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Promotion Analytics
 Promotion Effectiveness 

Key Concept

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Quantify sales uplift compared to a predicted baseline without promotion

Subtract discount to get net impact

Impact

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Reduce discounts on promotions with negative net impact (discount > lift)

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Use model to predict uplift of promotions with different mechanics

For example, BOGO vs 50% discount on Segment ABC

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Use the prediction model to explore potential mechanics for new promotions

 Mechanics Optimization 

Key Concept

Impact

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Narrow down promotion incentives to a small range for A/B Testing

Recommend optimized incentive range to maximize sales or profits

Depending on data, mechanics can be optimized for every level of business

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Reduce overall budget with improved promotion outcomes

 A/B Testing 

Key Concept

Impact

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Allow more members to receive the best promotions

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Stronger decision-making supported by statistics

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Apply inferential statistics to improve test reliability and minimize experiment size

Calculate statistical significance levels and adjust control groups to sample size to a minimum

Have a project in mind?

In this complex world,

we need to collaborate to deliver outstanding work.

 Product Recommendation 

Key Concept

Impact

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Predict interest score for every customer x product combination

Separate models can be built for new products or customers with no data

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Find top potential customers for product-specific promotions

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Combine with churn prediction for personalized retention campaign

 Category Decision Tree 
Key Concept
Impact
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Recategorize products using network analysis & clustering models

Grouping products with similar relationships together

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Support in-store and in-app digital assortment layouts

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Visualize category hierarchy that represents customer decision making

Visualize category hierarchy that represents customer decision-making

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Improve other analytics that use product categories as an input (segmentation, CLV key drivers, etc.)

 Cross-Sell Rules Mining 

Key Concept

Impact

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Quantify the relationship or “lift” between two products using apriori rules mining

Calculate lift, support, and confidence, and combine with chi-squared statistical tests

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Identify bundling opportunities for products with high lift

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Use as a feature for halo/cannibalization effect for promotion effectiveness

Have a project in mind?

In this complex world,

we need to collaborate to deliver outstanding work.

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