It took a decade-long effort, but the Media Rating Council has finally released “Outcomes and Data Quality Standards,” its set of uniform standards for measuring the outcomes of advertising and media buys, along with the data utilized for that. As a result of years of debate, drafts and public vetting, the MRC's report creates a common reference point, definitions, processes and best practices for so-called "attribution" and ROI measurement, along with other higher order measures of campaign outcomes.
The move to standardize outcomes has been part of an ongoing process of identifying and developing standards for a rapidly-changing media ecosystem, in which new sources of data and analysis are constantly evolving as a result of technological innovation, enabling those in the ad and media businesses to look at things they could have looked at previously.
“This initiative began more than a decade ago with projects designed to standardize measures of ad delivery and has now progressed to the measurement of business outcomes that are associated with ad exposure," MRC Executive Director and CEO George Ivie says.
Up next for the MRC: creating a framework for standardizing next-generation processes such as AI and machine learning that are increasingly being used to process and analyze data that goes into and comes out of a wide variety of industry measures.
"We have built some standards information into things like outcomes and audience measurement and cross-media that deal with AI and modeling, so we’ve already created guidance within each major component," Ivie tells MediaPost. “But we haven’t seen the need to come out with, let’s say an 'AI standard,' or a 'machine learning standard,' because training those models, updating them, having a champion/challenger model and all of those approaches, they’re already pretty standard, because it’s not just for the media business. This goes on in all kinds of businesses. So right now, we don’t have a plan to do that."