Looking for an alternative to ROAS? ROAS misses margin, retention, and incrementality. Here are smarter metrics that show true impact.
It’s time to rethink what ROI really means.
The problem with ROAS is not math. It’s the story you think it’s telling.
ROAS looks so clean on a dashboard. Spend a dollar, make three, feel alive again. It’s the metric equivalent of drinking a green juice and assuming you now have a personality.
Here’s the issue: ROAS is a ratio built on attributed revenue. “Attributed” is doing an Olympic amount of work in that sentence. Most teams talk about ROAS like it’s a direct line from ad to cash register, but it’s really a line from ad platform reporting to your hopes and dreams. ROAS is typically calculated as attributed revenue divided by ad spend, which is fine as a definition, but it bakes in whatever attribution rules you are using (and whatever your platform would like to take credit for).
So when I say “ROAS is dead,” I don’t mean you should never look at it again. I mean this: ROAS as the main decision-maker is done. It cannot carry the weight we keep putting on it, especially now that measurement is getting noisier and privacy-first changes keep shrinking the pool of trackable signals.
ROAS fails in three predictable ways (and it’s not your fault)
1) ROAS confuses “got credit” with “caused the outcome.”
Attribution is not causation. If your ad platform says a campaign “drove” revenue, what it often means is “a person who saw or clicked an ad later bought something, and we are calling that a win.”
The part ROAS can’t answer is the only part your CFO actually cares about: Would this sale have happened anyway? That’s incrementality, and it’s the reason two campaigns can have the same ROAS while one is genuinely growing the business and the other is just taking credit for demand you already created.
This is why you’ll see smart teams talk about incremental ROAS (iROAS), where the numerator is incremental revenue, not just revenue that happened to be attributed. Google describes incrementality testing and iROAS as a way to understand the additional value created by advertising, not just what got counted.
2) ROAS rewards the bottom of the funnel and punishes everything else
ROAS loves a “ready-to-buy” audience. It loves branded search. It loves retargeting. It loves any situation where you show up at the end of a customer journey and then take a victory lap like you personally invented shopping.
But lots of the work that makes marketing effective happens earlier, messier, and more indirectly. Brand, creative, social proof, pricing, product, website UX, and yes, email, all shape demand in ways ROAS struggles to see.
Marketing mix models (MMM) exist largely because modern marketing is a group project, and the group chat is chaotic. MMM takes an aggregated view, can account for interactions between channels, and can incorporate non-marketing factors like seasonality, competition, and economic shifts.
If ROAS is a close-up selfie, MMM is the wide-angle shot where you can finally see the background mess you’ve been pretending isn’t there.
3) ROAS gets shakier as privacy and signal loss increase
The industry has been living through years of signal loss and privacy-driven change that affects addressability and measurement. IAB’s State of Data report explicitly frames these challenges as permanent and describes how organizations are adapting.
And on the mobile side, Apple’s iOS privacy changes (including ATT and IDFA limitations) have materially affected measurement and attribution in the ad ecosystem.
When the inputs are wobblier, a single output metric like ROAS becomes a dangerously confident narrator.
The sneaky way ROAS messes with your email program
Because I’m me, I’m going to bring this back to email.
When you optimize paid spend to maximize ROAS, you tend to buy traffic that converts fast. That sounds great until you realize you may be feeding your email list a steady diet of people who only show up for discounts, bounce quickly, and go dormant the moment you stop bribing them.
ROAS rarely tells you:
Whether those customers become subscribers who actually engage.
Whether they buy again without paid support.
Whether they generate support tickets that cost more than their first order margin.
Whether your deliverability suffers because your list quality quietly dropped.
Paid media can be incredible for list growth, but list growth without list health is just a bigger bill from your email service provider. Congratulations on the new expense.
So if you want a real alternative to ROAS, it needs to measure outcomes that include email’s real job: turning first purchases into repeat behaviour.
Smarter metrics that actually reflect impact
This is where I get very practical, without turning this into a “click here, set up this dashboard” snooze-fest.
The goal is a measurement stack, not a single magic number. Different metrics answer different questions, and the biggest ROAS trap is asking one metric to answer all of them.
Metric 1: Incrementality (iROAS or incremental profit)
If you only adopt one upgrade, make it this: separate “attributed” from “incremental.”
Incrementality testing asks a causal question: what changes when ads run versus when they don’t. Google explicitly positions incrementality testing as a way to calculate incremental ROAS using incremental revenue divided by spend.
Why this is a better decision tool than ROAS: it tells you whether a channel is creating lift, not just collecting credit.
Email tie-in: Incrementality is also the best friend of your lifecycle brain. If paid is driving “new” customers who would have purchased anyway, your email program is the one stuck nurturing people who were already coming. That’s not a fair fight.
Metric 2: Contribution margin return (or profit-based ROAS)
Revenue is not profit. This is where ROAS gets people in trouble, because it can make a low-margin product look like a hero.
