Real-time recommendation and personalization to increase customer engagement and lifetime value
Build sophisticated personalization capabilities into your applications
As companies seek to improve customer engagement through more accurate product and content recommendations powered by machine learning, they face the complexities of building recommender systems, from data processing in real time to accuracy and scalability.
Amazon Personalize is a machine learning service that enables to more easily build real-time recommendation and personalization systems. The service can process a wide range of sales and demographic data to deliver personalized recommendations that are widely applicable in industries as diverse as retail, eCommerce, media & entertainment, and subscription-based internet businesses.
Amazon Personalize is like having your own Amazon.com machine learning personalization team at your disposal, 24 hours a day.
With Amazon Personalize, developers can easily overcome such problems as new users with no data, popularity biases and evolving intent of users, to deliver highly personalized recommendations based on specific needs, preferences, and behavior of your users.
Right product recommendations improve user engagement on your website. With Amazon Personalize, customer activity is analyzed and matched with their profile in real time to identify what they are looking for and deliver accurate recommendations before they leave.
Personalized recommendations can be easily integrated into websites, mobile apps, content management and email marketing systems, to drive tailored search, sorting, and offers. Companies can provide a cohesive experience for users across all channels and devices.
With the right technology under the hood and a user-friendly UI, developers can build, train, tune, and deploy a custom personalization model in just a few clicks, thus reducing the amount of time needed to deliver personalization experiences from months to days.
How It Works
Data streams, inventory and demographics data are provided to Amazon Personalize for processing. The right algorithms are selected, trained, and optimized to customize the personalization model, based on customer data.
Increase engagement and customer lifetime value by delivering accurately tailored, personalized recommendations based on a customer’s behavior, history, and preferences.
Improve the accuracy and relevance of search results on your website or in your application by analyzing a customer’s preferences and intent based on the behavioral data and past interactions.
Increase the efficiency of your marketing communication channels by aligning the messages your customers receive with the behavior based on the geodata, buying habits, sales data, and more.
What We Offer
POC in a Box is a joint program by Provectus and Amazon Web Services geared toward creating use case-based, deployment-ready POCs on Amazon Personalize in just a week-long hands-on engagement.
What We Offer
Provectus runs several assessment sessions with customer stakeholders to define goals and success criteria, check your organization’s data readiness.
Provectus explores potential use cases, builds initial models, and evaluates the metrics. All active models are evaluated to outline the path to production.
Provectus runs the model to test how it interacts with real-world data from your application. The model is fine tuned to improve performance.
Provectus evaluates A/B test results against initially defined goals and success criteria. The next steps required to move POC to production are provided.
As a result of the engagement, you receive a ready-for-deployment POC, which you can opt to move to production with Provectus.