The Third-Wave of Advertising Analytics: The Future of Measurement

July 22, 2022 -
By Scott Konopasek

The third wave of advertising measurement is approaching, and it is bringing a tsunami of change. If you’re not using tools to stay ahead of regulatory and industry changes, your competitors and those working at agencies with the foresight to move into this wave will be reaping all of the benefits of an accurate, granular, real-time picture of advertising performance.

What does this all mean for us? It’s simple: digital marketing is about to get a lot harder for those who don’t keep up (think iOs14.5). Marketing teams won’t be able to rely on the easy-to-press buttons anymore, and will have to become savvier in their efforts. This means we’re going to need new tools and standards for measurement.

Wave 1 – Media Mix Models

The first wave of analytics began in the 1950’s. This is the classic Mad Men era of advertising and they only had a handful of channels to buy: TV, print, and radio. With this uncomplicated media mix, statisticians created Media Mix Modeling.

Media Mix Modeling (MMM) began in the 1950s when George Luft, an executive at BBDO began experimenting with different combinations of media to determine which ones would be most effective at reaching consumers. He used a grid system with rows representing different media channels and columns representing different types of ads (e.g., print ads vs. radio commercials). The intersections represented different levels of reach and frequency for each combination or groupings of media channels being tested.

MMM uses statistics to predict how changes in ad spend will affect sales. Media Mix Models are still used by many companies to analyze how much money they should spend on various marketing strategies so they can maximize their return on investment (ROI). Machine Learning and A.I. are being added to increase the accuracy of the modeling. The biggest weakness of MMM is how little data is used as an input and the heavy reliance on assumptions and estimates.

It wasn’t until about 2010 when the industry saw any real innovation creating a new measurement methodology.

Wave 2 – Multi-Touch Attribution Models

The rise of smartphones, digital identity, and the ability to track a user across multiple devices launched Wave 2 of Measurement. Before users had multiple devices (desktop, tablet, smart tv, mobile), advertisers only had to measure desktop and in-store conversions. As devices became more complex, the need to tie a single user across multiple devices became more and more important.

The solution to this new challenge was Multi-Touch Attribution (MTA). MTA took Media Mix Models and added in user-level tracking to track the paths of customers throughout their purchase journey. Multi-touch attribution uses a combination of media sources, such as display, search and social, to assign a value to each touch point on the path to purchase.

Multi-touch attribution models can be complex and are prone to bias. They require a significant amount of data, and they can be highly susceptible to manipulation by marketers. Vendors often do not have access to all of your data or might not be able to interpret it correctly. The biggest problem with multi-touch attribution models is accuracy – they rely on assumptions instead of actual behavior data.

Moving forward, both MMM and MTA will become less effective as the advertising ecosystem evolves and new regulations come into effect.

What’s Changing?

A series of advertising privacy changes happened between 2017 and 2020:

GDPR (General Data Protection Regulation) is a European Union law that protects the privacy of EU citizens. It requires companies to be accountable for how they collect and use personal information about individuals.

The California Consumer Privacy Act (CCPA) is a new law that gives Californians more control over their personal information online and imposes new restrictions on how businesses use that data.

iOS 14.5 is Apple’s mobile operating system update which introduces tools to help users understand and manage their data privacy settings, blocking user-level tracking online and in apps.

Coming next is Google’s Death of Third-Party Cookies, making it harder for advertisers to track users across multiple websites and target their ads accordingly.

These changes and future changes will make existing analytics methodologies less effective and marketers will need new ways to see what’s working in their ad stack, prove campaign effectiveness, and reallocate budgets to spend smarter.

Wave 3 – What’s Next

Privacy changes are forcing marketers to choose – Do you want to use an attribution technology that’s dependent on models? Or do you want to directly measure your ads, using analytics that don’t use estimations?

As millennials become more tenured in our careers, we are the ones now running marketing departments. We don’t know an advertising world that doesn’t include digital. We’re seeing a higher level of digital savviness across the industry. That’s leading marketers to understand that they can directly measure more impressions, engagements, and conversions.

For years attribution vendors have overpromised and under-delivered, sewing distrust with marketers. The Third Wave of Measurement will be defined by moving away from free platforms, brands owning their first-party data, Direct Measurement, and Bi-Modal Attribution.

The Ongoing Need for Measurement

Despite marketers’ distrust in measurement, it’s still mission critical for brands to measure their advertising results and review regularly. Every single ad budget is to be accountable to somebody. Somebody somewhere is writing a check for advertising and they are going to demand accountability.

Measuring results and having a unified view of all the activity is key to justifying budgets. Measurement is still paramount, but here’s the problem: most brands mistrust attribution, so most still use free tools because it’s easy.

Moving Away from Free Platforms

Free reports (Google Analytics and ad platform reporting) default to last-touch attribution, but last-touch/last-click doesn’t accurately reflect how buyers interact with your ads. The biggest problem with last-click attribution is that it encourages marketers to spend their budget in ways that are not necessarily the most effective. We very frequently see that when channels work together, conversion rates are much higher. Last-touch is overly simplistic.

With privacy changes, the walled gardens of ad platforms become more entrenched and the need for independent measurement will grow. Proper independent measurement will be able to deduplicate clicks and conversions to unify reporting and analytics so marketers can better see and prove how ads are performing.

Owned First-Party Data

As the Death of Third-Party Cookies nears in 2023 (now 2024, or maybe never?), brands will need better ways to collect and measure user data. Companies are testing and validating different solutions and workarounds to Google’s announced update.

Google did, however, announce their recommended solution: Server-Side Tracking. Instead of sending a cookie to your browser when you visit a website, the host’s server can just capture the information directly. So, the user’s web browser is no longer the gatekeeper on what information you can capture. This means that brands can set their own cookie expirations to last a lifetime and directly capture ad platform ID’s for better matching and reporting.

The next wave of measurement will sit on a foundation of owned first-party data.

Estimation-Free Analysis

The next era of analytics is Direct Measurement. There’s no reason to guess or estimate using statistical modeling when you can now actually measure ads engagements and results directly.

The big problem of Second-Wave (MTA) is that attribution data can be manipulated to tell whatever story a marketer needs to tell. Multi-Touch Attribution is subjective because it relies on models and estimations to assign fractional credit. We call this a ‘Narrative-First’ approach to attribution. Marketers have learned not to trust Narrative-First or Subjective Attribution. The future of attribution is data-first.

Data-first measurement doesn’t need models, estimations, or assumptions. Direct Measurement will simply measure and report what’s happening without any data manipulation. Direct Measurement will replace MMM and MTA as marketers opt for trustless solutions that put the truth before narrative.

Bi-Modal Attribution

The final characteristic of Third-Wave measurement tools is bi-modal attribution.

Any advertising tactic can deliver value in 2 ways (modes): it can lift conversion rates in your media mix or reach and convert net new audiences.

These are the two modes for attribution: media mix lift and channel incrementality.

MTA and MMM only estimate media mix lift and don’t report channel incrementality. They’re incomplete.

The future of attribution is bi-modal, where solutions will fully explain to marketers the value of their marketing channels in both how they lift conversion rates AND deliver incremental reach.

Staying Ahead

The digital marketing world has changed dramatically over the last decade. As a result, the advertising landscape has shifted as well. Consumers are more aware of the value of their data and they’re becoming more protective and skeptical of how it’s used. Much of the advertising industry has been built on third-party data and marketers are increasingly worried about the lack of transparency and control over how data is collected and used.

Choosing the right measurement methodologies and partners will be key to staying in control of your revenue growth and not falling victim to platform and regulatory updates.