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Amazon Personalize

Score9.6 out of 10

8 Reviews and Ratings

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What is Amazon Personalize?

Amazon Personalize uses machine learning algorithms to create recommendations that respond to the specific needs, preferences, and changing behavior of users in real-time, to drive increased customer engagement.

Categories & Use Cases

Reviews

What users are saying about Amazon Personalize.
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Amazon Personalize to meet your daily Business Needs, Easy integrate

Incentivized
KAUSHIK DEBNATHView profile
SAP BASIS Consultant in Information Technology at Bristlecone (501-1000 employees employees)

Use Cases and Deployment Scope

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.

Pros

  • Easily implement personalized
  • Personalize every touchpoint
  • High-quality delivery in real-time

Cons

  • More features
  • More in-built applications
  • More frequent updates
  • New user recommendations can be sometimes not easy

Most Important Features

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

Return on Investment

  • Prioritizing business goals
  • Batch recommendations

Alternatives Considered

Eggplant, from Keysight, V7 Darwin and Neptune DX Platform

Other Software Used

Eggplant, from Keysight, V7 Darwin, Neptune DX Platform

A fantastic way to make recommendation easy and straightforward

Incentivized
Avinash SaklaniView profile
Frontend Developer in Information Technology at Fiverr (1-10 employees employees)

Use Cases and Deployment Scope

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.

Pros

  • Personalized Search.
  • Best Recommendations.
  • Maintaining the Dataset of Clients.

Cons

  • Repetitive Recommendations.
  • Needs to improve the search speed.
  • Costly to purchase.

Most Important Features

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

Return on Investment

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

Alternatives Considered

Amazon Pay, Amazon Web Services and Google Classroom

Other Software Used

Amazon Pay, Amazon Web Services, Google Cloud AI

Great product to get accurate data for your work

Incentivized
Verified User
Professional in Information Technology (501-1000 employees employees)

Use Cases and Deployment Scope

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.

Pros

  • Easy to use
  • Get accurate data

Cons

  • Nothing for now

Most Important Features

  • Easy to use
  • Capable with other Amazon products

Return on Investment

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

One of the best cloud, business-ready machine learning solutions.

Incentivized
Verified User
C-Level Executive in Information Technology (11-50 employees employees)

Use Cases and Deployment Scope

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.

Pros

  • Ingest virtually unlimited quantities of transactional data.
  • Provide world-class training capabilities.
  • Provide a free-tier to start your project.

Cons

  • Getting started may be hard for someone without prior machine learning experience.
  • IDE tools may help business users utilize these tools without the help of a programmer.

Most Important Features

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

Return on Investment

  • 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.

Other Software Used

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

Let Amazon do the heavy lift around ML for you and your team.

Incentivized
Verified User
Executive in Product Management (11-50 employees employees)

Use Cases and Deployment Scope

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.

Pros

  • Real time recommendations based on user activity & engagement.
  • Speed to market when it comes to iterations & refinements.

Cons

  • Pricing could be better.

Most Important Features

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

Return on Investment

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