Amazon Personalize

Personalized Machine Learning used to deploy API for meeting demands of customers. The day-to-day business needs are on-boarded to Amazon Personalize to meet business increased demands. The capability enhances user experience too in a more sophisticated way. We see more potential growth in customer business with the use of Amazon Personalize.

• personalized ad placements
• marketing communication improved
• Real-time recommendations

• Prioritizing business goals
• Batch recommendations

Eggplant, from Keysight, V7 Darwin and Neptune DX Platform

Eggplant, from Keysight, V7 Darwin, Neptune DX Platform

It is one of Amazon Web Services' best machine learning services for website recommendations. I created a fashion store website for a client in which I used the Amazon Personalize API to provide the best recommendations based on the visitor's preferences. It enables clients to select the best products and generates a personalized search as a result. Amazon Personalize is simple to set up and quickly maintain each dataset, so you never have to worry about manually updating the data whenever visitors log in to your website.

• Communication and Personalization Support.
• User Friendly.
• Accurate Recommendations of the Products.

• Increase number of sales.
• Interest from the clients.
• Great Customer Support service.

Amazon Pay, Amazon Web Services and Google Classroom

Amazon Pay, Amazon Web Services, Google Cloud AI

We already using all Amazon environment. Amazon Personalize is giving us opportunity to get feedback from our internal team and customers. With that feedbacks, we are focusing on our weak sides and try to fix them so quickly to give best experience to our internal and external customers. That is why Amazon Personalize doing a great job.

• Easy to use
• Capable with other Amazon products

• Giving accurate data to improve our work
• Getting real and strong feedback to solve our problems

We were looking for a platform to generate user segmentation based on their platform usage. Our platform provides billing and invoicing applications to various kinds of businesses. As a by-product, we generate transactional data that we wanted to use to segment usage data in groups around their hours of operation, transaction amounts, and product/service types.

• Support for real-time recommendations.
• Ease of integration with other tools using APIs.
• Support for analyzing unstructured information (ie. texts).

• We managed to analyze huge amounts of data from transactional records.
• We produced 5 different user/profile segments for our marketing team.
• We learned how to power marketing predictions using machine learning.

AWS Batch, AWS Lambda, Amazon S3 (Simple Storage Service)

We use Amazon Personalize to make bespoke experiences for our users. Rather than having a team of expensive engineers who are experienced with ML, ride the shoulders of the giant, that is, Amazon.

• Robust integration points across our tech stack (website, app, email marketing, etc.)

• We were able to reduce our bounce rate significantly by personalizing our landing pages to the location that our users are visiting from.