Amazon SageMaker enables AI-enabled customer segmentation
TABLE OF CONTENT
1. Introduction2. Webinar Video3. CloudThat 4. FAQs
Introduction
Artificial Intelligence (AI), and Machine Learning (ML), are two of the most favored technological terms of the twenty-first century. Many organizations are now using these technologies to solve their business problems. There is an urgent need to spread knowledge about AI-powered tools and services to the booming tech and not-tech communities.
CloudThat collaborated to AWS to host a webinar about how to leverage Amazon SageMaker, an AI tool for Customer Segmentation. It also covered understanding the implementation process for corporate apps, use cases, benefits and underlying technology provisioning.
Watch the webinar on AI-enabled customer segmentation using Amazon SageMaker Webinar’. It was presented by Mr. BhaveshGoswami, Founder and CEO at CloudThat.
Webinar Video:
About CloudThat
CloudThat is an official AWS (Amazon Web Services), Advanced Consulting Partner, Microsoft Gold Partner and Google Cloud Partner. It helps people learn about the cloud and help businesses achieve higher goals by using the best-in-industry cloud computing practices. We aim to create a strong cloud computing ecosystem by sharing knowledge about the technological intricacies of the cloud. We provide information for all stakeholders in the cloud computing industry through our blogs, webinars and case studies.
CloudThat is a cloud-based company that offers all-encompassing IT services, including multi-cloud security & compliance, cloud enablement services, cloud-native application development, and system integration services. Check out our consulting services.
Segmentation, AI-enablement or AWS SageMaker are all topics I am available for.
FAQs:
Are product recommendations made using AI/ML in e-commerce?
Product recommendations are often targeted at an individual and may differ from person to person. Segmentation focuses on recommending products to a specific customer/entity.
Sagemaker can you use unstructured data, such as customer interaction data, to better profile customers?
SageMaker can be used for unstructured data. Even the nature of segmentation is based upon, unsupervised learning, which requires identifying new patterns within unstructured datasets.
How can I justify the expense of AI/ML over other methods
Traditional methods for analyzing data and generating Intelligence are difficult, time-consuming, repetitive, and almost impossible to automate. If we view the business as a long-term use case, it is more feasible to have AI as a core component of the business.
How can I quantify the impact of AI/ML on business growth?
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 [email protected] and we can help you start your organization’s AI/ML journey.
What are the requirements for deploying this model as an API using SageMaker
Amazon SageMaker deployment is simple. It takes only 4-5 lines of code to deploy your model.
Is the AWS SageMaker platform able to process the data from paid campaigns analysis?
It all depends on which platform you use for paid campaigns. What data are they providing to you for analytics or database intelligence?