MaxAI Integration

Key Features of MaxAI

• Predictive Analytics: Leverage historical and real-time data to anticipate customer behavior and forecast outcomes with high accuracy.
• Real-Time Decisioning: Process data streams instantly to support dynamic, in-the-moment personalization and automated action triggers.
• Machine Learning Model Management: Build, deploy, and monitor custom ML models within a centralized, scalable infrastructure.
• Seamless API Integration: Connect MaxAI easily with external systems via RESTful APIs, ensuring smooth interoperability with customer data platforms (CDPs), CRMs, and marketing automation tools.
• Privacy and Compliance Controls: Built-in governance frameworks ensure that AI decisioning adheres to privacy regulations and data usage policies.

Understanding the Components

The cycle begins with data ingestion, where MaxAI collects and integrates information from various internal and external sources. Once the data is ingested, it undergoes pre-processing, where it is cleaned, structured, and prepared for analysis for ensuring quality and consistency for accurate modeling.

The next phase involves identifying the relevant variables from the dataset to improve model performance and efficiency. MaxAI then moves into model training, where it applies advanced machine learning algorithms to generate predictive models. After training, MaxAI supports visualization and explanation of model behavior, offering insights into how predictions are made and the factors influencing them. This enhances transparency and trust in the AI outcomes. Following this, the models are tested against unseen data in the model testing phase to validate their real-world effectiveness.

Once validated, models are prepared for production through model conversion and deployment, where they are transformed into formats suitable for operational use. Finally, MaxAI continuously manages model monitoring and observation, tracking performance metrics and detecting issues such as data drift, ensuring that deployed models remain reliable and up to date over time.

HCL MaxAI support the following reference models:

• Next Best Channel: Recommends the most effective communication channel for each customer.
• Send Time Optimization: Predicts the optimal time to send messages to maximize engagement.
• Churn Prediction Model: Identifies the likelihood that a customer will stop using a company's products or services within a given period.
• Buying Propensity Model: Predicts the likelihood that a customer, existing or new, will adopt or purchase a specific product in the near future.

For more information about MaxAI reference models, refer to the Reference Models section in the MaxAI workbench User Guide.

Integration Steps

MaxAI integration with HCL CDP enables marketers to leverage AI-driven decisioning within their customer engagement strategies. MaxAI delivers predictive insights and intelligent recommendations, such as Next Best Channel and Send Time Optimization.

By embedding MaxAI models directly into CDP campaigns, marketers can automate and personalize customer interactions at scale. This integration bridges customer intelligence with campaign execution, ensuring data-driven decisions that enhance engagement and improve marketing ROI.

1. Access MaxAI Models: Ensure that the MaxAI models like Next Best Channel, Send Time Optimization are trained and published. For more information about training the model, refer the Training the Model section of MaxAI Workbench User Guide.
2. Configure CDP to use MaxAI Models. For more information, reach out the support team.