DETERMINING BEST TIME TO REACH CUSTOMERS IN A MULTI-CHANNEL WORLD ENSURING RIGHT PARTY CONTACT AND INCREASING INTERACTION LIKELIHOOD

• US 20130060587A1
• Filed: 09/02/2011
• Published: 03/07/2013
• Est. Priority Date: 09/02/2011
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Dorai, Chitra, Bayrak, Halil, Bulbul, Ali A., Conser, Erik T., de Bergh, Guillaume, Veen, Alejandro
• Application Number:
  US13/224,757
• Publication Number:
  US 20130060587A1
• Time in Patent Office: Days
• US Class Current: 705/7.11
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

Estimating best time to contact a customer may include estimating a statistical model which computes a score for determining a successful contact with the customer for the time period based on a first set of historical customer contact data. A second set of historical customer contact data associated with at least one customer may be received and the score of a successful contact may be provided for the customer based on the second set of historical data and the estimated statistical model.

Claims

1. A method for predicting likelihood of reaching a customer in a time period, comprising:

receiving a first set of historical customer contact data;

estimating a statistical model which computes a score for determining a successful contact with the customer for the time period based on the first set of historical customer contact data;

receiving a second set of historical customer contact data associated with at least one customer; and

providing the score of a successful contact for said at least one customer based on the second set of historical data and the estimated statistical model.

2. The method of claim 1, wherein the first set of historical customer contact data includes at least a customer identifier, time period of contact, and an indicator variable recording whether the contact was successful.

3. The method of claim 2, wherein the indicator variable records a successful contact including, for a fax communication or text message, whether customers took a specific action within a first specified period of time, for E-Mails, whether the customers clicked on a link or responded to an email within a second specified period of time, for a phone call in a contact center, whether there has been a Right Party Contact or a Right Party Contact where an interaction lasted for at least a predetermined time length, for a letter, whether the customers called a number within or sent back a form within a third specified period of time, for an instant message, whether the customer responded within a fourth specified period of time.

4. The method of claim 1, wherein the statistical model includes an additive model that mixes overall baseline scores with customer-specific scores for successful contact in the time period.

5. The method of claim 4, wherein the additive model performs:

estimating a baseline score based on the first set of historical data;

estimating a customer-specific score based on the first set of historical data;

determining a weighted score based on the baseline score and the customer-specific score;

adjusting the determined weighted score with one or more additional factors; and

providing the score of a successful contact based on the adjusted weighted score.

6. The method of claim 5, where the estimating a baseline score includes computing a proportion of successful contacts for a given channel type in a given time slot using the first set of historical data.

7. The method of claim 5, wherein the estimating a baseline score includes computing a ratio of (a) sum of time-weighted successful contacts using a given channel type in a given time slot and (b) sum of time-weighted contact attempts using a given channel type in given time slot.

8. The method of claim 5, wherein the step of estimating a customer-specific score includes computing for the customer a proportion of successful contacts for a given channel type in a given time slot using the first set of historical data.

9. The method of claim 5, wherein the step of estimating customer-specific score includes computing for the customer using a given channel type in given time slot using the first set of historical data a ratio of (a) sum of time-weighted successful contacts and (b) sum of time-weighted contact attempts.

10. The method of claim 5, wherein the step of determining a weighted score includes:

if call history associated with the customer is available,

determining a weight for mixing the baseline score and the customer-specific score; and

computing the weighted score based on the mixing weight, the baseline score, and the customer-specific score,

and if no call history associated with the customer is available,

computing the weighted score as the baseline score.

11. The method of claim 5, wherein the adjusting step includes adjusting with at least one overall inbound contact score adjustment and adjusting with at least one inbound contact score adjustment associated with a selected time slot.

12. The method of claim 1, wherein the step of estimating a statistical model includes:

processing the first set of historical customer contact data, by one or more of aggregation, transformation, categorization, or combinations thereof in order to generate a set of model features; and

estimating coefficients of a relationship between the model features and a response variable, the response variable defined as the indicator variable recording whether the contact was successful.

