Forecasting & planning
Bottoms-up media forecasts and budget scenario models for beauty, ecommerce, and consumer brands — connecting paid media spend to revenue, CAC, and contribution margin.
Forecasts should be a working document, not an annual PowerPoint. Ours are built bottoms-up from channel math — spend, CAC, conversion, and margin assumptions at the channel level, rolled into a P&L view — and rebuilt as reality comes in.
The goal is a shared plan that finance trusts and marketing can execute against without a monthly re-negotiation. When the model, the media plan, and the board deck all run on the same numbers, planning meetings get shorter and decisions get faster.
What we do
- Channel and funnel forecasts. Bottoms-up projections for Meta, Google, TikTok, Amazon, and every channel in the mix — built from channel-level CAC, conversion, and AOV assumptions, with seasonality indexed in, not averaged away.
- Budget scenario modeling. Best, base, and worst cases with the levers clearly labeled — what happens at +20% spend, what breaks if CAC rises 15%, where diminishing returns begin — so trade-offs can be evaluated before budget is committed.
- Aligning finance and marketing plans. One model both teams work from, tied to the metrics the business already runs on: revenue, new customers, contribution margin, and MER. No more reconciling the marketing plan against the finance plan.
Our approach
Channel-level assumptions for spend, CAC, and conversion rolled up into a P&L view.
Best/base/worst cases with the levers clearly labeled so trade-offs are easy to talk about.
Actuals flow in weekly. The forecast updates itself instead of aging out.
Outcomes
- Finance and marketing on the same page, because both teams plan from one model with shared assumptions — not two spreadsheets that disagree by Q2.
- Faster reforecasts when the market shifts, because actuals flow in weekly and scenarios are pre-built; a CAC spike or inventory delay triggers a model update, not a fire drill.
- A clearer view of when to lean in versus hold, grounded in saturation curves and incremental returns by channel — so scaling decisions are made before the opportunity passes, not after.
FAQ
- How is this different from the forecast our finance team already builds?
- Finance forecasts tend to work top-down. A revenue target, an assumed blended CAC, done. Ours build up from channel math: what each platform can actually deliver at each spend level, with seasonality and diminishing returns baked in. The two should meet in the middle, and our model is usually where that conversation happens.
- How often does the forecast get updated?
- Actuals flow in weekly and the model updates as they land. Formal reforecasts happen monthly, or sooner if something material moves (a CAC shift, an inventory delay, a new channel going live). We don't let it get stale.
- Do you model seasonality and events like BFCM?
- Yes. Seasonality is indexed at the channel level from your own history, including Black Friday, Cyber Monday, gifting windows, and category-specific peaks like beauty holiday sets. Q4 plans come with pre-built scenarios for early, on-time, and late demand.
- How do you know where diminishing returns begin?
- A combination of your spend history, saturation curve modeling, and incrementality tests when the stakes justify them. The forecast flags spend levels where a channel starts to bend, so scaling decisions come with the math attached rather than relying on intuition alone.
- Can you build the model around our existing metrics and tools?
- Yes. We build it around what the business already runs on (revenue, contribution margin, MER, new-customer CAC) and plug into whatever you use, whether that's a spreadsheet, Looker Studio, or a warehouse. Nobody has to switch tools.
- Is forecasting a standalone engagement or part of media management?
- Both. Every media management engagement comes with a live forecast, and we also take on standalone planning work. Usually that's annual planning, a fundraise-ready growth model, or a Q4 scenario build.
