Online direct marketing system

1 . A method for creating marketing campaigns for a user in an integrated data processing environment comprising:

a. uploading customer transaction data from a user data processing machine to a hosting database;

b. analyzing the transaction data to provide a result that comprises at least one of predicted purchase probabilities, likely buyers, up-sell opportunities, cross-sell opportunities or potential defectors;

c. reporting the results of the analysis to the user;

d. from the results, selecting customers to target in a marketing campaign;

e. predicting at least one of anticipated response rate or revenue from the marketing campaign;

f. downloading a list of customers selected to be targeted in step (d);

g. collecting fees from the user based on the number of records downloaded in step (f).

2 . The method of claim 1 additionally comprising the steps of:

h. testing the targeting and offers to be used in the campaign;

i. sending one of (i) emails to targeted customers based on the analysis results, or (ii) sending direct mail to targeted customers based on the analysis results.

3 . The method of claim 2 additionally comprising the steps of:

j. uploading customer transaction data again after step (i);

k. analyzing customer transaction data resulting from the campaign; and

l. reporting a Return on Marketing Investment (ROMI).

4 . The method of claim 1 , wherein the step of analyzing the transaction data comprises:

h. determining a score for each customer using any one of several analytical methods including one or more of regression, RFM, genetic algorithms, or finite state machines;

i. predicting the probability of each customer in the customer population to buy each product or service in the set of products and services; and

j. segmenting the customers into groups based on their scores.

5 . The method of claim 1 , wherein the step of reporting the results comprises:

h. calculating a set of key performance indicators for dashboard display;

i. displaying a set of charts and graphs depicting the performance of individual customers; and

j. displaying a set of charts and graphs depicting the performance of the analyzed company as a whole.

6 . The method of claim 1 , wherein the step of selecting the customers to target in a marketing campaign comprises one or more of the following:

h. choosing a name for the marketing campaign;

i. choosing a type of service, where choices include up-sell, cross-sell, likely buyers; or customers at risk of defecting;

j. choosing products to sell in up-sell or cross-sell campaigns;

k. setting a purchase probability range so that targeted customers fall within the range;

l. selecting or suppressing groups of customers such as high or low ranking customers or customers in a particular marketing channel;

m. selecting or suppressing individual customers based on any or all of several other marketing metrics; and

n. setting a start date and duration for the marketing campaign so as to select customers whose metrics match the desired criteria during the campaign interval.

7 . The method of claim 1 , wherein the step of predicting response rate and revenue comprises:

h. using, as input data, transactions and segmentation of selected customers;

i. applying an automated response rate predictor; and

J. displaying the results in a web client.

8 . The method of claim 1 , wherein the step of collecting fees from users comprises:

h. setting up an account for each user;

i. collecting billing information;

j. counting the number of records downloaded in step (f);

k. multiplying the number of downloaded records by the per-record fee; and

l. charging the user's account or credit card for the download.

9 . The method of claim 1 , wherein the step of testing the targeting and offers comprises:

h. deciding whether to test targeting or offers;

i. selecting the experimental design (one factor at a time or multiple factors)

j. determining the size and composition of the test population in terms of their segmentation or other customer metrics;

k. suppressing one or more customers whose presence in the test population may distort results;

l. automatically subdividing the test population into various subgroups;

m. sending email or direct mail embodying the appropriate variations to subgrops members;

n. measuring the responses from each subgroup;

o. calculating the effects of the various factors using the methods in the associated patent application; and

p. displaying the results so users can select the best methods.

10 . The method of claim 1 , wherein the step of sending personalized emails comprises:

h. selecting email headers and sender names;

i. choosing email body copy from a set of preset or custom templates;

j. choosing the email campaign launch date; and

k. instructing an SMTP mail server to send the emails to the previously selected target customers.

11 . The method of claim 1 , wherein the step of sending personalized direct mail comprises:

h. choosing templates for print collateral copy; and

i. transmitting selected templates and selected customer records via an FTP server to Printing businesses for mailing.

12 . The method of claim 1 , wherein the step of analyzing the results of the campaign comprises:

h. calculating the actual response rate;

i. calculating the actual revenue generated by the targeted customers; and.

j. comparing the actual response rate and actual revenue with the predicted response rate and predicted revenue for the campaign.

13 . The method of claim 1 , wherein the step of reporting the Return on Marketing Investment comprises:

h. subtracting from the gross margin contribution of responding customers the several charges associated with selecting customers to target and generating email or direct mail to them.

14 . An online system for direct marketing comprising:

a. set of web servers that function to manage a direct marketing system, including handling messaging, and exchanging data files with Marketers, and the customers of Marketers;

b. set of database servers that function to manage transaction data and predictive analytics results for clients of the system;

c. set of analysis servers that function to analyze transaction data and predict purchase probabilities;

d. a central data store that functions to serve data to the various processing units of the system;

e. a job queue that functions to organize and prioritize a set of tasks necessary to operate the system; and

f. a controller that executes tasks in the job queue.

15 . The system of claim 14 , wherein the web servers include at least one of an HTTP server; FTP server; or SMTP server.

16 . The system of claim 14 , wherein the HTTP server manages a set of expert systems and wizards to plan, set up, and execute marketing campaigns.

17 . The system of claim 14 , wherein the FTP server manages external data transfers.

18 . The system of claim 14 , wherein the SMTP server manages email messaging.

19 . The system of claim 14 , wherein at least some of the analyses and data transfers are performed against a set of data stored in the central storage facility.

20 . The system of claim 14 , wherein the set of database servers includes an Administrative Database.

21 . The system of claim 20 , wherein the Administrative Database manages payment information and associated user privileges.

22 . The system of claim 14 , wherein the analysis servers execute code written in SQL to perform various functions which may include, among others, predicting customer behavior, identifying potential defectors, identifying likely buyers, identifying up-sell candidates, identifying cross-sell candidates, and calculating purchase probabilities.