How to Avoid Misrepresentation of Data

Audience creation data has surged in recent years, but accessing behavioral data with the same precision has been all but impossible. Here’s how to avoid the guesswork.

Digital advertising is everywhere. Some of us may have a hard time remembering life before it, but digital advertising has only been around for 20 years. It’s grown up quickly in this time, maturing into a targeted, personalized experience in which advertisers increasingly leverage rich behavioral data to build effective audiences and impress the right message upon existing and potential customers.

But measuring the effectiveness of digital advertising has not progressed as meaningfully and remains a relatively immature practice.

While the data available for audience creation has exploded in recent years, accessing behavioral data at the same granularity for measurement is challenging, if not impossible. This often leads measurement partners to take a “best guess” approach to sales attribution or model off of a small panel of known customers. A lack of verified, holistic data leads to misrepresentation of results and, crucially, may misinform future investment decisions. When bad information is fed to decision-makers, it only makes sense to expect stagnation in actual growth.

Partners who are transparent about the methods by which they collect data, match test and control groups on verified attributes, and report on the efficacy of media exposures via verified purchases will demonstrate the most reliable and repeatable returns on assets.

Retail media platforms are upending the status quo in digital media measurement, bringing accountability by leveraging rich first-party data to tie viewable, verified media exposures to actual purchases online and in-store. These platforms use a combination of loyalty card capture (very reliable), credit card data (partially reliable) and other methods to close the loop between media exposure and purchase, ideally verified 1:1. How retailers and their advertising partners use this data is the single most important factor driving material gains in performance and efficiency, while holding media accountable to real results.

That leads to the most important question: How? Trust between media platforms and advertisers is built upon the foundation of viewable, non-fraudulent inventory and the methodology by which results are reported to inform and influence continued investment. Gone are the days in which “comparing to the average” or “modeling off a 10% sample” will cut it. How it’s done matters.

Partners who are transparent about the methods by which they collect data, match test and control groups on verified attributes and report on the efficacy of media exposures via verified purchases will demonstrate the most reliable and repeatable returns on assets. It’s also crucial to consider how different methodologies demonstrate divergent results and therefore cannot be compared side by side.

This should lead advertisers to ask themselves a few key questions: What data is feeding your analysis? How do you understand which customer groups contributed the most to sales lift? What percentage of your impressions tie directly to a verified purchase? Do you trust the methodology enough to use that information to influence future decisions?

Image courtesy of Pixabay.