How to Measure PPC Metrics & Attribution in a Post-Cookie World

Like many facets of the digital landscape, pay-per-click (PPC) attribution is going through growing pains. Yesterday’s PPC metrics are becoming increasingly irrelevant as we transition into a new internet era at a breakneck pace.

Regardless of which side of the online tracking fence you sit on, there’s no denying that growing privacy regulations, user-controlled data tracking filters, and the near-obsoletion of cookies are forcing marketers to rethink how to plan and measure PPC campaigns.

Although change can be scary, don’t miss the forest for the trees. Remember that PPC is still an unfathomably powerful strategy for generating revenue and brand awareness.

• In the United States alone, online advertising generated $259 billion in 2024.¹
• Search advertising accounted for 39.8%.²
• Display advertising accounted for 28.7%.²
• Digital video ads accounted for 24%.²

Simply put, PPC isn’t going anywhere. As digital marketers, we just need to reevaluate our approach and do our due diligence to make sure we’re following, reporting, and leveraging accurate data. After all, how we measure PPC campaigns directly informs our next moves.

In this guide, we’re going to explain why antiquated analytics models have failed us and provide actionable steps you can take to start accurately and confidently gauging the true performance of your PPC campaigns as we’re all collectively ushered into the new age of ads.

Frequently Asked Questions

How do you measure PPC?

Traditionally, PPC performance is measured by tracking key performance indicators (KPIs) like impressions, clicks, and conversions, and comparing the cost of the campaign to the revenue generated. 

What is the goal of measuring PPC performance?

The goal of measuring PPC performance is to accurately assess if the campaign should continue, end, or be adjusted.

What is a PPC metric?

When you measure PPC performance, you use metrics, or data points, such as cost-per-click (CPC), click-through-rate (CTR), or conversion rate. These metrics are important indicators that show whether or not the desired outcome is being achieved.

What is attribution in PPC?

PPC attribution is essentially giving credit where credit is due. It’s the process of pinpointing why someone clicked and/or converted so that similar strategies can be reproduced and scaled.

What is last-click attribution?

Last-click attribution is an outdated PPC measuring performance that gives all of the credit for a conversion to the final click on the customer’s journey. Last-click attribution is problematic because it overlooks the many other possible touchpoints that led to the final outcome.

Closing the Chapter on Last-Click Attribution

When we measure PPC performance, the goal is to take what worked and do it again, but bigger and better. Continuously reusing and refining winning strategies naturally leads to increasingly successful campaigns and allows for informed budget planning.

The glaring problem with last-click attribution is that it oversimplifies the complexity of the average modern internet user’s journey. The days of linear A-to-B conversions are long behind us.  

Why Last-Click Metrics Are Unreliable

Imagine an iceberg in the ocean. At the iceberg’s tip, you have that last click. Underwater, you have a massive supporting structure that consists of upper- and mid-funnel efforts like consideration and awareness. Tracking PPC metrics based on last clicks ignores the crucial factors that cleared the path to conversion in the first place.

Furthermore, trying to measure PPC based on the final click fails to account for abstract and contextual factors like conversations the user has had about your brand or product, experiences they’ve had with your competitors, seasonality, and even their mood at the time of purchase (or bounce).

“Dark social” elements like word-of-mouth, online communities, and in-person events can contribute to and directly cause conversions, so why aren’t they getting more credit?

Can New Analytics Models Rescue PPC Attribution?

Data-driven attribution (DDA) models like Google Analytics 4 (GA4) leverage machine learning to analyze vast datasets with the goal of distributing credit across many touchpoints, rather than unfairly celebrating the last click. 

However, this way to measure PPC performance does have drawbacks of its own. Despite the cutting-edge tech behind them, attempting to track complex, cross-platform journeys barricaded by ad blockers and customizable cookie filters paints a fragmented picture. It’s like trying to follow a map after spilling your morning coffee all over it.

Common DDA Bottlenecks

• High Initial Data Requirements: GA4 requires a sample of 15,000 clicks and 600 Floodlight conversions within the last 30 days.³ Smaller businesses may have a hard time using it to track PPC metrics.

• Opacity: It’s not always possible to understand the how and why behind credit distribution. The results often feel esoteric and lacking in transparency.

• Incomplete Data: DDA models provide very limited insight into intangible factors used to measure PPC performance, such as cross-device interactions, non-Google platforms, and offline interactions and activities.

• Correlation vs. Causation: DDA models depend on correlation, not causation. In other words, you’re left wondering if the conversion would have occurred if the ad never existed.

Adapt and Evolve Your Methodology

It’s time to stop mourning the demise of perfect PPC tracking and move to the acceptance stage. Of course, acceptance doesn’t mean stagnation! With the loss of traditional PPC attribution comes the opportunity to reimagine our approach.
We’ve navigated workflow disruptions before, and we always come out on top. Rest assured, we have our own proprietary methodologies that allow us to measure PPC with a level of precision you won’t find anywhere else.

Without giving away too much of our secret recipe, we’re going to help you move away from the unattainable quest for perfect attribution and focus on actionable, pragmatic insights you can use to regain trust in your PPC metrics.

1. Revisit and Ramp Up First-Party Data Collection

As third-party cookies fade into oblivion, it’s time to start appreciating old-school, foundational, first-party data again. 

Now is the time to consensually capture and use as much customer data as you possibly can from channels like CRM (Customer Relationship Management) systems, analytics tools, and any of those “underwater” touchpoints that third-party cookies are missing.

