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Marketing Mix Modelling

Most of your sales would happen anyway.See what your marketing actually drives, and where the next dollar works hardest.

Marketing mix modelling reads your whole history, sales, spend, promotions, price and seasonality, and statistically separates the baseline from the incremental. You see how much each channel truly contributes in contribution margin, and the point where another dollar stops paying back. Causal and privacy-safe, not last-click.

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Causal measurement from the award-winning team behind 100+ brands and operators
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How it reads

Base, incremental, and the next dollar.

See where last month's sales actually came from, and where each channel's return on the next dollar falls as it saturates. This is the read the model gives you.

Marketing mix model · contribution & responseDemonstrative data
Where last month's sales actually came from
Base demand 42%Brand & Search 17%Paid social 16%Email & SMS 9%Promotions 9%Seasonality 7%
Response curves · where each channel saturates
Paid socialBrand & SearchEmail & SMS
Return on the next $1, by channel
Email & SMS$1.94 CM
Brand & Search$1.12 CM
Paid social$0.43 CM
Email still returns $1.94 in CM1 per next dollar; paid social has saturated to $0.43. The model shows where the next dollar works hardest, in contribution margin.
Baseline first

Separate what you caused from what you would have got.

A large share of revenue is base demand, it arrives whether you spend or not. Credit it to a channel and you will over-invest. The model holds the baseline constant, controls for price, promotions and seasonality, then measures the incrementalcontribution each channel actually made.

  • Causal, not correlational. The baseline is modelled, not assumed
  • In contribution margin. Incrementality measured in CM1, not revenue
  • Privacy-safe. No cookies, no pixels, no identity graph
Sales decompositionDemonstrative data
58% incremental
of last month's sales were driven by marketing
Base demand42%
Brand & Search17%
Paid social16%
Email, promo & seasonality25%
Diminishing returns

Find where the next dollar stops paying back.

Every channel saturates. The model fits a response curveper channel, so you can see the marginal return on your next dollar and the spend level where it flattens. The answer to "where should the next dollar go?" becomes a number, not an opinion.

  • Marginal return. What your next $1,000 returns in CM1, by channel
  • Saturation points. Where a channel stops scaling profitably
  • Scenario-ready. Move the dial and see the modelled outcome
Marginal return on next $1kDemonstrative data
Email & SMS$1.940 CM
Brand & Search$1.120 CM
Paid social$0.430 CM
Email still returns $1.94 in CM1 per next dollar; paid social has saturated to $0.43.
The raw signal

How customers actually get there.

The model is top-down. Underneath it sits the record: every order resolved to the exact path the customer took, touch by touch, with the engagement behind each step. Top-down and bottom-up, triangulated.

Acquisition · journey pathsDemonstrative data

From our own attribution engine, not platform-reported. Credit always adds to 100% per order, so no order is counted twice. Nothing is modelled, if a touch is not in a journey, we did not capture it.

Works with

Part of the same engine.

Marketing mix modelling shares its drivers with the rest of your Blufire capabilities.

Capability
Weather Demand Modelling
The weather and seasonality driver, modelled in its own right and fed into the mix model's baseline.
Driver →
Capability
Price Elasticity Analysis
How demand responds to price, the price lever the mix model controls for before crediting media.
Companion →
Capability
Board Packs & Custom Reporting
Drop the decomposition and response curves straight into your monthly board pack.
Report →
The team behind it

Built by an award-winning analytics team.

Blufire is trusted by 100+ mid-market and enterprise brands and operators, and recognised across the APAC and Global Search Awards. The same people now model your mix.

100+
Brands & operators
$5M-$1B
Turnover served
4
Industry awards
100 Fast StartersAPAC Search Awards 2025 WinnerGlobal Search Awards 2025 FinalistGlobal Agency Awards 2025 Finalist
Questions

The things buyers ask.

Attribution counts clicks and assigns credit touch by touch, which double-counts and flatters the platforms reporting it. Marketing mix modelling works top-down on your whole history, sales, spend, promotions, price and seasonality, and statistically separates what your marketing actually caused from the baseline that would have happened anyway. It is causal, privacy-safe, and does not rely on cookies or pixels.
Yes. That is the core output. The model decomposes your sales into a baseline (demand that arrives regardless of marketing) and the incremental contribution of each channel, promotion and seasonal driver, every figure expressed in contribution margin, not just revenue.
Yes. Each channel has a response curve with diminishing returns. The model shows the marginal return on your next dollar by channel, so you can see which channels still have headroom and which are saturating. We surface the numbers; you make the call.
No. Blufire is not an ad agency and does not manage your campaigns. We model what is working and where margin is made, then hand you the read. What you do with your budget stays entirely with you.
Sales by day, spend by channel, your promotional calendar, price, and ideally external drivers like weather and seasonality. Around 18 to 24 months of history gives the model enough signal. It runs on the data you already have in the platform.
Weather and seasonality are drivers inside the same model. Weather Demand Modelling is the dedicated view of that driver; marketing mix modelling places it alongside your channels and promotions so the baseline is properly controlled for before any media is credited.

Spend where it actually works.

Connect your history and let the model separate the baseline from the incremental, channel by channel, in contribution margin.

01

Connect your history

Sales, spend, promo, price, seasonality.

02

Model the baseline

Demand that arrives regardless of spend.

03

Measure incrementality

What each channel truly caused, in CM1.

04

Fit response curves

Marginal return and saturation by channel.

05

Decide

Where the next dollar works hardest.

Book a demo ↗See the model