Modern e-commerce is a paradox: We have more data than ever, but brands have never felt less certain about where to spend the next dollar.
Dashboards, platforms, and vendors all promise precision: This channel drove that revenue, this campaign has a 4.2x ROAS, this creator drove $X in revenue, etc.
But the people who actually own the budget know the uncomfortable truth: The numbers add up to 400% of the actual revenue, the models disagree, and the story changes depending on who built the report.
The answer isn’t to throw it all out, or to chase the impossible dream of flawless attribution.
It’s much more simple: Build a way of measuring that’s honest about what we don’t know but still robust enough to make big calls.
Signs of Attribution Chaos
First, let’s talk about what this looks like day-to-day. If any of it looks familiar, that’s your cue…
Channel whiplash
A brand sees Meta ROAS fall off a cliff in‑platform. They panic, slash spend, and celebrate “protecting efficiency.” For a moment, the dashboard looks better.
But then overall revenue drops, followed by organic and branded search, email, etc. The attribution model said Meta wasn’t driving value; the business reality says otherwise.
Reality: The closer a channel is to the conversion event, the better it tends to look in attribution tools — whether or not it’s actually creating demand.
Attribution tug‑of‑war & paralysis
The digital marketing lead shows a dashboard where paid social is printing money. The brand lead counters with a dashboard showing direct and branded search doing the lifting.
Or you look at analytics and see a huge chunk of revenue into “direct” or “unassigned.” Everyone has their own idea of how to interpret that, and there’s no objectively right answer.
Reality: With conflicting stories in the data, brands often just default back to intuition.
The result: Short‑termism and channel addiction
Because last‑click and in‑platform metrics favor easy‑to‑track conversions, teams drift into over‑investing in retargeting and branded search, and under‑investing in content, creators, and brand campaigns.
The cycle looks like this:
Cut upper‑funnel because it doesn’t “pencil out,” watch overall demand soften, then spend more on bottom‑funnel tactics to squeeze what’s left.
Inevitably CAC rises, and everyone blames the market… not the fact that they turned off their own demand engine.
Three Ways Out
You won’t fix this by hunting for a tool that solves marketing attribution. You fix it by changing how you think about measurement.
1. Use a measurement portfolio, not a single source of truth
Stop looking for the one true dashboard. It doesn’t exist.
Instead, use a portfolio of imperfect lenses:
- Platform data as directional, not gospel. If Meta says your CPA is spiking, that’s a signal to test and investigate, not an automatic kill switch.
- Blended business metrics as anchors: New and returning customer orders, MER, blended CAC, contribution margin, payback period, LTV/CAC by cohort. These are hard to game and reflect reality at the business level and aligned with the P&L.
- Simple mix and incrementality tests: On/off or heavy‑up tests by channel, basic geo holdout tests, brand vs. direct‑response splits at constant spend.
None of these are perfect alone. But when multiple lenses show you a similar story, it’s probably valid.
2. Move from conversion metrics to decision metrics
Most fights happen because people try to answer business questions with campaign‑level metrics, e.g., green-lighting a new SKU because they saw some juicy ROAS last week.
Instead, zoom out and start with the real decisions:
- How much can we profitably spend this month and quarter?
- What’s happening to CAC, MER, and payback as we change channel mix?
- Is new customer acquisition getting better or worse over time?
Then use channel‑level metrics to help answer those questions. Sure, ROAS is one metric. But also look at the share of new vs. returning customers, the impact on branded search and direct traffic, blended CAC and any other data you need for an informed decision.
For brand and creator work, look at search volume, site traffic, list growth, and the baseline of your performance campaigns.
Then you get past the dogfights over “Should this ad get credit for the sale?” and get to “Did this investment make the business healthier?”
3. Make experimentation part of planning
Most teams say they believe in testing; in practice, experiments are the first thing cut.
Don’t just jump to that. Instead:
- Set aside a fixed percentage of marketing spend for structured tests and protect it.
- Define each test up front: what you’re testing, how you’ll judge success, and the time window.
- Keep tests simple and repeatable: turn a channel on/off, creative concept vs. control, brand‑heavy vs. DR‑heavy at constant spend.
You’ll never have a “perfect” answer, but that’s ok. The point is to continuously learn, so every quarter you get more confident about where the next dollar should go.
The bottom line
If you wait for a clean, universally trusted attribution tool before making bold decisions, you’ll be waiting forever. The platforms will keep changing; the data will never be perfect.
The winning brands aren’t the ones with the fanciest dashboards. They’re the ones who accept uncertainty, use multiple imperfect views of reality, anchor on business outcomes, and run disciplined experiments to keep getting smarter over time.
Matt Raminick is the founder & CEO of Sunnyside, a profitability-first growth partner for lifestyle brands, connecting creative strategy, paid media, retention marketing, and financial planning to map marketing directly to your P&L. Founded in 2020, Sunnyside partners with brands like Brixton, Municipal, Nixon, Beek, Xcel Wetsuits, SALT. Optics, and Jetty. Prior to founding Sunnyside, Matt held senior digital marketing roles at Quiksilver, Volcom, and Pacsun. He can be reached on LinkedIn and at matt@sunnysidecalifornia.com
