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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

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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

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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?

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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

Learn more
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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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