Building a Test-and-Learn Strategy for Omnichannel Marketing
Marketing has become more complex. People move between email, websites, ads, and apps quickly and often. They might research a product on their phone, compare options on a laptop, and buy in-store, or skip the store entirely and purchase online after seeing an ad.
In response, many marketing teams are trying to keep up by using personalization to make messages more relevant. The thinking is that tailored messages will cut through the noise and lead to better results. But how do you know if the personalization is working?
That’s where testing comes in. A test-and-learn strategy helps you figure out which messages, formats, and combinations actually improve outcomes. Without this, it’s too easy to confuse activity for progress.
This article looks at how to build a simple, practical testing strategy that works across different marketing channels, using personalization as a central example.
Start with Simple Tests: Improve One Step at a Time
Small tests are a good starting point. These tests focus on one thing at a time—maybe a headline, an image, or a specific offer. They help answer clear questions:
● Will a personalized subject line increase open rates?
● Does offering 10% off to past buyers improve conversions?
● Does changing the CTA from "Learn More" to "Get Your Deal" make a difference?
These tests are usually easy to set up and run. They’re especially useful for channel teams working in silos—like the email or paid media team—because the scope is narrow. They help teams move quickly, adjust creative, and make decisions without waiting for big studies.
The downside? They don’t tell you how different efforts interact. A customer may see your ad, open your email, and click on a personalized homepage—all in the same journey. Testing these in isolation doesn’t show the full picture.
Look at the Whole Experience: See the Bigger Picture
Holistic testing takes a step back. Instead of looking at one piece, it asks: What’s the impact when all the personalized elements are combined?
To find out, you compare two groups:
● One sees the full version: personalized ads, tailored emails, and a custom website experience.
● The other sees a more generic version: broad targeting, standard content, and fewer custom touches.
By comparing results, you learn whether your personalization strategy is helping or just adding complexity.
These tests are larger and take more coordination. You need clear definitions of who is in each group, and you need to make sure people stay in their assigned experience. But they answer an important question: is this approach worth continuing and scaling?
Holistic testing is particularly useful before launching a major investment in personalization. It helps teams go beyond small wins and understand what works at the program level.
What It Takes to Run Holistic Tests Well
Because holistic tests span many parts of the marketing experience, they come with some technical and operational needs:
● Clean audience segmentation – To avoid overlap, you need a way to clearly separate test and control groups. This could be based on geography, customer ID, or account-level rules.
● Consistent identifiers – Tracking people across channels requires persistent IDs, like email addresses, login IDs, or device signals. With the decline of third-party cookies, this requires more planning and the use of first-party data systems.
● Cross-channel orchestration – Ads, emails, and website experiences must line up. That means tools like customer data platforms (CDPs) or campaign orchestration software become essential.
● Reliable tracking setup – You’ll need a way to track conversions, revenue, and behavior consistently across channels. This may include UTM tracking, event-level analytics, server-side tracking, or integrations with platforms like Google Analytics or Adobe.
● Testing governance – Without central oversight, different teams may run overlapping tests that confuse results. A shared calendar or testing center of excellence can prevent this.
When these pieces are in place, holistic tests can produce trustworthy insights. Without them, the results can be noisy.
Other Ways to Measure Incremental Impact
While A/B and holistic tests are effective, there are other methods marketers use to measure the real impact of personalization, especially when experiments aren't possible.
● Matched Market Testing – Compares similar regions or customer groups where one receives personalization and the other does not. This is helpful when user-level tracking is difficult.
● Incrementality Measurement – Uses platform tools like Meta Conversion Lift or Google Geo Experiments to isolate the causal impact of campaigns or experiences.
● Media Mix Modeling (MMM) – Takes a statistical approach using historical data to estimate the contribution of each marketing channel to overall performance. Great for high-level impact analysis, especially when privacy limits direct tracking.
● Multi-Touch Attribution (MTA) – Assigns fractional credit to each touchpoint across a customer journey. While not causal, it helps understand how personalization interacts with other channels.
● Uplift Modeling – Uses machine learning to predict which users are most likely to respond to personalization. Helps target more effectively and avoid wasted effort.
Each method has strengths and trade-offs. For most organizations, combining 2–3 approaches (e.g., A/B testing + MMM + attribution) gives the clearest picture of what’s really working.
Use a Layered Testing Approach
A strong test-and-learn plan includes a mix of small and large tests. Each layer serves a purpose:
● Small tests help improve details like messaging or visuals.
● Channel tests help improve how you work within email, ads, or your website.
● Holistic tests help measure the impact of all parts working together.
Let’s take personalization as an example:
● A small test might check if a personalized product carousel on the homepage increases clicks.
● A channel test might compare performance between personalized vs. non-personalized emails.
● A holistic test would look at the whole journey—did the combination of personalized media, email, and website content lead to more bookings?
When all three types of tests are used together, teams get a clearer picture. They can learn what works at each level and how those layers connect.
What Good Testing Looks Like
Teams that make the most of testing tend to have a few habits in common:
● They plan their tests in advance, so different teams aren’t testing the same audience at the same time.
● They use shared definitions for audiences, goals, and outcomes.
● They focus on business results—not just clicks, but purchases, signups, or repeat visits.
● They document what they learn, so future tests build on what came before.
● They make testing part of everyday work, not just something to do when there’s time.
A strong testing culture doesn’t require fancy tools. It requires discipline, collaboration, and a clear idea of what questions you're trying to answer.
Mistakes to Avoid
Even with the best intentions, it’s easy to fall into some common traps:
● Running lots of disconnected tests that don’t add up to real insight.
● Forgetting that people use multiple devices and channels.
● Giving credit to the last click when many things contributed.
● Measuring only easy metrics (like open rates) instead of important ones (like revenue).
Testing can be powerful, but only if you use the results to guide decisions.
Final Thoughts
Testing helps you figure out what’s working. That’s always helpful, but it’s especially important when you’re personalizing messages across many different channels.
Start with simple, focused tests. As you learn more, move toward testing full experiences. Over time, you’ll build a system that helps you understand, improve, and scale what works.
You don’t need to test everything. But you do need to test the right things—and that starts with a plan. When done well, a test-and-learn approach turns good guesses into confident decisions.
July 2, 2025
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