Feb 6, 2026
How to measure omnichannel retail without misleading yourself
Sam Faillace
,
VP of Marketing
Connect with Sam
You might be…
…increasing your paid media spend across Meta, Google and TikTok.
But DTC performance still looks flat in your dashboards. Amazon sales begin to rise, and retail revenue improves in a handful of regions. Still, none of it shows up clearly in your attribution tool.
You ask yourself:
Is our marketing working to create demand among buyers in all the places we sell?
This is a familiar moment for omnichannel retail brands. If a purchase doesn’t happen from an ad click, it can happen anywhere: retail, Amazon, marketplaces or on a different device at a different time.
When teams don’t know how to evaluate the efficacy of the ad campaign, they begin debating the purchase channels instead of outcomes.
At Paramark, we regularly see brands miss the central reality of omnichannel growth.
Your marketing is working, but your impact is distributed across various points of purchase that your dashboards are not designed to connect. Then, separate DTC and retail leaders each defend their numbers. And your paid media gets judged using a narrow lens.
For one high-volume beauty brand with global distribution that Paramark worked with, this was the turning point.
After we ran tests, we found TikTok drove meaningful incremental lift, but it showed up primarily in retail locations rather than online.
While their digital spend appeared inefficient for direct website purchases, it drove significant retail sales. Without an omnichannel view, we never would have discovered it.
Why omnichannel impact is hard to see
The omnichannel consumer brands we partner with follow a similar pattern as they scale.
Roughly 60–80% of revenue comes through Amazon or another large retailer (Sephora, Chewy, Whole Foods, etc.), with 20–40% through DTC. Other physical retail enters the mix over time. As distribution expands, measurement complexity increases.
And then there’s the customer reality:
People discover brands in one place and purchase in another. Paid social can drive Amazon sales. But Amazon ads also increase DTC traffic. Offline media lifts both.
In all cases, attribution breaks down because it assumes a direct, one-to-one relationship between touch and conversion.
Teams end up optimizing for what is easiest to see rather than what is actually incremental.
The most common omnichannel allocation mistake
The number one mistake we see omnichannel retail brands make is allocating spend by purchase channel, instead of treating the business as an interconnected system.
This shows up organizationally, too. One team owns DTC. Another owns retail. Each optimizes toward their own metrics and dashboards, and they arrive at different conclusions about what is working.
Conversely, we see other omnichannel brands win because they understand causal spillovers, or when one marketing action drives results somewhere else. That’s what marketing mix modeling (MMM) and controlled experiments are designed to reveal.
A real example: When digital ads drove retail lift
One prestige makeup brand selling both DTC and Sephora wanted to understand how new video ads were contributing to growth.
They ran a three-cell experiment across states:
→ Five states increased TikTok spend.
→ Five states increased YouTube spend.
→ The remaining states served as a control.
When the team evaluated only DTC performance, neither channel appeared to work. However, when they looked at total sales across DTC and retail together, a different pattern emerged.
TikTok drove meaningful incremental lift. But its impact showed up primarily in retail locations rather than online. YouTube did not drive lift in this specific test, but the brand filed away their learnings to retest YouTube with new creative and different hypotheses down the line.
Had the team relied solely on DTC attribution, they would have concluded that the channel failed. Instead, they learned where demand was being created and how customers preferred to buy.
What the data revealed
Here’s a simplified version of how the results were reviewed:
Test Cell | Channel | Metric View | Incremental Lift |
TikTok States | TikTok Ads | Total Sales (DTC + Retail) | +7% |
TikTok States | TikTok Ads | DTC Only | 0% |
YouTube States | YouTube Ads | Total Sales | 0% |
When we do these tests, it isn’t about crediting DTC versus retail. It’s about understanding how channels interact with distribution and customer behavior.
How leading teams measure omnichannel impact
Strong omnichannel teams match measurement to how the business makes money, not how platforms report performance (AKA, grade their own homework).
Here’s a simple workflow to start:
Pick one primary outcome to anchor on, like total sales across Amazon and DTC.
Pull weekly spend and impression data across all major channels, even if it’s not perfectly clean.
Use MMM to understand which channels are driving the most impact.
Pressure-test the biggest bets with geo-based experiments, especially paid social and offline media.
Reallocate budget on a quarterly cadence using your test results and scenario planning, instead of platform dashboards.
This approach gives your whole marketing team a shared source of truth. We recommend avoiding siloed decisions and keeping the budget focused on what’s growing your business, not what looks good or bad in isolation.
One key tip for omnichannel measurement
As retail brands grow, complexity increases fast. Data starts living in too many places, owned by too many teams, and reported in too many ways.
Before you think about a new approach to measurement or a new channel, start with a data reset.
That means unifying DTC, Amazon, retail and media data around a shared set of outcomes.
Once data is centralized, everything gets easier. It sets teams on a path to seeing how channels work together, not in isolation.
The takeaway
The complexity of omnichannel should be an advantage, not a limitation. You have the unique opportunity to capture your customers’ demand whenever they prefer to buy.
Complexity can be measured, as long as you don’t measure each point of purchase in isolation.
When brands step back and look at the full picture – all advertising and purchase channels – teams gain holistic clarity about where demand is created, how channels reinforce one another and what to scale next.