2. Integrate CRM Systems and Ad Platforms

Measure PPC performance by integrating your CRM with ad platforms to track user behavior and keep an eye on post-click actions. More importantly, don’t just track clicks; measure data that matters: real conversions.

3. Shift Focus to Incrementality

In today’s digital landscape, you must overcome the desire to measure success and failure through the lens of vanity clicks and even real conversions. PPC attribution doesn’t carry the same weight it once did. 

Focus on the behind-the-scenes factors that truly drive sales.

Instead of attempting to piece together highly complex online shopping journeys, ask yourself:

Which conversions wouldn’t have happened without the campaign?

Once you start identifying and crediting ads for causality and not correlation, you can measure PPC campaigns with as much confidence as possible in these uncertain times.

Separating cause and correlation can take some experimenting and A/B testing. For example, you could only show ads to a specific region and compare the conversion rate with the exposed and isolated groups. 

If the isolated group is still buying at the same rate, you know the ads are unnecessary. On the other hand, if the exposed group has a higher conversion rate, you can open up and scale the campaign without worrying about blowing your budget.

Make It a Habit.

Incrementality testing isn’t a one-and-done project to test the waters. It should be a core part of how you measure PPC performance and how you plan the next campaign. After establishing this framework, you can be confident that your PPC metrics are rooted in reality.

Leverage MMM for a Top-Down, Holistic Perspective

Marketing Mix Modeling (MMM) is a statistical technique that works top-down to provide a holistic view of which channels and activities are leading to specific outcomes.

While traditional PPC attribution tools and techniques work bottom-up at a granular level by designating credit for clicks and conversions to specific user-level touchpoints, MMM aggregates and leverages traceable, historical, non-user data to determine which channels and activities caused revenue generation on a much larger, long-term scale.

Why Use MMM to Measure PPC?

MMM doesn’t depend on cookies. Instead, it analyzes a broad spectrum of online and offline channels to reveal areas that perform well, diminishing returns, and cross-channel synergies.

How MMM Can Inform Strategic Decisions

Single-touch attribution models are narrow in scope. MMM allows you to take a bird’s-eye view of your all-encompassing approach to digital marketing and fine-tune your strategies and plan your PPC marketing budget accordingly.

• For example, MMM could show that video ads are still increasing brand awareness that drives sales, even though last-click data implies poor performance. 

• Or, it could reveal that email marketing and social media ads convert more frequently when used together than they do independently.

MMM should be used to measure PPC performance quarterly or annually. It’s not a substitute for short-term analysis, but it can shed light on elements of your PPC metrics that are easy to miss. Use MMM to plan the campaign and first-party data to follow it in real time.

Build a Synergistic Analysis Framework

Don’t put all your eggs (or cookies) in one basket. There isn’t one model that adequately covers the complex and vast scope of an internet user’s journey to conversion. Leverage a variety of tools to gain a more accurate and comprehensive overview.

Combine the individual strengths and weaknesses of data-driven PPC attribution, MMM, and incrementality testing to fill gaps and leaks in the overarching methodology. 

Hard Data Isn’t Everything

When you measure PPC performance, don’t overlook qualitative insights that can get lost in vast datasets. 

From customer surveys and reviews to social media chatter, you can glean a great deal of supplementary information from factors that digital tools don’t always take into account.

Teamwork Makes the Dream Work

With all of this talk about digital tools, it’s easy to forget the importance of the human element. 

When you have a group of hotshot PPC, SEO, and social marketers all vying for individual glory, results tend to suffer. Much like how credit shouldn’t be assigned to the last click, it’s important to remember that collaboration is the true key to achieving optimal outcomes. A closely aligned human team is such a powerful asset in a field rife with uncertainty.

When you measure PPC metrics, try to keep the whole team united around the ones that really matter. There’s nothing wrong with celebrating growth, but the goal is to create sustainable frameworks that keep delivering. Metrics like incremental revenue and pipeline contribution are much more valuable than quick gains. Keep your collective eyes on the real prize!

PPC Attribution Is Inherently Flawed (and That’s Okay)

Data tracking is imperfect, but you can still make it work, warts and all. The first step is embracing the new landscape instead of trying to fight it with rusty weapons. Abandon last-click attribution, and start learning how to measure PPC campaigns holistically.

As long as you adopt a unified, multifaceted framework that focuses on trends, patterns, and actionable insights, while also leveraging first-party data, MMM, and incrementality testing, you should be able to arrive at conclusions that are accurate enough to make highly informed decisions that consistently lead to ideal results. 

Reimagine Your Approach to PPC

In summary, we strongly encourage you to reevaluate your current PPC measurement strategies. Integrating first-party data, MMM, and incrementality testing will go a long way in helping you measure PPC metrics with confidence. Today’s experiments are tomorrow’s standards, so stay curious!

Perfect tracking is long behind us, but the ability to adapt and evolve is what separates leaders from imitators. As the industry’s top PPC specialists, we’re not only keeping pace with the changes, but crafting and shaping the solutions. Contact us for a free consultation.

Sources:

1. https://www.statista.com/statistics/183816/us-online-advertising-revenue-since-2000/

2. https://www.statista.com/statistics/190458/categorie-breakdown-of-us-online-advertising-revenue-2010/3. https://support.google.com/sa360/answer/15544604?hl=en