EasyClick

Unlock the power of recurring revenue

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Inspiration

🔍 The Challenge: Effectively managing customer data is crucial for businesses in today's dynamic environment. Manual processes in product subscription management can lead to inefficiencies and errors. The challenge lies in effectively predicting customer loyalty to reduce churn rates and enhance retention.

💸 The Impact: According to a report by Fivetran and Wakefield Research, nearly 20% of companies have experienced the loss of customers due to not leveraging customer information for targeted marketing efforts, such as personalized advertising and promotional campaigns. The absence of precise data-driven insights leads to missed opportunities in effectively engaging and retaining customers.

🌐 The Solution: With technology advancing at a breakneck pace, leveraging automated systems for customer data analysis and targeted marketing is becoming increasingly crucial for businesses to stay competitive and relevant.

What it does

EasyClick is a subscription management platform that uses predictive analytics for customer loyalty ratings, enabling businesses to target key customer segments. It not only simplifies subscription management but also transforms it into a strategic asset for businesses, driving growth and fostering long-lasting customer relationships.

Key Features of EasyClick:

💳 Seamless Payment Integration:

  • EasyClick facilitates smooth financial transactions for product subscriptions.
  • Streamlines the billing process, making it hassle-free for both businesses and customers.

🎯 Targeted Marketing and Personalized Offers:

  • Utilizes advanced analytics to accurately predict customer loyalty ratings.
  • Identifies key customer segments, allowing businesses to focus their marketing efforts more effectively.
  • Enables the delivery of personalized email campaigns, tailored to individual customer preferences and behaviors.

🔍 Enhanced Customer Retention Strategies:

  • Aims at significantly reducing churn rates by keeping customers engaged and satisfied.
  • Personalized offers and promotions are crafted based on customer loyalty insights, ensuring higher relevancy and effectiveness.

📊 Real-Time Analytics and Reporting:

  • Provides businesses with real-time insights into subscription metrics and customer behaviors.
  • Helps in making data-driven decisions for optimizing marketing strategies and subscription models.
  • Reduces the administrative burden, allowing businesses to focus on growth and customer engagement.

How we built it

Here's an overview look at the key components and strategies we employed:

Backend Development and API Integration

  • Robust Backend with Django: The backend is built with the Django framework which supports complex subscription management tasks.
  • Django REST Framework for API Services: We utilized Django REST Framework for creating RESTful APIs to make data transfer and retrieval.

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Task Scheduling and Data Management

  • Celery for Background Task Management: We integrated Celery, a distributed task queue,to facilitate scheduled runs for pushing data from our local database to the Databricks data warehouse.
  • Redis as a Message Broker: Redis plays a pivotal role in our architecture, acting as a message broker between Django and Celery. It ensures efficient handling of task queues and real-time data processing.

Data Storage and Processing

  • Databricks Data Warehouse: For robust data storage and advanced processing, we chose Databricks as our data warehousing solution. It stores vast amounts of customer data and feeds into our machine learning pipeline for analyzing customer loyalty.

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  • Machine Learning for Predictive Analytics: Our journey in predictive modeling involved exploring various machine learning algorithms. After the model comparison, we found Residual networks to deliver the highest classification accuracy for predicting customer loyalty ratings.

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Integration with Third-Party Services

  • Twilio SendGrid for Email Marketing: To enhance our marketing efforts, we integrated Twilio SendGrid. This powerful tool enables us to send personalized email campaigns based on customer loyalty scores, directly impacting customer engagement and retention.
  • Close CRM for Management: Close CRM was chosen for its robustness in managing customer relationships. It helps us keep track of customer interactions, subscriptions, and feedback, all in one place.
  • Square's Payment API for Payments: For secure and reliable payment processing, we integrated Square's Payment API. It simplifies the transaction process, offering a safe and convenient payment experience for our users.
  • AWS S3 for Data Analytics: We leveraged Amazon S3 for its unparalleled data analytics capabilities. It serves as a repository for storing and analyzing large-scale customer data, providing us with actionable insights.

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Challenges we ran into

  • Complex API Integrations: Integrating Square's Payment API was challenging.
  • Handling Advanced Billing Scenarios: Implementing and managing complex billing scenarios like prorated billing.
  • User Experience Design: Crafting an intuitive and user-friendly interface for EasyClick, which simplifies subscription management for users, was a critical yet challenging aspect of our project.
  • Selecting the Optimal Predictive Model: One of the challenges we faced was determining the most effective machine learning model for accurately predicting customer loyalty ratings. Each model offered insights but fell short in capturing the intricate patterns hidden within our data.

Accomplishments that we're proud of

  • Streamlined Subscription Management: Automated the subscription lifecycle.
  • Celery for Task Scheduling: This automation was crucial in maintaining the freshness and relevance of our data in the warehouse, ensuring that our predictive analytics and reporting are always based on the latest information.
  • Innovative Predictive Analytics: Implemented ResNet for customer loyalty prediction.
  • Successful API Integration: Overcame challenges in integrating Square's Payment API.

What we learned

  • Machine Learning Model Selection: Learned about model selection, feature engineering, hyperparameter tuning, and deployment for customer data analysis.
  • Celery and Redis: Through their integration, we learned how to manage background tasks efficiently and handling real-time data processing. This knowledge was instrumental in automating crucial processes like data synchronization and scheduled transfers to our data warehouse.
  • Using Databricks: We learned to leverage Databricks' robust data processing capabilities, which were pivotal in handling and analyzing large volumes of customer data.

What's next for EasyClick

  • Advanced analytics and reporting capabilities.
  • Introducing more customization options for businesses.
  • Leveraging AI and machine learning for automating subscription-related tasks.

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