Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Discount or incentive
Reexamination Certificate
1999-09-16
2003-05-20
Gravini, Stephen (Department: 3622)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
Discount or incentive
Reexamination Certificate
active
06567786
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to a marketing system and method, and in particular, to a system and method for increasing the effectiveness of customer contact strategies.
BACKGROUND OF THE INVENTION
Direct marketing involves advertising to customers at a location other than the point of sale. Catalogs, first-class mail, telemarketing, and e-mail are some examples of direct marketing techniques that are currently utilized to promote the sale of goods or services.
Direct marketers today face challenges that are far different than those with which the industry contended during its explosive growth over the last twenty years. Among the problems of particular interest:
The percentage of households purchasing through the mail has been essentially flat since 1993.
The consumer base is becoming increasingly diverse and individualistic.
The average number of promotions received per household continues to climb.
The costs of advertising (and in particular, paper, postage and ink) has been steadily increasing and shows no sign of leveling off.
Consumers increasingly demand services such as the ability to place phone orders and expedited delivery as standard.
Increasingly, retail companies are adding direct marketing to their mix of marketing techniques. In addition, with the explosion of the internet and e-commerce, consumers are presented with increasingly attractive alternatives to mail for the direct purchase of goods and services in their homes.
In response to these changes, direct marketers have responded in a variety of ways. Many direct marketers have improved their targeting of recipients of direct marketing through automation. For example, automation has been achieved by programming computers to perform sophisticated statistical analysis and modeling, develop marketing databases, increase the sophistication of their predictive models, or enhance their current processes with leading edge marketing tools such as data mining. While these efforts have helped reduce the negative impact of the changing marketing atmosphere, the industry has not been able to improve the average response rate to direct marketing.
A commonly-used marketing technique is called the RFM (Recency, Frequency and Monetary Value) technique. PCT International Application No. PCT/US908/22613, published as International Publication No. WO 99/22328 (incorporated fully herein by reference) discloses a computer-implemented targeted marketing system which evaluates many factors, including the RFM factors, to determine a customer list to be used for sending marketing materials in connection with a single proposed promotion event. The RFM technique is based on the theory that the customers that are most likely to respond to a proposed direct marketing event (e.g., a mailing of an offer) are those that have most recently been customers (Recency), and that have frequently been repeat customers (Frequency), and that have purchased significant dollar amounts (Monetary Value). Existing customers are scored based on their characteristics related to each of these three criteria, and a customer with a high RFM score is considered a good target for the proposed marketing event under analysis. Based on the RFM scores, a specialized customer list is generated for a single proposed marketing event.
FIG. 1
portrays a “promotion flag” table which is used herein to explain the prior art RFM method of determining if a customer should receive a particular promotion “p.” RFM marketing techniques are a form of “natural selection.” All customers (depicted in numerical order by customer number in
FIG. 1
along the vertical axis as C
0
, C
1
, . . . , Cn) are sorted and ordered in a known manner from highest to lowest RFM score for a single promotion, and then a threshold line is drawn at a predetermined point based on expected sales and profitability. All customers on or above the threshold line are included in the current promotion, and all those below the line are excluded. In the promotion flag table of
FIG. 1
, a “1” indicates that a customer has scored at or above the threshold (i.e., that the customer is a “go” for inclusion in the promotion) and a “0” indicates that the customer scored below the threshold (i.e., that the customer is a “no-go” for inclusion in the promotion). Thus, high RFM customers are selected to become repeat targets while the lower RFM customers are targeted less or not at all.
Though the RFM technique achieves adequate results, since the focus is on only a single proposed marketing campaign at a time, a marketer ends up saturating its best customers with promotions, often sending out a subsequent and possibly redundant promotion before the previous promotion has been allowed to generate it's maximum return-on-investment (ROI). Further, low RFM customers, which may represent a major growth opportunity for the marketer, receive little or no attention.
The Applicant recognizes the desirability of a marketing method and system which analyzes customer preferences, needs, and historical tendencies, which looks at an entire promotional plan comprising a set of at least two proposed promotion events and takes into account the effects of a current promotion event on promotion events generated before, simultaneous with, and after the current promotion event.
SUMMARY OF THE INVENTION
The present invention takes a more global approach to marketing and focuses on the customer rather than any one particular promotion event, and factors in the effect on each other of promotion events to be implemented and already implemented. The present invention improves upon prior art marketing methods by analyzing customers based upon historical criteria; analyzing a promotional plan (a group of promotion events implemented or to be implemented over a particular time period) to determine the effect of each promotion event on the other promotion events in the promotional plan; and, based on this analysis, determining the optimal promotion stream (a specific subset of the promotional plan to be sent to customers or a group of similar customers) so as to maximize the ROI of the promotional plan as a whole.
According to the present invention, rather than focusing on an individual promotion event and determining which customers, based on historical data, meet a certain ROI criteria and excluding those who do not meet the criteria, the present invention focuses on a particular customer or customer group (called a class), and their ROI value with respect to an entire set of promotion events proposed to be implemental over a period of time. An analysis is also made of the impact of saturation and the “cannibalization” effect saturation may have on promotion events occurring before or after a particular promotion start date, or even occurring at the same time.
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Acti
Bibelnieks Eric
Bullock Mark
Crowder Harlan
Haydock Michael
Kugel Wayne
Doudnikoff Gregory M.
Gravini Stephen
Synnestvedt & Lechner LLP
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