Method and apparatus for internet customer retention

• US 20020046096A1
• Filed: 03/13/2001
• Published: 04/18/2002
• Est. Priority Date: 03/13/2000
• Status: Active Grant

• Current Assignee: Intellions, Inc.
• Original Assignee: Intellions, Inc.
• Inventors: Srinivasan, Kannan, Shamos, Michael I.
• Granted Patent: US 8,280,773 B2
• Time in Patent Office: Days
• US Class Current: 705/14
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0211 Determining the effectiveness of discounts or incentives
• CPC Class Codes: G06Q 30/0222 During e-commerce, i.e. online transactions
• CPC Class Codes: G06Q 30/0253 During e-commerce, i.e. online transactions
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

A method of dynamically optimizing customer retention for a web marketing site is provided. That method includes specifying a permissible defunct threshold, specifying a range of offers to be included in a set of promotions, determining a probability that a customer will become defunct in a predetermined period of time since the last interaction of that customer with the web site, and providing a promotion to a customer if the probability that the customer will become defunct in the predetermined period of time since the last interaction of that customer with the web site is greater than a predetermined threshold.

Claims

1. A method of dynamically optimizing customer retention for a web marketing site, comprising:

specifying a permissible defunct threshold;

specifying a range of offers to be included in a set of promotions;

determining a probability that a customer will become defunct in a predetermined period of time since the last interaction of that customer with the web site; and

providing a promotion to a customer if the probability that the customer will become defunct in the predetermined period of time since the last interaction of that customer with the web site is greater than a predetermined threshold.

2. The method of claim 1, further comprising segmenting the sample population based on a characteristic of the customers sampled.

3. The method of claim 2, wherein the characteristic is an amount that the customers spent at the web site in the past.

4. The method of claim 1, wherein the last interaction includes accessing the web site.

5. The method of claim 1, wherein the last interaction includes making a purchase from the web site.

6. The method of claim 1, further comprising maximizing profit by optimizing an amount of discount offered in the promotion.

7. The method of claim 6, wherein optimizing is performed continuously.

8. The method of claim 6,

wherein optimizing includes sampling responses received from customers that are offered promotions of varying amounts;

and

optimizing the promotion amount provided to other customers based on the optimum promotion amount discovered in the sample.

9. The method of claim 1, wherein data related to whether a customer has interfaced with the web site is stored in the database.

10. The method of claim 1, wherein an amount spent by a customer is stored in a database.

11. The method of claim 9, wherein a customer is segmented for random sampling based on the amount spent by that customer.