Relying on last-click attribution is like taking a photo as the last lick of paint goes onto your new custom home and expecting that picture to represent the whole build. It ignores all the planning, teamwork and expertise that went into the process.
In the same way, last-click attribution overlooks the many touchpoints like social media, content and ads that led your customers to take that final step. It misses the foundational work that made the sale possible.
Adding multi-touch attribution (MTA) will show you more details, like how the cabinets were installed and where the lighting fixtures were hung, but you still don't have information to help you understand the work and resources required and what steps made the biggest impact.
Last-touch and multi-touch attribution simply don’t go far enough in measuring your channels' overall marketing effectiveness. You need a holistic measurement paradigm that assigns credit where credit is due to fill the gap. That’s where triangulation comes in.
Marketing measurement triangulation offers a more comprehensive and accurate picture, accounts for foundational steps that build up a campaign and truly helps you determine the best way to invest your marketing spend.
The evolution of the marketing measurement paradigm
When it comes to your campaigns, multi-touch attribution (MTA) might capture a lot of the process, but the primary focus is still on the finishing touches. It often overlooks the critical early stages that make a successful campaign possible, like brand building and establishing trust with your market.
In terms of your customer journey, if MTA assumes that all conversions came from paid ad campaigns, for example, it doesn’t capture the impact of all the organic work and offline marketing that you’ve been doing. However, the reality is that there could have been multiple unseen points along the customer journey that led to the conversion.
Multi-touch attribution may work brilliantly for tracking paid digital touchpoints across digital-only channels, but your marketing mix might not be that straightforward.
With marketing efforts spread across multiple channels (online and offline) and a mix of paid and organic, you need a method that gives you an accurate view of exactly which touchpoints contributed to the sale — or, to continue our analogy, which steps contributed the most to the building of the house from the foundations up.
The measurement paradigm is moving toward a new framework: measurement triangulation.
Enter measurement triangulation.
What is marketing measurement triangulation?
Measurement triangulation combines multi-touch attribution (MTA), incrementality testing and marketing mix modeling (MMM) to give you a much more holistic and comprehensive understanding of marketing performance.
By combining a mix of methods, your measurement has room to include other attribution data, like that which comes from your ad platforms (think impressions, views and engagement) and even post-purchase surveys.
It allows you to combine various types of data and better understand the effects on your marketing, be it above-the-line (ATL) or below-the-line (BTL) advertising. You can even include external factors like inflation, the unemployment rate, seasonality and changing consumer behavior.
This approach allows you to combine multiple tools, considering their strengths, limitations and individual roles, and feed them all into an intermediary platform. It gives you a better version of the truth so you have a more reliable base from which to interrogate your data with your experience and judgment.
The benefits of a holistic approach to measurement
Because most marketers use similar data sources and tools, it’s difficult to stand out based solely on what technology you use. Instead, the real opportunity for differentiation lies in how you use data.
If you can better analyze and interpret marketing performance data — specifically, through the quality of reporting and the depth of insights you gain — you learn more about your customers and what resonates with them. Then, you can improve your marketing further so it’s more effective.
In other words, success isn’t just about gathering data; it’s about crafting clear, accurate and compelling “data stories” that translate raw numbers into meaningful insights for smarter decision-making.
For example, MMM is ideal for offline marketing integration but it often lacks the operational campaign optimization you need. It also captures high-level digital trends like total impressions or spend for digital channels, meaning it’s not limited to offline tracking. But by adding in MTA, you can refine your MMM insights for better nuance in your campaign analysis.
Incrementality testing then gives you a clear, causal understanding of whether a specific marketing activity drove a measurable change in outcomes, such as sales or conversions — in short, there’s no more guesswork.
As these three measurement approaches work together, they inform and improve each other.
Triangulation balances the strengths and weaknesses of each method.
As you can see, each of these three pillars mitigates the other's weaknesses and improves the clarity of the whole picture. That’s why triangulation lets you create a more reliable data narrative.
What does triangulation need to work?
