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Pricing & Promotions Optimization

Traditional, correlational, Machine Learning approaches are often not sufficiently trusted or suitably capable to address some of the most crucial Pricing & Promotion questions

We brought to market the first operating system for decision making powered by Causal AI, decisionOS, to empower enterprises to optimise their Pricing & Promotion strategies

Traditional machine learning approaches often fail

to improve Pricing & Promotion strategies as they are unable to answer key business questions

Correlation, not causation

Spurious correlations lead to bad decisions


Read more on our blog:
How can AI discover cause and effect

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They struggle to answer why

And are often perceived as “black boxes”


Read more on our blog:
Explainable AI doesn’t explain enough

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Prediction, not next best action

E.g They can predict if a customer will convert at a certain price but cannot answer ‘what’s the optimal price for customer X and why?

Read more on our blog:
From predicting to Influencing

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Do these questions sound familiar?

Enterprises run on causal questions


What are my products’ price elasticities and what is the optimal price for a certain SKU?

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What are the next best actions (interventions) I should make in my promotions and discounts strategy to optimize for market share or profit margins?


How does competitor behavior impact my market share or margins?

See the solution in practice

Interactive Example

License our platform to answer these questions using Causal AI

Discover cause-effect relationships within your Pricing & Promotion data

Discover cause-effect relationships in your data by combining the best of domain knowledge with data-driven, statistical, approaches

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Build Causal Models

Discover causal models, based on cause-effect relationships and causal graphs, that can robustly predict estimate the effect of changes (e.g. price changes) and allow you to run powerful what-if scenarios

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Make better decisions with Decision Intelligence Engines

Leverage our pre-built engines on top of your causal models to:

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Perform powerful what-if analyses and estimate counterfactual scenarios

E.g Understand the impact of a 10% price increase

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Design next best actions

E.g Decide what promotions you should run on Black Friday

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Test the fairness of your models

Assess how fair the model is with respect to gender

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Build Decision Apps

Leverage Dara, our app building framework, to seamlessly deliver beautiful, interactive decision making applications to the marketing, pricing & executive teams

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Track and optimize Pricing & Promotion decisions

Build, deploy & monitor your decision workflows while attributing KPI performance to the appropriate actions whether that’s yours, your competitor’s actions or the macro-economic environment

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Understanding Sales Drivers

Causal AI at Nestle

Proven value in weeks

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    Internal meeting

    One hour

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    Scoping sessions

    Two to three hours

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    Platform Trial

    Three to four weeks

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    Deployment in production

    Twelve months

Start your Causal AI Journey

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