Intelligence & Personalization

To better optimize content, recommend products, build segments, and drive marketing decisions—such as next best offer and next best action—enterprises must analyze and derive insights from customer interactions. Intelligence & Personalization solutions on AWS use artificial intelligence and machine learning (AI/ML) in addition to generative AI for predictive personalization. By using these solutions, enterprises can ultimately increase customer engagement and conversion.

AWS Services
AWS Solutions
Partner Solutions
Guidance

AWS Services

Purpose-built cloud products

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AWS Solutions

Ready-to-deploy solutions assembling AWS Services, code, and configurations

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Partner Solutions

Software, SaaS, or managed services from AWS Partners

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  • Segment

    Twilio Segment helps data, marketing, product and engineering teams leverage real-time, structured data for context relevant and personalized engagement.

  • Salesforce Marketing Cloud Customer Data Platform

    Salesforce helps the user collect and unify all data to create a single source of truth on each customer, build highly targeted audiences with actionable, AI-powered insights and grow revenue and build trusted customer relationships.

  • MoEngage

    MoEngage is an Intelligent Customer Engagement Platform trusted by enterprises in 35 countries, including several Fortune 500 brands. MoEngage offers deep personalization of customer interactions to drive better engagement, retention and loyalty.

  • Adobe Commerce

    Adobe Commerce enables personalized commerce experiences and seamless integration with in-store, retail associate, and order management technologies. Hosted on AWS, it provides scalability and flexibility for global expansion, allowing businesses to scale horizontally and vertically while minimizing storage latency. It enables a holistic and seamless shopping experience for customers, simplifying the buying process and providing secure solutions, all backed by the Amazon A-Z Guarantee.

  • Amplitude

    Amplitude helps financial services organizations like Square meet customers in the moment, with real-time experiences that drive engagement, improve conversion and bolster retention. Amplitude helps teams to bring these experiences to life by providing them with quantitative and qualitative insights, recommendations and predictions about what customers are doing and why across the entire customer journey. And because Amplitude standardizes, governs and centralizes data across all sources, teams can confidently use these insights to drive the best results.

  • Sprinklr

    Customer Experience Management Customer Experience Management with Voice powered by Amazon Connect Modern Sales & Engagement Modern Marketing & Advertising Modern Listening
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Guidance

Prescriptive architectural diagrams, sample code, and technical content

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  • Integrating a Custom Foundation Model with Advertising and Marketing ISVs on AWS

    This Guidance shows how independent software vendors (ISVs) across the advertising and marketing technology industry can increase their customer engagement by integrating their customers’ large language model (LLM) within the ISV’s generative artificial intelligence (AI) application.

  • Creating Dynamic Content with Brand Intelligence on AWS

    This Guidance demonstrates how to design an intelligent brand system that is capable of evaluating social media posts, so you can measure brand performance, create dynamic content, and protect your brand.

  • Predicting B2B Churn on AWS

    This Guidance uses machine learning (ML) to help you build a churn prediction model using structured and unstructured data.

  • Near Real-Time Personalized Recommendations on AWS

    This Guidance helps businesses build a real-time recommendation pipeline using Amazon Personalize. The pipeline creates personalized recommendations based on a user’s profile and behavior to improve the customer experience.

  • Connected Customer Journey Hub on AWS

    This Guidance helps to create a single source of truth of customer touch points to automatically understand and extract customer linked information from siloed, raw, and disparate data.

  • Subscriber Churn Prediction and Retention on AWS

    This Guidance leverages Machine Learning (ML) techniques to build churn prediction models that identify subscribers who are high risk to churn and their key drivers.

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