AI-Enabled Customer Segmentation using Amazon SageMaker

Introduction

Artificial Intelligence (AI) and Machine Learning (ML) are two of the most popular technological terms in the twenty-first century. To solve business problems, most organizations are now leveraging these technologies to automate their processes. However, there is a need to disseminate AI-powered tools and services knowledge to the booming tech and non-tech population.

CloudThat collaborated with AWS to conduct a webinar on spreading the knowledge about leveraging Amazon SageMaker, the AI tool for Customer Segmentation, and understanding the implementation process for corporate applications, use cases, benefits, and underlying technology provisioning, along with a demonstration.

Watch the webinar on ‘AI-enabled Customer Segmentation using Amazon SageMaker Webinar’ by the Founder and CEO of CloudThat, Mr. Bhavesh Goswami here, Mr. Meghanathan Manjunath, Solution Architect, Amazon, and Arihant Bengani, Lead SME Architect, CloudThat.

Webinar Video:

About CloudThat:

CloudThat is the official AWS (Amazon Web Services) Advanced Consulting Partner, Microsoft Gold Partner, Google Cloud Partner, and Training Partner helping people develop knowledge of the cloud and help their businesses aim for higher goals using best-in-industry cloud computing practices and expertise. We are on a mission to build a robust cloud computing ecosystem by disseminating knowledge on technological intricacies within the cloud space. Our blogs, webinars, case studies, and white papers enable all the stakeholders in the cloud computing sphere.

CloudThat is a house of All-Encompassing IT Services on the cloud offering Multi-cloud Security & Compliance, Cloud Enablement Services, Cloud-Native Application Development, and System Integration Services. Explore our consulting here.

If you have any queries about Segmentation, AI-enablement, or AWS SageMaker, drop them in the comment section and I will get back to you quickly.

FAQs:

1. In the e-commerce domain, are the product recommendation using AI/ML?
   

   Product Recommendations are usually targeted towards an individual and might differ person by person, segmentation focuses on recommending to a specific group of customers/entities

2. Can you use unstructured data e.g., customer interaction data to better profile customers using Sagemaker?

   Yes, you use SageMaker for unstructured data, even the nature of segmentation is based on, unsupervised learning which requires identifying new patterns in unstructured data.

3. How do I justify the cost of using AI/ML over other methods?
   

   Traditional methods of doing analytics and deriving Intelligence from the data are quite complicated, require a lot of time/effort and its very much repetitive, and automation is almost impossible to achieve. Thus, if we consider the business as a long-run use case it’s more viable to have AI as a core component to drive the business.

4. How do I quantify that the business growth is coming from the usage of AI/ML?

   It is quite subjective, it depends on the problem statement you are trying to solve, for more details you can reach out to us at consulting@cloudthat.com and we can help you start your organization’s AI/ML journey.

5. What are the provisions of deploying this model as API using SageMaker?

   With Amazon SageMaker deployment is quite simple, it’s 4-5lines of code to deploy your model.

6. Does the data from paid campaign analysis go through the AWS SageMaker platform?

   It depends on the platform you are using for the paid campaigns and what kind of data they are providing for you to run analytics or to derive database intelligence.

WRITTEN BY Arihant Bengani

Arihant Bengani is a Cloud Solution Architect leading the vertical of Data, AI and IoT for Tech Consulting at CloudThat. He is a Technology Enthusiast, AWS Data Analytics Speciality Certified and AWS Solutions Architect Associate Certified. He has published many tech blogs related to AI/ ML, IoT and Data Analytics.