A profit-based return (contribution margin divided by spend) forces you to account for discounts, COGS, shipping, returns, and payment fees. It is less glamorous than ROAS, which is exactly why it works.
Email tie-in: profit-based thinking stops the endless cycle of “acquire with a discount, try to recover margin in email.” That approach is basically a rom-com where everyone is crying by minute 40.
Metric 3: CAC payback period
ROAS tells you a snapshot. Payback tells you time.
CAC payback period answers: How long until we earn back the acquisition cost from gross profit? This is especially helpful for subscription, membership, or any business where the first purchase is not the whole story.
Email tie-in: Email often does the heavy lifting inside the payback window. If your paid team is high-fiving a day-zero ROAS while payback stretches into “sometime next season,” your lifecycle programme is quietly becoming the financial plan.
Metric 4: LTV:CAC, but used like an adult
Yes, LTV:CAC is a classic. No, you cannot just pick a 12-month LTV number from vibes.
If you use it, treat it as a directional indicator, grounded in cohorts. The point is not the exact decimal. The point is whether your acquisition engine produces customers who stick.
Email tie-in: cohorts are where email finally gets credit for being more than a “blast channel.” If cohorts acquired from Channel A retain and reorder more than Channel B, your email strategy (and your product experience) is part of that outcome.
Metric 5: Blended efficiency (MER, blended ROAS, or revenue per total marketing cost)
This one is popular when attribution is messy because it does not pretend you can perfectly assign credit. Blended efficiency metrics look at total revenue (or profit) against total marketing spend across channels.
Is it perfect? No. Is it sometimes the most honest number in the room? Absolutely.
This is also why MMM has surged in interest. It’s designed to measure marketing’s impact on business KPIs using an aggregated view that does not rely on individual-level data, and it can reflect how channels amplify each other.
Email tie-in: blended metrics naturally include email’s impact because they’re not limited to what the paid platform can track.
Metric 6: Incremental lift by channel using MMM and experiments
If your business is multi-channel, if you run promotions, if seasonality is real (it is), or if you have offline components, you eventually hit the ceiling of platform reporting.
MMM helps answer cross-channel questions and can incorporate external factors that affect sales performance.
The smartest teams combine approaches: use experiments for causal proof in specific areas, and MMM for a holistic view. That combo keeps you from steering the entire ship using one leaky compass.
A simple decision framework (so you pick the right “alternative to ROAS”)
When someone asks, “What should we measure instead of ROAS?” I think the better question is: What decision are you trying to make?
If you are trying to decide whether to scale a channel, you want incrementality or profit-based return, because scaling without lift is just buying yourself a bigger illusion. The industry has been moving toward incrementality as scrutiny on ad spend grows, especially in places like retail media, where ROAS can be particularly misleading.
If you are trying to decide whether you can afford your acquisition strategy, you want CAC payback and LTV:CAC, grounded in cohorts.
If you are trying to align marketing with finance, you want contribution margin return and blended efficiency, so both teams are speaking in the same currency.
If you are trying to understand cross-channel contribution in a privacy-first world, you want MMM plus experiments, because the signal loss problem is not going away.
And if you are trying to keep your email programme healthy, you want acquisition quality metrics baked into the scorecard, not treated as “someone else’s problem.”
The awkward truth: attribution is changing, so ROAS is changing under your feet
Even within Google’s ecosystem, attribution options have been simplified over time, with models being sunset and data-driven approaches being pushed forward.
That means the same campaign can show different ROAS depending on how credit is assigned, how conversions are defined, and what data is available. This is not a reason to panic. It’s a reason to stop treating ROAS like a law of physics.
ROAS is not the truth. ROAS is reporting.
What I would actually put on a modern marketing scorecard
If you want a cheat code (ethical, non-cringe version), it’s this: pair one causal metric, one profit metric, and one customer-quality metric.
Your causal metric keeps you honest about lift (incrementality).
Your profit metric keeps you honest about economics (contribution margin return).
Your customer-quality metric keeps you honest about the future (cohort retention, repeat rate, or payback).
Then, and only then, I’d keep ROAS around as a diagnostic. Not as the boss.
Because when ROAS is the boss, the boss makes everyone do weird stuff. Like spending more on retargeting people who were literally in your checkout already. That’s not “performance marketing.” That’s stalking with spreadsheets.
Key takeaways
ROAS is a useful ratio, but it reflects attributed revenue, not guaranteed causal impact, and attribution is increasingly constrained by privacy and signal loss.
If you want a credible alternative to ROAS, prioritize incrementality (iROAS), profit-based returns, payback, and cohort-based customer value so you can make budget decisions that hold up outside the ad platform.
Email performance improves when acquisition is measured on customer quality, not just instant conversion, because lifecycle outcomes are where the business actually compounds.
If this made you want to delete at least one dashboard tab (in a healthy, cathartic way), you’ll probably like The Click Brief, my weekly newsletter on email, measurement, and marketing psychology without the nonsense. Subscribe to The Click Brief, or come say hi on LinkedIn or Instagram.