13. The method of claim 12, wherein the model features include total contact time per time period for each customer.

14. The method of claim 12, wherein the processing of the first set of historical customer contact data includes:

aggregating contact time per time period for each customer if a contact method is by phone;

aggregating total count of contacts if the contact method is email;

transforming the first set of historical contact data by a log, power, or identity transform;

categorizing based on channel type such as home phone, work phone, cell phone, other phone, if the contact method is by phone.

15. The method of claim 1, wherein the step of providing the score of a successful contact includes:

processing the second set of historical customer contact data by one or more of aggregation, transformation, categorization, or combinations thereof in order to generate a set of model features;

providing the score of a successful contact for said at least one customer based on the set of model features and the estimated statistical model.

16. A system for predicting likelihood of contacting a customer in a time period, comprising:

a processor;

a statistical model operable to run on the processor, the statistical model estimated based on a first set of historical customer contact data to compute a score for determining a successful contact with the customer for the time period;

a prediction module operable to receive a second set of historical customer contact data associated with at least one customer, and provide the score of a successful contact for said at least one customer based on the second set of historical data and the estimated statistical model.

17. The system of claim 16, wherein the first set of historical customer contact data includes at least a customer identifier, time period of contact, and an indicator variable recording whether the contact was successful.

18. The system of claim 17, wherein the indicator variable records a successful contact including, for a fax communication or text message, whether customers took a specific action within a first specified period of time, for E-Mails, whether the customers clicked on a link or responded to an email within a second specified period of time, for a phone call in a contact center, whether there has been a Right Party Contact or a Right Party Contact where an interaction lasted for at least a predetermined time length, for a letter, whether the customers called a number within or sent back a form within a third specified period of time, for an instant message, whether the customer responded within a fourth specified period of time.

19. The system of claim 16, wherein the statistical model includes an additive model that mixes overall baseline scores with customer-specific scores for successful contact in the time period.

20. The system of claim 19, wherein the additive model performs:

estimating a baseline score based on the first set of historical data;

estimating a customer-specific score based on the first set of historical data;

determining a weighted score based on the baseline score and the customer-specific score;

adjusting the determined weighted score with one or more additional factors; and

providing the score of a successful contact based on the adjusted weighted score.

21. The system of claim 20, where the estimating a baseline score includes computing a proportion of successful contacts for a given channel type in a given time slot using the first set of historical data.

22. A computer readable storage medium storing a program of instructions executable by a machine to perform a method of predicting likelihood of contacting a customer in a time period, comprising:

receiving a first set of historical customer contact data;

estimating a statistical model which computes a score for determining a successful contact with the customer for the time period based on the first set of historical customer contact data;

receiving a second set of historical customer contact data associated with at least one customer; and

providing the score of a successful contact for said at least one customer based on the second set of historical data and the estimated statistical model.

23. The computer readable storage medium of claim 22, wherein the first set of historical customer contact data includes at least a customer identifier, time period of contact, and an indicator variable recording whether the contact was successful.

24. The computer readable storage medium of claim 22, wherein the indicator variable records a successful contact including, for a fax communication or text message, whether customers took a specific action within a first specified period of time, for E-Mails, whether the customers clicked on a link or responded to an email within a second specified period of time, for a phone call in a contact center, whether there has been a Right Party Contact or a Right Party Contact where an interaction lasted for at least a predetermined time length, for a letter, whether the customers called a number within or sent back a form within a third specified period of time, for an instant message, whether the customer responded within a fourth specified period of time.

25. The computer readable storage medium of claim 22, wherein the statistical model includes an additive model that mixes overall baseline scores with customer-specific scores for successful contact in the time period, wherein the additive model performs:

estimating a baseline score based on the first set of historical data;

estimating a customer-specific score based on the first set of historical data;

determining a weighted score based on the baseline score and the customer-specific score;

adjusting the determined weighted score with one or more additional factors; and

providing the score of a successful contact based on the adjusted weighted score.