Azure ML-powered Personalized Recommendations for Marketing Campaigns Solution: 8-week PoC

Affine Inc

Drive more engagement and conversions from your marketing campaigns by implementing Affine’s Azure ML-powered Personalized Recommendations Solution in 8-week PoC

Affine's Personalized Recommendations for Marketing Campaigns Solution 8-week POC consulting offer powered by Azure ML is designed to provide a customized solution that can help address the multi-dimensional needs of modern marketing. The recommendations can be customized to identify a range of use cases – Up-sell/Cross-sell Product Recommendations Including Bundles, Category recommendations, Content & Creative recommendations, etc.

 

Solution Approach:

  • Data engineering: Consolidate data from various sources, including customer demographics, purchase history, and promotions data.
  • Supervised modeling: Use supervised machine learning techniques to train a model that can predict the order value for each customer across different promotions.
  • Business heuristic rulesets: In addition to the prediction model, implement business heuristic rulesets to improve the recommendations. These rulesets will take into account factors such as customer RFM segment and promotion relevance to ensure that the recommendations are as relevant and effective as possible.
  • Azure Services: The solution leverages Azure services such as Azure ML Services, Azure Data Factory, Azure Synapse, Azure Data Lake, Databricks, Power BI etc.

 

Benefits:

  • Cross-sell and up-sell: Personalized recommendations can help retailers promote related or complementary products to customers, which can lead to increased sales and revenue.
  • Improved conversion rate: Personalized recommendations can provide a more relevant and engaging experience for customers, which can help increase the conversion rate of marketing campaigns.
  • Increased promotions redemption rate: Personalized recommendations can also help increase the redemption rate of promotions by presenting customers with offers that are more likely to be relevant and appealing to them.

 

Agenda – 8 weeks:

  • Week 1: Business Understanding
  • Week 2: Exploratory Data Analysis
  • Week 3: Analytical Data Set Creation
  • Week 4: Customer 360 Profiling
  • Week 5: Model Creation
  • Week 6: Model Fine Tuning and QA
  • Week 7: Visualization – Dashboard Creation
  • Week 8: Implementation and Ongoing Optimization

 

This Proof-of-Concept implementation can be expanded to your production environment.

 

Outcome:

Solution output integrates with a web tool that can generate weekly recommendations for each customer. This will allow retailers to easily access personalized recommendations and use them to drive more engagement and conversions from their marketing campaigns.

 

Why Affine

Enabling business-focused data science, AI and BI development with deep domain expertise.  Affine believes in faster design to faster deployment through key differentiators- Experimentation Focus and Speed to Value.

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