Customer Relationship Capacity Planning

Patent metadata

Field	Value
Publication number	US-2016019481-A1
Application number	US-201414332283-A
Country	US
Kind code	A1
Filing date	Jul 15, 2014
Priority date	Jul 15, 2014
Publication date	Jan 21, 2016
Grant date	—

Abstract

Methods and apparatuses, including computer program products, are described for customer relationship capacity planning. A computing device receives (i) financial plan attributes associated with a financial plan of a customer and (ii) personality characteristics associated with the customer. The computing device determines a relationship complexity score associated with the customer based upon the financial plan attributes and the personality characteristics. The computing device determines a target workload value for customer service managers of the financial services entity based upon the relationship complexity score for a plurality of customers and a past number of relationship service hours associated with the plurality of customers. The computing device allocates the customer to a customer service manager based upon the target workload value and a current workload of the customer service manager. The computing device updates an allocation table that contains information relating to the allocation of customers to customer service managers.

First claim

1 . A computerized method for customer relationship capacity planning by a financial services entity, the method comprising:
receiving, by a computing device, (i) financial plan attribute data associated with a financial plan of each of a plurality of potential customers and a plurality of newly-acquired customers, wherein the financial plan attribute data relates to scope of assets and feature set of the financial plan, and (ii) personality characteristic data associated with the customer, wherein the personality characteristic data relates to a level of interaction requested by the customer and a structure of the customer's employees; aggregating, by the computing device, the financial plan attribute data for the plurality of potential customers and the plurality of newly-acquired customers into a binned memory structure comprising a plurality of bin storage locations, wherein the plurality of potential customers and the plurality of newly-acquired customers are grouped by at least a financial plan asset value before being allocated to a bin storage location and wherein each bin storage location contains data for customers with similar financial plan asset values; assigning, by the computing device, an average number of hours spent in a previous time period to service existing customers having similar financial plan attribute data to the financial plan attribute data for the customers in the binned memory structure; determining, by the computing device, a relationship complexity score associated with each of the potential customers and the plurality of newly-acquired customers based upon the financial plan attribute data, the personality characteristic data for each customer, and the average number of hours assigned to the customer's bin storage location; determining, by the computing device, a current workload value for a customer service manager of the financial services entity based upon the relationship complexity scores for each of a plurality of existing customers already allocated to the customer service manager, the current workload value representing a level of effort from the customer service manager to provide service to the plurality of existing customers already allocated to the customer service manager; determining, by the computing device, a target workload value for the customer service manager based upon relationship complexity scores for each of the existing customers of the financial services entity and a past number of relationship service hours spent in a previous time period to service each of the existing customers; allocating, by the computing device, a portion of the potential customers and the newly-acquired customers to the customer service manager based upon the current workload value and the target workload value for the customer service manager, including
determining, by the computing device, a customer satisfaction value for each existing customer already assigned to the customer service manager,
aggregating, by the computing device, the customer satisfaction value for each existing customer into a customer satisfaction score for the customer service manager,
displaying, by the computing device, a graph of a comparison between current workload values for a plurality of customer service managers and customer satisfaction scores for the plurality of customer service managers including placing one or more visual indicators on the graph to isolate data points corresponding to one or more customer service managers that have a customer satisfaction score greater than a predetermined threshold and a current workload value that is less than or equal to the target workload value, and
allocating, by the computing device, the portion of the potential customers and the newly-acquired customers to the customer service manager if the data point corresponding to the customer service manager is within one of the visual indicators on the graph; and
updating, by the computing device, an allocation table that contains information relating to the allocation of customers to customer service managers.

2 . The method of claim 1 , wherein the step of determining a relationship complexity score further comprises assigning, by the computing device, the customer to a cluster based upon the financial plan attribute data including the scope of assets and the feature set of the financial plan.

3 . The method of claim 2 , further comprising analyzing, by the computing device, the financial plan attribute data associated with each of the customers in the cluster to identify similarities among the customers.

4 . The method of claim 1 , wherein the step of determining a relationship complexity score further comprises assigning, by the computing device, a weight value to each of the financial plan attribute data and the personality characteristic data.

5 . The method of claim 1 , wherein the past number of relationship service hours is associated with a predetermined service period.

6 - 7 . (canceled)

8 . The method of claim 1 , further comprising:
determining, by the computing device, a tolerance associated with the target workload value; and allocating, by the computing device, the portion of the potential customers and the newly-acquired customers to the customer service manager if (i) the relationship complexity scores for the portion of the potential customers and the newly-acquired customers are greater than the difference between the current workload value for the customer service manager and the target workload value for the customer service manager and (ii) the difference between the current workload value for the customer service manager and the target workload value for the customer service manager is less than or equal to the tolerance.

9 . (canceled)

10 . The method of claim 1 , further comprising determining, by the computing device, a manager performance metric based upon the customer satisfaction score for the customer service manager, the target workload value for the customer service manager, and the current workload value for the customer service manager.

11 . The method of claim 1 , wherein the personality characteristic data is based upon survey responses from the customer.

12 . A system for customer relationship capacity planning by a financial services entity, the system comprising a computing device configured to:
receive (i) financial plan attributes associated with a financial plan of each of a plurality of potential customers and a plurality of newly-acquired customers, wherein the financial plan attributes relate to scope of assets and feature set of the financial plan, and (ii) personality characteristics associated with the customer, wherein the personality characteristics relate to a level of interaction requested by the customer and a structure of the customer's employees; aggregate the financial plan attribute data for the plurality of potential customers and the plurality of newly-acquired customers into a binned memory structure comprising a plurality of bin storage locations, wherein the plurality of potential customers and the plurality of newly-acquired customers are grouped by at least a financial plan asset value before being allocated to a bin storage location and wherein each bin storage location contains data for customers with similar financial plan asset values; assign an average number of hours spent in a previous time period to service existing customers having similar financial plan attribute data to the financial plan attribute data for the customers in the binned memory structure; determine a relationship complexity score associated with each of the potential customers and the plurality of newly-acquired customers based upon the financial pl

Assignees

• Fmr Llc

Inventors

• Roy Bidhan

Classifications

• G06Q30/01

  Customer relationship services · CPC title

• G06Q10/0639 Primary

  Performance analysis of employees; Performance analysis of enterprise or organisation operations · CPC title