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Creating a Customer Interaction Strategy in Pega Customer Decision Hub

Updated: Dec 11

In today’s data-driven world, understanding customer behavior and creating strategies  that respond intelligently to their interactions is crucial. The Pega Customer Decision  Hub (CDH) offers a comprehensive way to craft strategies that use interaction history  for informed decision-making. A common use case is identifying whether a customer  has previously engaged with a specific action, such as clicking a mortgage offer. 


Why Check for Previous Interactions?

 

Identifying customers who have previously interacted with an offer or action helps tailor  future interactions and refine marketing efforts. For instance, if a customer has clicked  on a mortgage offer, it indicates interest, and a well-timed follow-up offer can be more  effective. Conversely, if a customer has never engaged, a different approach may be  needed. 


Step-by-Step Guide to Create the Strategy 

Follow these steps to build a strategy that checks for past interactions in Pega CDH: 





1. Create the Strategy in Pega CDH 

• Navigate to Intelligence > Strategies. 

• Click Create > Start with new canvas. 

• Give the strategy a descriptive name, like "Engaged with Mortgage Offers," and  select the Customer class from the Primary Context, e.g., PegaCRM-DataCustomer. 

• Click Create and open. 

2. Enable External Input 

• Right-click inside the strategy canvas and select Enable external input. 

3. Add Essential Components 

• Add the following shapes to the canvas: 

o Interaction History Summary: This shape pulls past interaction data. 

o Data Join: Combines data for richer context. 

o Two Filter Shapes: Filter and refine data based on specific criteria. 

4. Configure the Interaction History Summary 

• Double-click the shape and name it (e.g., "Action Outcomes"). 

• Set the Summary data set field to OfferOutcomeCount. 

• Click Submit. 

5. Set Up the First Filter 

• Name this filter "Clicked on Mortgage Actions." 

• Open the expression builder and create a condition to count specific  interactions, like clicks on mortgage offers. 

• Click Submit. 6. Configure the Data Join 

• Name this shape "Join Mortgage Clicked Count." 

• Choose the first filter as the source component and set conditions like .pyIssue =  .pyIssue. 

• Map properties to set .Count = .Count. 

• Click Submit. 7. Set Up the Second Filter 

• Name it "Clicked Once or Many Times." 

• Add a condition: .Count > 0 to check if the click count is greater than zero. 

• Click Submit. 

8. Mark the Strategy as Relevant 

• Select Actions > Mark as relevant record to make the strategy easily  accessible. 


Result: The strategy uses two filters to determine past interactions. The first filter summarizes  interaction history and identifies counts of specific actions. The second filter checks if  the count is greater than zero. If the customer clicked on a mortgage offer at least once,  the strategy result is true; otherwise, it is false. 

Defining an Eligibility Rule Using Your Strategy To refine customer qualification further, you can add an eligibility rule in your  engagement policy using the strategy. 

Here’s how: 

1. Navigate to the NBA Designer 

• Open Customer Decision Hub. 

• Click Next-Best-Action > Designer > Engagement policy and then click Edit. 

2. Add the Eligibility Rule 

• In the Eligibility section, click the Add a row (+) icon. 

• Specify the rule as: Customer <your strategy name> has results for Final  output. 

• For example: Customer Engaged with Mortgage Offers has results for  Final output. 

3. How the Rule Works 

• The rule checks if the strategy has results for the final output. If the  customer’s interaction count is greater than zero (indicating previous  engagement), the strategy result is true, and the customer is eligible for  another action. If the count is zero, the result is false, and the customer  will not qualify. Practical Applications Imagine you are running a campaign for mortgage refinancing: 

• If a customer has previously clicked on a mortgage offer, the eligibility rule  makes them eligible for the refinancing action. 

• If the customer has not interacted with mortgage offers, they will not qualify, and  you can direct them to a different action. 


Conclusion 

By leveraging Pega CDH’s strategy and integrating it into the NBA Designer, businesses  can make data-driven decisions, improve customer engagement, and create more  meaningful and personalized offers. Checking for previous interactions and adding  eligibility rules ensures that your engagement strategies are highly targeted and  effective, optimizing customer experience and maximizing marketing success.




--TEAM ENIGMA

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