The conversation usually starts the same way. Margins are lagging. The board wants answers. The team has already done the obvious things: cut a vendor contract, paused some ad spend, renegotiated rates with the 3PL. And then comes the line that shows up in founder conversations more often than you'd think:
"We made the obvious cuts, but we didn't know what else to do."
Here's what that moment usually means: the brand has run out of cost-cutting ideas, but it hasn't run out of EBITDA opportunity. The two are not the same thing.
The brands that make the biggest EBITDA improvements — 18, 20 percentage points in under a year — almost never do it by cutting more aggressively. They do it by seeing more clearly. They discover that a segment of their customers is loss-making. That one channel is dragging their blended margin. That the timing of a capital decision is worth $4 million. The lever was there the whole time. They just couldn't see it.
EBITDA improvement for consumer brands isn't primarily a cost problem. It's an information problem.
The EBITDA problem hiding in your customer mix
Not all revenue is created equal — but the standard P&L won't tell you that. It shows top-line growth. It shows blended COGS. What it hides is whether the customers generating that revenue are actually profitable over time.
Mad Rabbit found out the hard way. The brand had strong DTC revenue and healthy-looking top-line numbers. But when Oliver Zak's team ran cohort-level analysis through Drivepoint, a different picture emerged: 20% of their DTC customers were loss-making. These were buyers who purchased a single product on sale, never came back, and never generated a second dollar of revenue. The brand was spending real acquisition dollars to acquire customers who would never pay back that investment.
Once the data made that visible, the decision was obvious: stop acquiring those customers. Shift new DTC acquisition to a bundle-only strategy that raised the economics of the first transaction and improved retention odds from day one.
The result: +20% EBITDA improvement in months. 95% reduction in planning cycles.
"Drivepoint gives me very strong conviction in the decisions I need to make because the numbers are clear as day, and that makes the decisions easier." — Oliver Zak, Co-Founder & CEO, Mad Rabbit
The EBITDA lever was already there. The cohort data just made it findable.
The AOV lever: how an 18% shift changed everything
Sometimes the lever isn't identifying and cutting unprofitable customers. It's understanding what makes one customer dramatically more valuable than another — and concentrating every marketing dollar behind that version of the customer.
Geologie was unprofitable. The brand had built a wide product mix with varied price points, and the blended unit economics weren't working. The team knew something had to change, but the standard reports didn't show them where to focus.
Scenario modeling in Drivepoint surfaced the answer: if they could increase first-purchase AOV by 18%, the EBITDA math flipped. The brand would move from negative margin to over 9% EBIT margin — not through cost reduction, but through a shift in which products and bundles they concentrated their marketing on.
That single scenario changed everything about how they allocated their next marketing dollar.
The result: +18% EBITDA margin improvement year over year.
"Modeling everything out in Drivepoint showed us exactly how much impact increasing AOV could have on our business. It gave us the confidence we needed to focus and execute instead of spreading our efforts too thin." — Nick Allen, Co-Founder & CEO, Geologie
The timing lever: when "should we invest?" is the wrong question
Not every EBITDA improvement comes from margin. Sometimes it comes from getting the timing of a capital decision right — and quantifying what waiting actually costs.
Oats Overnight knew a new production facility would improve capacity and unit economics. The question wasn't whether to invest — it was when. Most brands in that position make the decision based on gut feel, cash position, or whatever the CFO can model in a spreadsheet over a weekend.
Drivepoint's financial models showed something different: Q4 demand was going to surge, and waiting even one additional quarter would mean missing revenue that far outweighed the cost of the capital outlay. The time urgency wasn't conceptual. It was quantified, visible, and defensible to the board.
The decision to accelerate the investment was worth $4M in EBITDA improvement, helped secure a $20M Series A, and resulted in 98% forecast accuracy the following year.
"We knew investing in a new facility would be an improvement conceptually. But it took seeing it in the Drivepoint model with the impact on our P&L to understand the time urgency." — Nina McKinney, CSO, Oats Overnight
This is a question most brands never think to model: not just whether to make a capital investment, but when — and what waiting one quarter costs in real dollars.
The common thread
These three stories look different on the surface. One is about customer cohorts. One is about product economics. One is about the timing of a capital decision.
What they share: the EBITDA improvement was already there. The data revealed it. The decision to act required conviction — and conviction requires a model you trust enough to bet on.
The numbers back this up. The median EBITDA margin for 8-figure consumer brands sits around 7–8%, according to eCommerceFuel's 2025 Trends Report. The $25–50M revenue tier — a sweet spot for operationally mature brands — nets 13.8% on average. The top performers push past 20%. The gap between those tiers is rarely explained by cost structure alone. It's explained by financial visibility and the speed at which brands can act on what they see.
If you're at 7% and trying to get to 13%+, you probably don't need to cut harder. You need to see more clearly.
Three practical starting points
1. Run a cohort analysis. If you don't know which customers are actually profitable over their lifetime, you're flying blind on a major EBITDA driver. Break your DTC customers into cohorts by acquisition channel, first-purchase SKU, and discount depth. You will almost certainly find a segment dragging your blended unit economics — and once you see it, the decision is usually obvious.
2. Model your AOV scenarios. What happens to EBITDA if average first-purchase order value increases by 10%? 15%? 20%? Run this across your channel mix. The answer tells you where to concentrate your next marketing dollar and gives you the conviction to say no to everything else. Drivepoint's scenario modeling is built for exactly this kind of analysis.
3. Ask not just whether to invest — but when. Capital decisions have timing dimensions that most brands never model. A facility expansion, a new product launch, a large PO: the timing of these decisions often matters as much as the decision itself. Quantify the time cost. The math usually surprises you.
The brands that move EBITDA see more
The brands that move EBITDA don't all start in the same place. But they tend to follow the same path: they stop treating profitability as a cost problem and start treating it as an information problem.
When your model shows which 20% of customers are loss-making, you know what to do. When it shows that an 18% AOV increase flips your margin positive, you know where to focus. When it quantifies the time-cost of waiting on a capital decision, you act.
See how brands like Mad Rabbit, Geologie, and Oats Overnight use Drivepoint to build this kind of financial visibility — and the decisions it makes possible — on the Drivepoint customers page.
