Engagement Policy & Customer Offers

• This is a student Guide on Cross-Selling on the Web
• It is valid as of April 10, 2024

Next Best Action on Digital

• A typical cross-selling use case on the web channel and its four phases of implementation are described
• The goal is to improve 1-to-1 customer engagement, drive sales, and deliver Next-Best-Actions in real time

Business Use Case: Cross-Sell on the Web

• Pega Customer Decision Hub's Next-Best-Action Designer lets one configure how the "always-on brain" selects the best offer for a customer

• Cross-selling on the web channel aims to improve 1-to-1 customer engagement, drive sales, and deliver Next-Best-Actions in real-time

• U+ is a retail bank that wants to use its website as a marketing channel to improve customer engagement, drive sales, and deliver Next-Best-Actions

• The bank uses Pega Customer Decision Hub™ to recommend relevant banner ads to customers visiting their personal portal

• Banner ads are displayed on various website pages

• The homepage features a Hero banner with a larger image and typeface

• Tile banners, which are typically smaller, are also displayed

• When customers log on to their personal portal, they also see a tile banner on the ‘Account overview' page

• The main intent of U+ is to increase web engagement, measured by click-through rate from the 'Learn more' link

• The bank wants to display relevant offers on the ‘Account overview' page, selected using AI and business rules within the Pega Customer Decision Hub.

• The Pega Customer Decision Hub is the always-on customer brain, acting as a single decision authority selecting the right offer for each customer

• The bank plans to implement changes in multiple phases:

• Proof of concept is the first phase, to display a credit card offer on the U+ website by setting up the environment, business structure, Action, and Treatment for Next-Best-Action

• Engagement Policies is next, which adds conditions like eligibility, applicability, and suitability to qualify an offer, so customers only see relevant offers

• Contact policies use suppression rules to put offers on hold after certain outcomes, preventing over-exposure by limiting how many times a customer is exposed to the same Action

• Arbitration balances customer relevance with business priorities by assigning numerical values to Propensity, Context Weighting, Business Value, and Business Levers to determine the top offer

Next Best Action Designer

• The Next-Best-Action Designer guides through creating a Next-Best-Action strategy, providing personalized customer experiences across inbound, outbound, and paid channels

• Tabs at the top represent steps to define next best actions

• Taxonomy: Defines the business structure.

• Constraints: Implements channel limits

• Engagement Policy: Defines rules controlling offers to customers

• Arbitration: Configures action prioritization

• Channels: Configures where next best actions initiate

• The system uses these definitions to create a Next-Best-Action Strategy framework, leveraging best practices and AI Models

• The taxonomy tab defines the hierarchy of business issues and groups and creates and manages customer journeys

• You can define, manage, and view all strategy result properties and action properties, including system and custom properties, on the Properties tab

• Constraints specify outbound contact limits and limit overexposure

• Outbound channel limits restrict the number of outbound communications.

• Action limits restrict actions seen during interactions

• The Constraints tab defines suppression rules through a Contact Policy library Suppression or pausing prevents over-exposure to the same action

• Engagement policies define appropriate actions for customers

• Eligibility determines if a customer qualifies

• Applicability determines relevance at a specific time

• Suitability determines appropriateness for ethical reasons

• Contact Policies determine suppression of actions

• Arbitration determines prioritization of eligible actions

• Weighing factors include Propensity, Context weighting, Business value, and Business levers

• Propensity is the likelihood of a customer responding positively, calculated via AI

• Context weighting assigns weighting to context values within an Issue or Group

• Business value assigns a financial value to prioritize high-value actions

• Business levers accommodate ad hoc business priorities by specifying a weight for an action or group

• The final priority indicates the top action for the customer, which can be explored in the Customer Profile Viewer

• Customer Profile Viewer examines specific profile and behavioral data

• Next-Best-Action Designer delivers actions through inbound, outbound, and paid channels

• Channels can be enabled or disabled

• External real-time channels (website, call-center, mobile app) display Customer Decision Hub selected actions and a placeholder (real-time container) for content

• A trigger mechanism invokes a Next-Best-Action decisioning process

Defining and Managing Customer Actions

• Next-Best-Action Designer builds business issue/group hierarchies
• The goal is to organize a customer action under a specific business issue/group hierarchy and rename it to better reflect a business context

Action Hierarchy

• Next-best-action customer recommendations take many forms, such as an upsell offer, a retention offer, or a cross-sell

• Customer actions are actions the system can take based on interactions, including personalized messages, offers, recommendations, or other forms of customer engagement in contact center, mobile, or the web

• Each customer action has properties defining its characteristics, like images, price, benefits, titles etc.

• Customer actions apply to various business issues, forming a three-level hierarchy

• Business Issue: The purpose of the action you want to offer the customers.

