Your brand now has the power to build personalization and recommendation engines using the same platform as Amazon.com-with no machine learning experience required.
Amazon offers Amazon Personalize, which uses Amazon's machine learning technology to make it easy to develop an application and/or custom model that can:
- Create a completely personalized experience with customer data.
- Serve up custom content recommendations with your own personalized recommendation engine and machine learning model.
- Individualize search results and item recommendations for a truly unique customer experience.
- Run personalized marketing promotions based on behavioral data.
According to Amazon:
"Amazon Personalize reduces the time to build a custom (machine learning) model from months to days. When using Amazon Personalize, customers provide the service an activity stream from an application (e.g. page views, signups, or purchases) along with an inventory of the items to recommend (e.g. music, videos, products, or news articles), and receive recommendations via an API."
If you have some development expertise—or can rent some—Amazon Personalize could be a great choice to spin up high-quality personalized recommendations for your users, prospects, and customers.
What Is Amazon Personalize?
Amazon Personalize is a machine learning service that makes it easy for developers to create personalized user experiences at scale.
It uses the same recommender system technology that Amazon uses to create its own personalized recommendations.
According to Amazon:
"Amazon Personalize makes it easy for developers to build applications capable of delivering a wide array of personalization experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing. Amazon Personalize is a fully managed machine learning service that goes beyond rigid, static rule-based recommendation systems and trains, tunes, and deploys custom ML models to deliver highly customized recommendations to customers across industries such as retail and media and entertainment.
Amazon Personalize provisions the necessary infrastructure and manages the entire ML pipeline, including processing the data, identifying features, using the best algorithms, and training, optimizing, and hosting the models. You will receive results via an Application Programming Interface (API) and only pay for what you use, with no minimum fees or upfront commitments. All data is encrypted to be private and secure, and is only used to create recommendations for your users."
There are three big benefits to using artificial intelligence from Amazon Personalize:
1. Create high-quality recommendations.
Using Amazon Personalize, you can quickly create and deploy useful recommendations on your site, including content recommendations and product recommendations. These recommendations cause users to engage more—and longer—with pages, content, and products, behavior that in turn drives revenue.
2. Personalize every part of the user journey.
Amazon Personalize integrates into all of your marketing channels and devices. So, no matter where a user engages with your brand, you can create personalization recommendations every step of the way.
3. Deploy in just a few clicks.
Amazon touts Personalize's ability to delivery personalization "within days, not months." In fact, Amazon Personalize can often be deployed with a few clicks, rather than brands having to build and train their own recommendation model.
Amazon Personalize Pricing
Amazon Personalize has a pay-for-use pricing model that results in personalized costs for customers based on usage.
There are no minimum fees or upfront commitments, and customers are charged based data processing and storage, compute hours to train the models and the number of recommendations performed. You are charged per gigabyte of data uploaded to Amazon Personalize. You are also charged for the training hours used to train machine learning models with the tool.
The service has a free trial, where you receive up to 20 gigabytes per month of data storage, up to 100 training hours per month, and up to 50 TPS hours of real-time recommendations per month.
Amazon also has an Amazon Personalize pricing calculator to help you more accurately gauge your individual cost.
4 Amazon Personalize Use Cases for Marketers
Marketers can use Amazon Personalize in four compelling ways.
1. Content Recommendations
You can use Amazon Personalize to serve up additional content to your users based on different criteria (for instance "Because You Watched X").
2. Product Recommendations
You can deliver personalized product recommendations to users based on their browsing and purchase behavior. This includes showing them similar items they might enjoy.
3. Contextual Recommendations
You can use Amazon Personalize to generate content and product recommendations that trigger only within certain contexts, such as device time, location, or time of day.
4. Personalized Promotions and Notifications
Last, but not least, marketers can use the service to personalize promotions to users based on their behavior. You can also notify users based on different personalization factors.
Paul Roetzer is founder and CEO of Marketing AI Institute. He is the author of Marketing Artificial Intelligence (Matt Holt Books, 2022) The Marketing Performance Blueprint (Wiley, 2014) and The Marketing Agency Blueprint (Wiley, 2012); and creator of the Marketing AI Conference (MAICON).