For triangulation to really work, you need to have smooth data integration with an intermediary platform. The goal is to make sure your data is accurate and high-quality, flowing in real time for up-to-date reporting.
Your tool should also pull in extra data, like ad platform attribution or post-purchase survey responses. This helps you make smarter decisions when it comes to budgeting and activating your data. (You’ll see how awork pulled this off in their success story below.)
Finally, you need someone (or a system) who can interpret all this data and paint the bigger picture for you with accurate reporting that can easily be shared with the platforms you already love, like Power BI, Tableau and Google Looker Studio. But before we get too deep into the considerations, let’s break down how measurement triangulation works.
How measurement triangulation works — with examples
Imagine you’re putting together a large mural from three different paint-by-numbers kits. Each kit — MMM, MTA and incrementality testing — offers a unique view of how well your marketing efforts are working, but each one paints only part of the picture.
In the MMM kit, there’s a large section labeled “Google search campaigns.” It tells you that you spent $3,000 on these campaigns and generated 600 sales. This high-level view shows the big-picture impact of Google ads but doesn’t break down the specifics of individual campaigns.
The MTA kit zooms in on smaller, detailed areas like “Google/back-to-school,” “Google/spring promo” and “Google/summer sale.” Each area represents a specific campaign.
When combined, these smaller sections reveal that 550 sales were made. This discrepancy happens because MTA might miss some sales due to tracking limitations or undervalue certain interactions, especially from offline or indirect channels.
Now, the incrementality testing kit comes in, adding another layer. It allows you to test if these Google campaigns truly drove those sales or if some would have happened anyway.
For example, by running a test on the “Google/back-to-school” campaign, you discover that it generated an incremental lift of 200 additional sales compared to a similar group who didn’t see the campaign. This helps you see which parts of the mural made a difference versus those that had no or minimal impact.
To complete the mural and get the full picture, you need to align all three kits — linking the MMM overview with MTA’s detailed touchpoints and validating the actual impact with incrementality testing. By fitting these pieces together, you get a clear, holistic understanding of your marketing effectiveness, allowing you to make smarter, data-informed decisions.
The features of each measurement pillar
Each corner with its individual powers combines to become triangulation. So, what does each of these triangulation methods bring to the table?
Data-driven MTA features
Some of the critical features of MTA include:
- Integrating tracking data to analyze user journeys
- Using machine learning to compare touchpoints, helping to see which led to conversions and which didn’t
- Providing detailed insights on specific sequences at the user or order level
- Including campaign, ad, keyword and Google Click Identifier (GCLID)-level analysis
- Exporting raw data, like customer journeys, for further analysis
- Offering reverse extract, transform and load (ETL) functions to push attribution data back into ad platforms, such as Google Ads, on a GCLID level
Incrementality testing features
Conducting experimentation is not always straightforward. For example, running tests at scale across channels and markets can be costly and logistically complex.
Incrementality testing features can help with this by:
- Recommending tests automatically, making it easier to decide what to test and when
- Designing tests based on regions, duration or spend combinations
- Analyzing test results to provide insights on what’s working and what could be improved
Triangulation features
Triangulation supports your data-informed marketing efforts by:
- Combining MTA and test results to calibrate the MMM
- Using regular tests to validate MMM and MTA attributions to make sure you’re seeing the most accurate results
- Breaking down incremental revenue and conversions to the campaign level or even more detailed levels to give you nuanced insights you can’t get any other way
- Allowing flexibility to integrate other attribution methods — think in-platform attribution and/or post-purchase surveys.
When it comes to your marketing intelligence, triangulation covers all your bases. It provides the nuance you need to not only give you a reliable view of the past but also help you make data-informed decisions about the future.
Considerations when creating your triangulation system
When it comes to setting up triangulation for the first time, there are some important considerations to keep in mind. First, for a system that combines the observational methods of MMM and MTA to get a full picture of both online and offline media, you need a framework that lets you calibrate your model regularly.
Automation is key here.
You know well enough that anything that requires more manual effort isn’t helping. What we’re aiming for here is seamless data calibration. Anything else will just increase the chance of things going wrong, ultimately making it frustrating to use.
