MARKETING & STRATEGY
Marketing mix optimization: put each euro where it returns most
Marketing mix optimization with TIMi estimates the profit each marketing action is expected to generate, then searches for the split of investment across actions that maximizes the total, under your budget and capacity constraints.
Profit per action
Estimate what each marketing action should return.
Explicit constraints
Total budget, channel limits and stock are part of the search.
Readable assumptions
Each estimate rests on factors you can inspect.
HOW IT WORKS
How marketing mix optimization works.
Three steps, in one engine, on a standard server with no cluster.
1. Prepare the data
Anatella gathers campaign history, measured responses, costs and customer data, then structures them into variables.
2. Estimate the response
Modeler builds propensity models for each action or offer, to estimate the expected response and profit for each customer.
3. Optimize the split
The optimization toolbox integrated in Anatella searches for the allocation of budget and offers that maximizes expected profit under your constraints.
Anatella
ModelerGETTING IT RIGHT
Choices that shape a marketing mix model.
The result is only as useful as the question and the constraints it is given.
Define profit, not only response
A response model ranks customers. A mix decision needs a value for each response (margin, cost per contact). Those values come from your business and finance teams.
Past campaigns are the raw material
Estimates rely on campaigns already run, with measured results. With little history, the first outputs are indicative and improve as results accumulate.
Make constraints explicit
Budget, channel capacity, product stock and contact pressure per customer are entered as constraints of the optimization, not adjusted by hand afterwards.
EXPLAINABILITY
A split is only useful if you can defend it.
A budget split moves real money. A white-box model shows which customer characteristics drive the expected response to each action, so marketing and finance teams can challenge the assumptions behind the numbers.
For marketing teams
See which customer profiles respond to which action, instead of relying on a single average rate.
For finance
Expected profit per action rests on explicit inputs: response, margin and cost.
For model owners
Modeler’s built-in Drift Report shows when a model loses accuracy, so you update it when needed instead of on a fixed calendar.
DATA
What data a marketing mix model uses.
Anatella connects to more than 80 sources, so this data can be gathered without prior custom development.
Campaign history
Actions run, audiences contacted, dates and measured responses.
Costs and margins
Cost per contact and margin per product or action.
Customer data
Profile, purchase history and behavior.
Constraints
Budget, channel capacity and stock.
PROOF
Marketing mix in practice.
We do not have a published case study dedicated to marketing mix optimization. The reference below is indirect: it shows the scale of the propensity scoring on which a mix model rests.
63 products scored across 300,000 stores
Not a documented marketing mix case. It illustrates the scale of the scoring step: 2.4 million scores per second, one score per product and store, computed on a single platform.
FAQ
Common questions.
Does TIMi decide the budget for us?
No. It estimates the expected profit of each action and proposes a split under your constraints. The decision, and the business values behind it, stay with your teams.
How much history do we need?
The models learn from campaigns already run, with measured results. With little history, the outputs are indicative and improve as results accumulate.
Can it handle stock or contact limits?
Yes. Constraints such as limited stock per product or a fixed number of offers per customer are handled by the optimization toolbox integrated in Anatella.
Does it measure attribution across channels?
Not by itself. It works on the actions and responses you track. Attribution rules remain defined by your teams.
RELATED USE CASES
Keep exploring.
Marketing ROI Simulation
Simulate the return of a campaign at different sizes before launching it.
Next Best Offer
Rank the offers each customer is most likely to accept, with the reasons why.
Lead Scoring
Rank leads by their likelihood to convert, with the reasons behind each score.
SEE FOR YOURSELF
Test it on your own data.
Run TIMi on your own data with a free trial, or talk to us about your case.
