How to adapt your marketing measurement as privacy changes take hold

May 1, 2024


When it comes to recent privacy changes, marketers are like frogs in boiling water (yes, you read that correctly).

If you put a frog in hot boiling water, it will immediately jump out. But according to urban legend, a frog will stay in slowly warmed water, even when it boils. Why? Because the frog doesn’t perceive the gradual danger. 

Marketers are in that deceptively lukewarm pot, and many don’t even realize it. 

Apple, Google, and regulatory bodies have slowly increased the temperature since 2018 by releasing privacy updates every year. Marketers know these changes are happening, but many don’t realize how much these shifts impact the way they track campaigns—specifically, how they understand individual users’ behavior. 

These privacy restrictions are here to stay (and will probably intensify), so now’s the time to adapt your analytics strategy. In this post, we’ll break down the most important privacy shifts impacting marketing analytics and share actionable recommendations for evolving your measurement methods. 

What privacy changes are impacting marketing analytics?

Google, Apple, and regulatory bodies have made the following privacy changes over the last few years. These updates make it challenging for marketers to track clicks, taps, and touches at the user level and tie those interactions directly to sales. 

Third-party cookie restrictions

Nearly every website has a cookie consent banner today due to the 2018 General Data Protection Regulation (GDPR). Any site with EU and UK visitors must comply with GDPR by asking people if they want to accept or reject non-essential cookies. 


GDPR set off a wave of new privacy laws in recent years, with states like California, Virginia, and Colorado enacting their own cookie consent legislation in the following years. Cookie consent banners have become ubiquitous as most companies must follow these regulations.

What does this mean for marketing measurements? If your site visitors reject third-party cookies through these banners, you won’t be able to monitor their activity through GA4 and other analytics platforms. GDPR doesn’t consider analytics cookies—the ones that enable tracking through GA4—essential. 

Following GDPR’s lead, major tech companies have blocked (or are in the process of blocking) unnecessary cookies. 

Given these changes, third-party cookies are no longer a feasible way for marketers to track consumers’ site activity. 

Link tracking protection

Many marketers track campaign engagement with UTM codes. Analytics tools like GA4 or Hubspot’s internal tracking monitors URLs with UTM tags to show marketers the source of link clicks, like Facebook or their email provider. 

But in 2023, Apple restricted this measurement technique with its iOS 17 update. The company now strips out UTM codes from links in Apple Mail, Messages, or private Safari browsing. 

Link redirects are a current workaround to this update. Set up the URL to add the UTM tags on the redirect, and Apple won’t detect and remove the codes. For example, the email marketing platform Klaviyo uses redirects to track links

This fix, though, is just temporary. We expect Apple and other tech platforms to restrict UTM tracking even further in future updates, so it’s best to find long-term solutions that don’t rely on these codes.  


Beyond following formal regulations and platform rules, marketers must also change their personalization strategies to fit consumers’ changing attitudes towards the practice. People increasingly feel uneasy about companies leveraging real-time data on their actions and locations to send hyper-personalized campaigns.

Consider research from the marketing platform Marigold’s 2024 Global Consumer survey. Sixty-one percent of respondents reported that they found campaigns based on third-party cookie tracking creepy, compared to just 39% who found it cool. Likewise, only 36% of consumers said location-based ads from brands they don’t recognize are cool, while 64% found them creepy. 

The main takeaway from this data? Most consumers are put off by hyper-targeted marketing based on information they didn’t share. To stay on their audience’s good side, marketers should use zero- and first-party data instead.  

How to adapt your marketing measurement techniques

In light of these privacy changes, brands can’t rely on old methods of tracking individual campaign engagement. Instead, choose alternative privacy-friendly measurement techniques, like MMM and experiments, that use aggregate-level data. These methods enable marketers to gauge their campaigns’ incremental impact without monitoring single users. 

Estimate your campaigns’ impact with marketing mix modeling

Marketing mix modeling (MMM) is a statistical technique that uses historical performance data to gauge and forecast each channel’s incremental impact. By analyzing the relationship between channel performance data (such as impressions or traffic) and sales, MMM can help you answer questions like:

  • What is the ROI of each marketing channel?

  • How much sales lift is attributable to marketing vs. other factors?

  • Where should the next dollar be allocated for maximum impact?

Critically, MMM doesn’t require user-level tracking. The only inputs needed are aggregated channel and sales data. This approach complies with privacy changes restricting monitoring individual activity with cookies and UTM codes. Plus, MMM provides a comprehensive view of marketing performance by accounting for both online and offline efforts.

MMM historically has been too expensive and time-consuming for organizations, but recent advances in data processing and machine learning have made the methodology more accessible than ever. Paramark users only need one year of daily marketing data to get their models up and running. 

Confirm your campaigns’ impact with incrementality testing

While MMM is a powerful tool for estimating incrementality, keep in mind it reveals correlations, not causation. Run marketing experiments known as incrementality tests to prove your campaigns’ impact. 

Like MMM, marketing experiments are privacy-friendly because they rely on aggregate data rather than individual tracking. You’re comparing target metric outcomes for groups of consumers—one test group that’s exposed to a channel with your campaigns and a control group that doesn’t see your brand’s marketing on this channel. This setup isolates channel exposure as the cause for performance differences so you can confidently optimize your marketing spend. 

Say your MMM shows a strong positive correlation between billboard campaigns and sales. To test this relationship, you could compare one region with your brands' billboards to a similar area without billboards. If sales are higher in the former region, that’s a clear sign to increase your billboard budget. 

As you run tests, feed experiment results back into your MMM. This data will help your model estimate each channel's incremental impact even more accurately.

Goodbye individual tracking, hello incrementality

Add up five years’ worth of regulations, tech companies’ tracking restrictions, and consumer privacy concerns. What do you get? A world where you can’t track users down to every click and device.

That doesn’t mean returning to the dark days when marketing measurement was just an educated guess. Instead, you can aggregate customer data and analyze it with MMM and testing. These measurement methods aren’t just compliant—they provide an accurate view of campaigns’ impact by applying sound statistical techniques to large amounts of data.  

Ready to start your incrementality journey? Contact us today for a free demo to learn how teams are measuring campaigns in the privacy-first era.