Systems And Methods For Probing Customers And Making Offers In An Interactive Setting
AssigneeInternational Business Machines Corporation
InventorsRohit M. Lotlikar, Pradeep N. Pachigolla, Virendra K. Varshneya, Sneha S. Chaudhari
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Abstract
Methods and systems for recommending a product to a customer based on the customer's responses to a prioritized list of questions. A list of questions to ask the customer is created based on stored customer identifiers. The list of questions is priorities based on a pre-existing propensity score associated with the customer, and the agent asks the ranked questions. Based on the response of the customer, the propensity score and/or the list of questions is updated, and the agent is presented with a recommended product to suggest to the customer.
Claims21
A method for recommending a product to a customer based on the customer's responses to a prioritized question, the method comprising the steps of:
- providing a computer having a database stored in the memory thereof and in which data is stored, said data representing a bank of questions, identifiers for a plurality of customers, and pre-existing propensity scores associated with the plurality of customers;
- establishing communication with said customer;
- computing a list of questions for the customer based on one of said identifiers for the customer, wherein said list comprises a predetermined number of questions;
- prioritizing said list of questions based on said pre-existing propensity score for the customer;
- asking said customer at least one of said questions based on said prioritization;
- entering in the computer a response of the customer to the at least one of said questions;
- electronically updating said propensity score for the customer based on said entered response;
- and
- recommending a product to the customer based on said updated propensity score.
The method of claim 6, wherein said prioritizing step comprises prioritizing said list of questions based on the rank associated with each question in said list of questions.
A non-transitory computer-readable storage medium containing program code comprising:
- program code for computing a list of questions for the customer based on at least one customer identifier, said at least one customer identifier stored in a database, wherein said list comprises a predetermined number of questions;
- program code for prioritizing said list of questions based on said pre-existing propensity score for the customer;
- program code for receiving an entered response of the customer to at least one of said questions;
- program code for electronically updating said propensity score for the customer based on said entered response;
- program code for identifying the product to be recommended to the customer based on said updated propensity score.
A system for recommending a product to a customer based on the customer's responses to a prioritized question, the system comprising:
- a computer having an associated database in which data is stored, said data representing a bank of questions, identifiers for a plurality of customers, and pre-existing propensity scores associated with at least some of said plurality of customers;
- a communications protocol adapted to communicate with said customer;
- a question selection module, said question selection module adapted to compute a list of questions for the customer based on one of said identifiers for the customer;
- a propensity scoring module, said propensity scoring module adapted to prioritize said list of questions based on a pre-existing propensity associated with the customer, and further adapted to update the propensity score for the customer based;
- a user interface associated with said computer, wherein said user interface is adapted to present to an agent said list of questions for the customer and to receive a response of the customer to at least one of said list of questions, and wherein said user interface is further adapted to present to said agent a product to be recommended to said customer based on an updated propensity score.
Dependencies are inferred from the claim text.