A bank has been running traditional marketing campaigns for many years.

In the always-on outbound customer engagement paradigm, leveraging AI and continuous decisioning is crucial:

AI-Driven Decisioning:

Step 1: Configure the primary schedule to run daily, allowing the AI engine to continuously evaluate and select the best action for each customer.

Step 2: The AI considers engagement policies, customer behavior, and contextual data to determine the most relevant action.

Benefits of Always-On Engagement:

Continuous evaluation of customer interactions ensures that the actions presented are timely and contextually relevant.

It allows for dynamic adjustment of offers based on real-time data and customer responses.

Implementation Steps:

Step 1: In Next-Best-Action Designer, set up a primary schedule to run daily.

Step 2: Define engagement policies and configure AI models to select actions based on customer interactions and preferences.

Step 3: Allow the AI to decide whether to resend the original offer or present a new offer based on the customer’s response or lack thereof.

Example:

If the customer ignores the first email, the AI might decide to send a reminder email or a different offer based on updated engagement data and policy rules.

References:

Pega-Customer-Decision-Hub-User-Guide-85.pdf: "Configuring a recurring schedule for Next-Best-Action" section.

Pega documentation on "Using AI in decisioning".