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Intelligent Marketing DataLake

🎯 Would you like to build an end-to-end pipeline to improve engagement with your customers by delivering personalized messaging and product recommendations?

✅ Are you a Data Engineer, Data Analyst, or anyone involved in building customer experiences for your organization?

1. Product Overview

Intelligent Marketing Data Lake >> AWS Services

An Intelligent Marketing Data Lake helps your customers maximize the use of all AWS services and their existing SaaS analytics products (MarTech tool), making it easy to leverage a single environment to manage their end customers engagement and interaction (Front-end and Back-end).

  • Amazon Pinpoint
  • Amazon Athena
  • AWS Glue
  • Amazon QuickSight
  • Amazon SageMaker
Intelligent Marketing Data Lake >> Major Features

  • Given the ever-increasing number of brands competing for a finite amount of customer attention, maximizing customer engagement is vital. In today’s digital marketplace, it is critical to keep your users coming back to your app. One method that can help improve customer engagement is to deliver personalized messaging to your users. Personalized messaging can help build trust in your brand and increase conversion rates.

  • We are going to show you how Amazon Pinpoint helps you engage with your customers by sending personalized email, SMS and voice messages, and push notifications. With Amazon Pinpoint, you can place your customers in groups based on demographics, behaviors, or other key performance indicators that are important for your business, and send highly personalized, timely, and relevant messages to those groups.

  • Additionally, Machine Learning (ML) can also help you improve your customer engagement by analyzing your customer activity, identifying patterns, and making recommendations to help you convert users. However, it can be a challenge to integrate ML models with messaging tools for companies without deep, in-house ML expertise. We will show you how easily you can leverage the personalized messaging engine of Amazon Pinpoint with machine learning without ML expertise.

This PoC is designed to provide a simple architecture to demonstrate how to use ML to make product recommendations and automatically update your endpoints and segments. You can build upon this architecture for a variety of use cases.

2. Architecture & Technology

Intelligent-Marketing-DataLake Architecture

🔎 Architecture Overview
  • [x] A digital user engagement solution, Amazon Pinpoint, collects user engagement data from email, SMS, push notifications, voice, and in-app notifications. The data collected from Amazon Pinpoint (customer demographic and subscription information data) is streamed to Amazon S3 bucket through the Amazon Kinesis firehose. The data for the solution has been uploaded for now, but organizations and businesses can import their own data from CRMs or other sources of customer information.
  • [ ] Customer demographics are stored in the fully managed serverless database, Amazon DynamoDB. DynamoDB provides predictable low latency response to quickly look up information by Customer ID or Customer token.
  • [ ] AWS Glue infers the table structure from the data stored in Amazon S3 and Amazon Athena provides a mechanism to query the data using SQL-based structures.
  • [ ] Using Amazon Sagemaker endpoint, where we have a ML model deployed and it gives you an inference output that predicts customer churn. As part of this solution, we have a model deployed, but customers can build their own algorithm model and deploy it in Amazon Sagemaker to predict customer churn.
    • As a result of the inference from Amazon Sagemaker, the segment that is likely to churn is fed into Amazon Pinpoint, which creates a customer segment, and businesses can then use it to send out any promotional emails or run advertising campaigns specifically targeted to that segment. So its providing actionable intelligence and also the ability to take action on that. From within Amazon Pinpoint you can use the HTML template to create an email, send it across to them with personalized messages.
  • [ ] Amazon QuickSight is used to visualize Amazon Pinpoint engagement data in Amazon S3. Customers can build KPIs like daily engagements, daily active users, etc. by using Amazon QuickSight.
Setup
  • [x]

3. Fast-track Implementation & Delivarables

Digital User Engagement Solution
  • [ ] 1. Collect and Store real-time customer interaction
  • [ ] 2. Creating Marketing e-mail campaing
  • [ ] 3. Analyzing the data from Data Lake
  • [ ] 4. Predict Customer Churn
  • [ ] 5. Visualizing Customer Activity
Resources & Services
  • [x]
Fast-track Implementation
  • [ ] Prepare Fasttrack-Template.xls
  • [ ] Validate & Import the Fasttrack-Template.xls
  • [ ] Test & Go-Live