The Next Era of E-Commerce Measurement and Attribution in a Privacy-First World

In a privacy-first world where new technologies are evolving rapidly, the digital marketing industry is experiencing an upheaval due to its historic lack of standardized measurement and attribution. As e-commerce businesses struggle to adapt their approaches to performance reporting, companies that don't prioritize deeper analytics investments will face greater challenges than others. Let's take a look at the factors that need to be considered when allocating these investments.

The Dangerous Lack of Consistency in Measurement

The lack of consistency regarding measurement and attribution in the digital marketing space isn't new, but recent industry changes have greatly exacerbated it. The sheer speed of the advertising industry and the evolution of its careers are key reasons there is no standard for measuring advertising value.

Many e-commerce marketing professionals started in one form of advertising: Google Ads, Meta, Amazon.com, email, search engine optimization — you name it. The multitude of entry points into our industry has yielded a variety of perceptions about what metrics to use for setting goals. The variance of these lenses influences how businesses view marketing and what data is trusted in making decisions.

At the same time, the shift to Google Analytics 4 (GA4) this year has caused changes in reporting while simultaneously opening the door for conversations about alternative ways to measure success. From a practical standpoint, the move from Universal Analytics (UA) to GA4 requires internal reports to be updated. The learning curve required to do so with GA4 has proven steep enough to prompt some businesses to consider alternative measurement tools for performance reporting, such as their e-commerce platforms, third-party cross-channel attribution tools, or platforms like Klaviyo. Depending on the type of business and how its marketing is structured, some of these tools are more useful than others.

In short, there was tentative stability regarding e-commerce campaign measurement. And now, even the UA data that did give some semblance of stability has been upended, lessening confidence in performance and leading to delayed decision making.

The Impact of Third-Party Cookie Deprecation

At the same time, leading to more confusion, cookie deprecation is negatively affecting the ability of e-commerce marketers to target audiences and understand the impact of their campaigns. Individual channel return on ad spend (ROAS) is being met with more skepticism: Is performance worse because audience relevance is weaker? Or are we getting worse measurements due to less visibility into ad interactions? This skepticism, like the challenges caused by the shift to GA4, is also leading to greater acceptance of new forms of measurement.

We've seen this before. In 2021, Apple limited first-party cookies to seven days and third-party cookies to 24 hours. This change required Meta (then Facebook) to alter its standard attribution window from 28 days to seven days. The result was that e-commerce marketers saw less measured value for their campaigns on Meta since they had lost the ability to map users who saw or interacted with those ads more than seven days ago. Meta advertising was still valuable, there was just less value recorded in the campaigns since the ad interactions were beyond the seven-day, first-party lookback window.

Marketers face a similar but even more complicated conundrum with the removal of third-party cookies in Chrome. Third-party cookies on Chrome aid in ad relevance, not just measurement, so it's unclear what the full effect of deprecation will be. Will cookie loss make audiences less relevant and cause costs to go up? Will ads stay relevant while measurement deteriorates, leading to a perception of performance decline? Will it be some degree of both? Regardless, neither impact is great for small or midsized businesses that rely on marketing efficiency to thrive.

At the same time, our industry has become increasingly dependent on AI-driven platforms to identify attributes of individual users and map them to relevant types of ad campaigns. These tools are losing their detailed, user-based relevancy of the past 15 years and are giving way to broader AI-driven audience approaches. These AI ad platforms now require more data and time to "train," leading to higher advertising costs as the tools learn where a brand's ads are likely to be most effective.

The Path Forward for Measurement and Attribution

To ensure greater sustainability and consistency going forward, the future of digital marketing measurement and attribution needs to focus on more holistic ways of measuring than it has in the past. While measurement has been a longstanding challenge for our industry, recent privacy changes have finally pushed the importance of this issue to the forefront. Now, in an era when it could become more expensive to advertise effectively, measurement techniques need to be well understood for businesses to make better decisions.

Implementing media mix modeling for budgeting and first-party data for online advertising attribution will help marketers make better decisions. Media mix modeling is a cookie-less way of measuring advertising across different channels to help decision-makers with budgeting and performance expectation setting. Meanwhile, first-party attribution tools can help your channel specialists understand the impact of their advertising as a part of the whole, outside of individual channel ROAS measurements. However, these techniques will require some work to ensure campaigns are properly tagged and considered within various tools.

A proactive strategy will also be crucial when it comes to measuring tactical value. Strategic campaign planning enables teams to design controlled tests and target specific measurements to gauge success. Identifying the segments that are key to your business and forming hypotheses around those segments is a great way to start planning and measuring the results of your marketing tactics.

Meanwhile, AI is constantly advancing and changing, so it's critical to consult with experts who understand the impacts of these technologies. Ensuring you understand which tools to use, how advertising journeys interact across platforms, and how to measure tactical marketing changes will help you gain a clearer understanding of campaign performance, leading to better decisions.

The media measurement and attribution challenges marketers face today — from GA4 to cookie deprecation to evolving AI tools — represent some of the most consequential happenings in the e-commerce industry in more than a decade. To remain competitive, marketing leaders must identify new, holistic ways to understand the impact of their marketing efforts.

Chris Charczuk is senior director of data science at Agital, a company that unites agile strategies and innovative technology to deliver marketing services that create measurable impact for its clients, partners, employees and the industry.