Ideally, this is a system that should run daily, without needing your constant intervention. But, how?
When it comes to triangulation system design, solid data integration is both the foundation and the biggest challenge.
“Real-time” reporting through data integration can take some time to set up correctly. Data integration can be slow, require custom API setups and sometimes involve a manual refresh process depending on the platforms involved.
You also need to align both aggregate data (like overall campaign performance) and user-level data (individual user actions) to truly measure your marketing impact.
By collecting both data types simultaneously — using tools like tagging or unified dashboards — you can avoid the inconsistencies that can skew your model’s accuracy. However, to rely on this data, you have to be able to rely on its accuracy.
You can do this by connecting your ad platforms via API to an aggregated data collection system like Funnel. Then, add server-side tracking for better MTA insights or connect your existing tracking systems like GA4, Adobe Analytics or Snowplow so that all your data feeds into the same place.
Next, make sure you're accurately matching costs by keeping your media spend and impression data well-organized across platforms. This will allow your MMM and MTA models to work together more smoothly.
When you successfully link media contributions from MMM (using cost or impression data) with MTA, you create a more integrated, effective measurement approach, giving you a clear picture of what’s driving results.
The challenge, though, is that all this relies on perfect data integration. If your data is clean and aligned, your intermediary platform can handle the rest, seamlessly bringing these elements together so you can focus on optimizing, not troubleshooting.
2 measurement triangulation success stories
To see measurement triangulation in action, let’s look at two businesses that have embraced new ways of data-gathering and interpretation:
Project management development company awork optimizes its spend
The team at awork wanted to move beyond last-click attribution to better understand the full impact of their marketing efforts. Their challenge was tracking multiple data sources and managing the complexity of cross-channel attribution.
With Funnel, awork was able to easily integrate data from various marketing platforms, giving them a comprehensive view of their customer journey. This allowed them to see the true contribution of each marketing channel, not just the last touchpoint.
The results?
They were able to reallocate 30% of their marketing budget to high-performing channels.
With improved attribution, they gained the confidence to significantly increase their overall media spend.
This smarter approach to budget allocation also allowed them to lower customer acquisition costs across their campaigns, making sure that they got more value out of every marketing dollar spent.
As a result, awork improved their attribution model, gaining deeper insights into their campaigns and making more informed decisions. This helped them optimize their marketing spend and understand which channels were driving real growth.
Deuba discovered that social media ads were 80% under-attributed
Deuba, a leading online retailer, was relying on last-click attribution, which made it hard to fully understand the impact of their marketing channels — especially for social and display ads that don’t always get clicks but are still valuable.
By partnering with Funnel, they adopted AI-powered multi-touch attribution and marketing mix modeling, which gave them a much clearer view of how all their channels worked together. This new approach revealed that their social media ads were performing 80% better than they’d previously thought.
Armed with these insights, the team at Deuba was able to optimize their Google Ads strategies, improving both cost per acquisition and return on investment. With Funnel as their single source of truth, they now make smarter, more data-driven decisions, leading to better results and growth across their campaigns
But don’t just take our word for it. Here’s what Mark Prediger, Head of Online Shops and Marketing at Deuba, had to say about the benefits of a more holistic marketing measurement approach:
“Transitioning from a last-click attribution model to a holistic measurement approach, which now includes display and social ad impressions, has given us the power to accurately measure the real ROI of every marketing move. Armed with this newfound clarity, we're making informed decisions and driving targeted growth.”
-Mark Prediger, Head of Online Shops and Marketing at Deuba
Funnel: data coverage that tells the whole story
Last-click, multi-touch attribution, MMM or incrementality testing alone, just don’t cut it anymore when it comes to truly measuring your marketing’s effectiveness. The way we measure success is evolving, and it’s time for a more holistic approach that goes beyond traditional metrics.
Stop stressing over the numbers and start focusing on creating ads and messaging that people love. Explore triangulation and see how much further you can take your marketing. Download your free copy of the Triangulation Tango ebook and learn how to make your data dance for you.