Course material · Lesson 04 · Marketing's job on the P&L
What you save today. What you lose over 24 months.
The CFO looks at the marketing line during a downturn and sees a large, visible number that can be cut immediately. What the CFO does not see is the trajectory that starts the moment the cut lands: CAC rises after three to six months, direct traffic flattens, price promotions become necessary, and by month 12 to 18 market share is slipping. This tool models that trajectory so you can put a number to it in the board conversation.
Model
Your baseline
Enter your current monthly numbers. Defaults are a mid-scale D2C business.
Cumulative EBIT impact — 36 months
Each line shows the running P&L delta versus continuing to invest. Above zero = the cut is net-positive. Below zero = the cut has cost you more than it saved.
ScenariosBaseline (no cut)Cut brand 30%Cut brand 50%Cut brand 100%
1. CAC drift
Awareness campaigns are what warms the audience. When you cut them, click-through rates fall, conversion rates fall, CPMs rise. CAC creeps up over 6–12 months.
2. Direct / organic traffic
Buyers who typed your brand name into a browser are the residue of past brand investment. That traffic decays without new inputs — Binet & Field's "leaky bucket" at the demand-generation layer.
3. Price promotion depth needed
As mental availability weakens, you need larger promotions to hit the same volume. This eats gross margin permanently — and trains buyers to wait for the discount.
4. Market-share change
The lag indicator. By the time share slips, the cut is 12–18 months old and the CFO who signed off has moved on. The new CMO inherits the deficit.
At month 24 — the CFO-relevant summary
Pick a scenario to see the two-year outcome in the numbers a CFO uses.
The empirical foundation · Dale W. Harrison, BAM
Why this tool exists, and where the decay curves come from.
The interactive simulator above compresses a much more rigorous piece of quantitative marketing science into four exponential-approach curves. The underlying phenomenon — that brand memory builds slowly toward a steady-state equilibrium, decays with a specific memory half-life the moment marketing stops, and rebuilds when marketing resumes — is Dale W. Harrison's Brand Awareness Model (BAM). Harrison models it as a dynamic stochastic partial-differential equation in vector-calculus state-space notation, then runs Monte-Carlo simulations against 100,000 customers across five brands to observe the trajectory. It is the reason a stationary model like NBD-Dirichlet cannot answer "what happens when I cut brand spend" — you need the dynamic model to see it.
Months 0–24: brand memory builds toward a steady-state equilibrium closely tied to relative market share. Brand A (50% share) plateaus at ~55% memory-at-purchase; Brand D (5% share) plateaus at ~28%.
Month 24: all four brands pause marketing. Memory decays at a category-specific half-life (here: one quarter).
Months 24–36: the four brands converge downward — the market-share advantage compresses because the memory that separated them is what marketing was refreshing.
Month 36: marketing resumes. Memory rebuilds toward the previous equilibrium — but the interim revenue lost during the decay window is unrecoverable.
Four factors that shape the equilibrium
1. Relative market share — determines the free cash available to invest in brand and therefore the achievable equilibrium.
2. Memory half-life — longer for high-consideration B2B categories; shorter for low-involvement FMCG.
3. Purchase cycle length — the longer between buying occasions, the more forgetting happens between them.
4. Reach frequency — how often you refresh each buyer's memory. Below the refresh rate needed for your memory half-life, you cannot hold the equilibrium.
Where the real market moves the steady state.
The BAM curves assume a category that sits still while brand budgets do their work. Real categories do not sit still. Four dynamics move the equilibrium underneath you, quarter by quarter — and any of them can be the reason your steady-state number is drifting even when your spend has not.
Competitive share of voice, not absolute spend.
Your equilibrium is set by what you invest relative to your competitors, not by what you invest in absolute terms. When a new player enters and spends aggressively, everyone's steady state moves down. When a competitor cuts brand spend, your effective share of voice rises without you changing anything, and your equilibrium can climb without a euro of new investment. This is the mechanism behind the "hold spend during downturns" argument — the maths does the work.
Media price cycles.
In recessions, advertising demand falls and media prices fall with it. The same brand budget buys more reach, refreshes more buyers per month, and holds a higher equilibrium. In booms the reverse — CPMs rise and your budget refreshes fewer buyers, so the same spend now supports a lower steady state. Your P&L line looks the same. Your mental availability quietly drifts.
Attention scarcity is shortening the half-life.
Harrison's illustrative example uses a one-quarter half-life. In categories where attention is fragmenting fastest — anything competing with algorithmic feeds and short-form video — the effective half-life has shortened over the last decade. The consequence is that the same reach frequency now supports a lower steady state than it did five years ago. Categories that felt "brand-heavy enough" in 2018 are quietly undersupported today.
Category growth vs. stationarity.
BAM assumes a stationary category. In a growing category, net-new first-time buyers are entering and forming their initial memory associations at the same time; the in-market pool is not 5% but 25–35% (Harrison — see Lesson 2). Performance marketing is unusually efficient during that window, and the equilibrium your brand is building toward keeps rising as the category expands. In a shrinking category the reverse. Read your growth rate against the category, not against your own history.
The maths of BAM tells you the shape of the response. Which shape you actually see is the composition of BAM with these live market conditions. This is why the answer to "how much do we need to spend on brand" is never a fixed number — and why the CMO who is not tracking these four inputs alongside their own spend is planning against a variable they cannot see.