The only way to resolve it is to end the tug-of-war match and utilize the panel and person-based data to back up the household-level ACR data, which helps brands feel that they are hitting the right streaming consumers in the right places. This is why panels are so hot right now, and why we recently saw alt currency provider iSpot invest in panel-based measurement platform TVision.
AW: So this is where we start to get into the issue of transparency, right?
AH: The issue of transparency and “who is on the couch” are some of the biggest challenges in the industry right now. On traditional linear TV buyers know exactly where their ads will run, right down to the position in the ad pod. On digital TV, however, buyers typically only get insight into what platform the ad ran on, but oftentimes not the channel, network, or show.
Since panel data for CTV has still not fully matured, advertisers don’t know who in the household was on the couch when the spot aired. Therefore, savvy TV buyers are often in the dark about who is actually being reached and left to rely on a hodgepodge of 3rd party services and data to try to piece the puzzle together.
This is one of the big causes of widespread inefficiencies throughout the industry, from planning campaigns to inconsistent and inaccurate measurement standards, and lack of transparency in reporting. It also leads to advertisers not knowing how best to spend their ad budgets, how to evaluate their campaign’s performance, and whether their campaigns achieved the desired results.
AW: What are some of the doors that open when you start to integrate panel and ACR data?
AH: It allows us to build efficiencies across various POVs. By leveraging panel-based data to understand who is watching within a household, we can then combine that with ACR data to find the true price of inventory for a specific demo target.
With that problem solved, we can make good on a promise: truly making TV a performance channel. Like buying ads on Instagram, we’re providing advertisers with the ability to choose their goals — reach, awareness, website visits, app downloads, and even sell-through metrics — and then predict and optimize across platforms.
AW: Madhive’s initial success was helping local broadcasters transition to streaming — how does local factor in here?
AH: We’re evolving that conversation one step further to the “nationalization of local”, and helping customers predict and track their exposure metric goals to determine a baseline of saturation at the local level. This means advertisers can spend money in geographic areas until those outcomes are reached, then automatically shift spending to less-performing geo segments.
For example, a national auto dealer can activate hundreds of local campaigns simultaneously, while optimizing against website visits, in-store visits, or even inventory. Once those are reached, the spend is shifted to other locations around the country to achieve the desired results. It truly is the “Waze of Programmatic.”
To learn more, visit Madhive.com