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Transforming Email Marketing with AWS-Powered Intelligence for Leading Hospitality Brand

Summary

In the competitive travel and hospitality industry, our client, a distinguished leader with an impressive portfolio of resorts and vacation retreats, continually strives for excellence. Despite their industry-leading position, they faced the common challenge of relying on a decade-old legacy system for email marketing, leading to imprecise customer targeting and low click-through rates (CTR). Proactively recognizing the need for modernization, they enlisted Tredence to redesign their email marketing strategy using cutting-edge technology and data-driven insights.

Goal

The primary objective was to create a state-of-the-art, production-ready, and fully automated end-to-end solution. This innovative system would incorporate multiple propensity models, email click prediction models, and an advanced optimization process. The aim was to substantially improve the accuracy of email click predictions, transforming into better customer targeting and more focused marketing efforts. Over the course of six months, Tredence developed an end-to-end solution comprising of ETL tools , which included ETL tools, machine learning models, and an optimizer leveraging various AWS services.

Insights Powered by AWS

At the heart of this transformation was the robust and versatile Amazon Web Services (AWS) ecosystem. AWS provided the technological backbone that enabled us to build, deploy, and manage its sophisticated marketing models with unprecedented efficiency and scalability. 

The AWS-powered insights allowed for:

  • Real-time data processing and analysis: Enabled up-to-the-minute decision-making in email marketing campaigns.
  • Advanced machine learning capabilities: Facilitated the development of highly accurate propensity and email click prediction models.
  • Seamless integration of various data sources: Provided a holistic view of customer behavior and preferences.
  • Scalable computing resources: Handled the complex optimization processes required for targeted marketing.
  • Automated pipeline management: Ensured consistent model performance and easy retraining at regular intervals. 

These AWS-powered insights transformed raw data into actionable intelligence, allowing us to understand and predict customer behavior with far greater accuracy.

Approach

The approach to revolutionizing the email marketing strategy was multi-faceted and comprehensive, leveraging cutting-edge technologies and methodologies:

1. ETL in Snowflake:

The foundation of the new system was laid with a robust Extract, Transform, Load (ETL) process implemented in Snowflake. This process involved extracting and processing a wide array of features crucial for both Propensity and Email Click models, including:

  • Customer Booking Information
  • Customer Demographics
  • Customer Engagement Metrics (Website and App Views)
  • Customer Loyalty Membership details
  • Various Offer Attributes

This comprehensive data collection ensured that subsequent models had access to a rich, multi-dimensional view of each customer and offer.

2. Model Development in Amazon SageMaker Studio:

The heart of the new system centered on sophisticated machine learning models developed and deployed using Amazon SageMaker Studio. Key aspects of this phase included:

  • Implementation of XGBoost, a powerful gradient boosting framework, to handle the highly imbalanced dataset for both the Propensity and Email Click models.
  • Rigorous model selection through cross-validation assessment and hyperparameter tuning.
  • Utilization of Cumulative Lift Value as a critical evaluation metric to benchmark model performance against industry standards.

3. Gurobi Optimization:

The final component was the implementation of Gurobi Optimization. This advanced mathematical optimization solver was utilized to:

  • Identify the optimal set of offers to be sent to eligible customers.
  • Maximize the expected probability of customers clicking on the emails.
  • Ensure a balance between customer preferences and marketing objectives.

This three-step approach synergized data processing, predictive modeling, and optimization, resulting in a robust, data-driven email marketing system.

AWS Services Used

The success of this project was bolstered by the strategic utilization of several AWS services:

  • Amazon SageMaker: Serving as the backbone of the model development process, Amazon SageMaker offered a fully managed machine learning platform. It provided comprehensive tools and workflows for building, training, and deploying machine learning models at scale.
  • Amazon S3: This scalable storage service played a crucial role in storing and retrieving the extensive datasets required for model training and execution, ensuring seamless accessibility and reliability.
  • Amazon CloudWatch: Utilized for monitoring and observability, Amazon CloudWatch enabled continuous tracking of system performance. It facilitated proactive measures by triggering alerts when deviations or issues arose, ensuring the system operated smoothly and efficiently.

 

Benefits & Results

The implementation of this advanced, AWS-powered email marketing system yielded impressive benefits:

1. Significant Improvement in Customer Engagement: 

The new system achieved a substantial increase in Click Through Rate (CTR), rising from approximately 0.7% to 1.8%. This represents a remarkable 2.3x boost in engagement.

2. Focused Marketing:

The precision of the new models enabled more targeted marketing efforts, enhancing efficiency in acquiring new customers and re-engaging existing ones. This approach improved customer experience by delivering relevant and compelling offers.

3. Fully Automated Production Pipeline:

End-to-end automation of the marketing pipeline brought unprecedented efficiency and consistency. The system's capability for easy monitoring and regular retraining ensures ongoing effectiveness amidst evolving customer behaviors and market dynamics. 

4. Enhanced Data Utilization:

Leveraging extensive customer data—from booking details to app usage—provided a comprehensive understanding of customer preferences and behaviors. This enriched data utilization supports personalized and impactful marketing strategies.

5. Scalability and Future-proofing:

Built on AWS services, the system ensures scalability to handle increasing data volumes and evolving marketing complexities. This future-proofs the email marketing efforts, keeping the client competitive in the market.

6. Cost Efficiency:

Improved targeting and higher engagement rates optimize the use of marketing resources, potentially leading to significant cost savings over time.

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