• Group: Organizes actions logically.

• Action: An offer, such as a reward card or a fixed rate.

Managing Business Structure

• Next-Best-Action Designer builds business issue and group hierarchies, organizing customer interactions associated with a business issue and group.
• You can view and define new Issues and Groups that contribute actions to next-best-action decisioning on the Taxonomy tab
• You can add, remove, or create new Issues
• The issues marked blue are already active, and the deactivated issue is automatically removed from the business hierarchy

Creating Actions

• An action holds details about an offering like Start/End Date and Expected Revenue, backed by a decisioning proposition
• An action can represent a banner ad, retention offer, or service message
• Actions can be an in one of the following categories: Always-on or One-time actions.
• A short description of the new Action should be entered when creating a single Action, then select the Issue and Group
• Attributes distinguish one Action from another, and they are used to select the right Action for each customer
• In a Context, an Action can be associated and evaluated, in this instance, Customer is the primary context
• Then to save, follow the save button
• To view Actions within a certain Group, you can filter by Issue and Group
• Comma Separated Value (CSV) file files are useful for bulk Action creation

Renaming Actions

• Pega Customer Decision Hub uses the term ‘actions' to refer to messages delivered during a customer interaction
• Actions can be renamed with terms based on the business issue and product groups.
• Action landing page shows all created Actions and shows each configured Issue and Group filter
• Change the default naming convention in Next-Best-Action Designer within the Taxonomy tab

Presenting a Single Offer on the Web

• Focus is on real-time containers and displaying actions through Customer Decision Hub on real-time channels
• Focus is on Configuring Next-Best-Action Designer to select a single banner offer for website display
• Customer Decision Hub’s Next Best Action capability wants to display a banner offer on a account
• Real-time container functionality is used in implementation
• a real time is a placeholder for content for specific content

Creating and Configuring A Real-Time Container

• Create and configure the Real-time container on the Real-Time Artifacts landing page

• An external channel uses the identifier of real-time container when it requests Customer Decision hub

• Can change the identifier to the channel in desired environment

• Turn real-time containers ability to respond from channel on and off

• “Impression capture", allows the external channel to control how the Customer Decision Hub records

• Means that hub immediately retrieves

• “Captured by channel" Instead channels tell the hub to look where its time is

• Can select action flow or click only behavior

• Configure Next-Best-Action strategies associated

Presenting a Single Offer on the Web

• Next step focuses on configuring next-best action in single banner location
• Focus for U+Retail bank, and it is their intent to display it on their website

To implement, here are the following steps

1. Navigate to next best
2. Configure the defined action However in this scenario U+ bank is in charge of credit card offers With a treatment being added and selected Then a tile treatment that gives an image with an offer Select where the image is from And configure where the website offers.

• The real time container is added
• Configure from the business perspective that it is looking at
• Example: Customer and credit credit cards in this example

Defining Customer Engagement Policies

• Set of conditions such as suitability for offering to Customers

• Goal is to use Next-Best-Action Designer to define conditions Eligibility rules for actions such as only existing customer are considered or that you must be over 18 Applicability rules for what is offered based on the customer situation

• You specify three types of rules Eligibility and Suitability.

• Actions go through three phases of actions based on these rules • Finally actions go through the Arbitration stage to choose action to push to the customer

  • With action value and Business values

Defining Eligibility, Applicability and Suitability Rules

• Goal is to set engagement practices in all three rule categories, all found in designer next best action panel Two credit cards eligibility for both U+ Existing, and over 18 To be available for new customers, that are the minimum requirements

• The goal is for all not to be deemed suitable for everyone

• Rewards card will be considered only for good credit card users

• There are rules for each card group is eligible are considered

• You set different suitability variables

• If credit score is in range cards are displayed

Creating and Testing Personas

• Use next best analysis testing

• To review results from testing

• Test recent configured analysis in Customer Profile Viewer

• To show data Dedicated spacing is managing channel contact on personal management page

The is Three Category

• Input data manually

Persona from file when creating in bulk Existing customer, uses info from a customer in database In use case U+ Uses Troy Murphey, to test configuration It is best to use common profile names that can can categorize and reduce confusion

Then system populates customer attribute tree

The Next Category Channel,

• And is named as such, and on that page

Creating Personas And Using AI

• Ai is the method that is used on testing and results

Testing Engagement Policy Configurations and Use Cases,

• Here is how the customer receives exact expected offers for business requirements
• And the bank goals for the set cards

Two Persons

• Mature low risk, financially
• You and low risk financially and volunerable

Review questions on customer offers and engagement policies. Examines offer prioritization, applicability rules, and suitability within customer profile context. Focuses on strategic decision-making regarding customer engagement.