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Q1.

MyCo, a telecom company, notices that when customers call to check on bill status, 80% of the time, they received the wrong offer promotion, leading to customer dissatisfaction. The company decides to boost customers' needs in the prioritization formula, to improve sales in the current quarter.

Which arbitration factor do you configure to implement the requirement?

AContext weighting

BBusiness weighting

CPropensity

DBusiness value

Answer: C

See the explanation below.

The arbitration factor is a parameter that allows you to adjust the weight of each factor in the prioritization expression, based on your business strategy and preferences. The arbitration factor is multiplied by the factor value to calculate the final priority score of each offer for each customer. If you want to boost customers' needs in the prioritization formula, you can increase the arbitration factor for the propensity, which is the factor that reflects the predicted customer behavior. The higher the arbitration factor for the propensity, the more influence it has on the priority score, making the offers that match customers' needs more likely to be selected and presented to the customer. Verified Reference: [Pega Decisioning Consultant | Pega Academy]

Q2.

You are the decisioning architect on an Al-powered one-to-one customer engagement implementation project. You are asked to design the next-best-action prioritization expression that balances the customer needs with the business objectives.

What factor do you consider in the prioritization expression?

APredicted customer behavior

BOffer eligibility

CCustomer contact policy

DOffer relevancy

Answer: A

See the explanation below.

The prioritization expression is a formula that calculates the priority score of each offer for each customer, based on various factors that reflect the customer needs and the business objectives. One of the most important factors is the predicted customer behavior, which is measured by the propensity. The propensity is a value that indicates how likely a customer is to accept an offer, based on their attributes and behaviors. The propensity is calculated by using predictive analytics models that learn from historical data and feedback. The higher the propensity, the higher the priority score, making the offer more relevant and valuable for the customer. Verified Reference: [Pega Decisioning Consultant | Pega Academy]

Q3.

MyCo, a telecom company, recently introduced a new mobile handset offer, MyFone 14 Pro, for its premium customers. As the bank has financial targets to meet, the business decides to boost the MyFone 14 Pro offer.

As a decisioning architect, how can you ensure that the MyFone 14 Pro offer is prioritized over other offers?

AIncrease the business weight of the MyFone 14 Pro offer.

BIncrease the starting propensity of the MyFone 14 Pro offer.

CIncrease the context weight of the MyFone 14 Pro offer.

DIncrease the business value of the MyFone 14 Pro offer.

Answer: A

See the explanation below.

The business weight is a parameter that allows you to manually adjust the priority of an offer based on your business objectives and preferences. The business weight is multiplied by the business value and the propensity to calculate the final priority score of an offer. A higher business weight means a higher priority score, making the offer more likely to be selected and presented to the customer. Therefore, if you want to boost an offer, you can increase its business weight. Verified Reference:Pega Decisioning Consultant | Pega Academy

Q4.

U+ Bank presents various credit card offers to its customers on its website. The bank uses AI to prioritize the offers according to customer behavior. With the introduction of the Gold credit card offer, the offer click-through propensity decreased to 0.42.

What does the decrease in the propensity value most likely indicate?

ASimilar customers do not qualify for the offer.

BSimilar customers show interest in the offer.

CSimilar customers purchase other offers.

DSimilar customers ignore the offer.

Answer: D

See the explanation below.

The propensity is a measure of how likely a customer is to accept an offer, based on their attributes and behaviors. The propensity is calculated by using predictive analytics models that learn from historical data and feedback. A low propensity value indicates that the offer is not relevant or attractive for the customer, and that similar customers have ignored or rejected the offer in the past. Therefore, if the offer click-through propensity decreased to 0.42, it most likely indicates that similar customers ignore the offer. Verified Reference:Pega Decisioning Consultant | Pega Academy

Q5.

U+ Bank implemented a customer journey for its customers. The journey consists of five stages. The bank observes that as customers progress through the journey, one customer entered the third stage of the journey, and then received an offer that is not included in any journey.

Which statement explains the cause of this behavior?

AThe bank implemented upweighting for the third stage.

BThe customer was not eligible for the last stage of the journey and the system presented an offer outside the journey.

CThe customer can be involved in only one active journey at a given moment.

DThe customer always receives the most relevant action, even if an action is not a part of any journey.

Answer: D

See the explanation below.

Pega Customer Decision Hub always selects and prioritizes the most relevant and valuable action for each customer at any given moment, regardless of whether the action is part of a journey or not. A journey is a way to group and organize actions that are related to a common business objective or customer need, but it does not override the Next-Best-Action strategy that determines the best action for each customer. Therefore, if a customer receives an offer that is not included in any journey, it means that the offer is more suitable and beneficial for the customer than any other offer in the journey. Verified Reference:Pega Decisioning Consultant | Pega Academy

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