WO2001088799A1

WO2001088799A1 - Business growth optimization system through direct mail communications

Info

Publication number: WO2001088799A1
Application number: PCT/NZ2001/000091
Authority: WO
Inventors: Adrienne Barbara Bullock
Original assignee: Adrienne Barbara Bullock
Priority date: 2000-05-17
Filing date: 2001-05-15
Publication date: 2001-11-22
Also published as: CA2409396A1; AU2001260839A1

Abstract

A method, system, devices hardware and software processes for business optimization through relationships enhancement by use of greetings cards, e-cards and the like direct mail communications which comprises the collection, identification, tagging, mailing, measurement, correlation and analysis of customer data and/or employee in relation to direct mail (including E-mail) to achieve a particular desired end result.

Description

BUSINESS GROWTH OPTIMIZATION SYSTEM THROUGH DIRECT MAIL COMMUNICATIONS

FIELD OF THE INVENTION

This invention relates generally to a system and process of performance and profit optimization of a business. More particularly it relates to a process for business optimization through relationships enhancement and or motivational messages by use of Greeting Cards and the like direct mail communications. It is based upon the hypothesis that profit maximization can be achieved by measuring and controlling and optimizing business relationships through judicious use of cards such as greeting cards, Thank You notes etc.

BACKGROUND:

Although historically the use of greeting cards, electronic cards (E-Cards), talking cards and postcards has been limited to personal use, many businesses are now finding that cards are also a very effective tool to build customer loyalty and motivate people to take important next steps in business. Modern business practice recognizes the importance of customer relationships, customer loyalty and referral business to grow their business. This invention empowers a business to implement customer relationship (including relationships with employees, stock holders etc) strategies and improve results in many different situations. The purchasing decisions of customers/clients are then shifted away from simple cost versus features analysis of a product or service, to choosing a supplier on the strength of the relationship and understanding between the parties involved.

SUMMARY

The present invention is a system and process including hardware and software for achieving certain Desired End Results. It comprises techniques for collecting, identifying and measuring customer, business and sales related information, so that a business can identify opportunities for improvement. Each business then matches these opportunities to a desired end result (DER) strategy. Once a DER strategy has been implemented, the business then records, measures, analyses and tabulates the results to identify the effectiveness of that DER strategy in achieving the desired end result. This invention includes correlating, tagging, and analyzing client/customer/employee transactional and/or behavioral data for direct mail such as postcards, electronic cards (cards), talking cards and/or greeting cards, both before and after each desired end result (DER) strategy is implemented. The 7 step process is described in full later. PRIOR ART

A prior art search was conducted. Following are typical examples of the closest U S patent as prior art arranged in the reverse chronological order for ready reference of the reader.

07. United States Utility Patent 5,991,735 granted to Thomas Gerace on November 23, 1999 for "Computer Program Apparatus for Determining Behavioral Profile of a Computer User"

06. United States Utility Patent 5,893,075 issued to Plainfield et al on August 6, 1999 for "Interactive System and Method for Surveying and Targeting Customers . "

05. United States Utility Patent 5,857,175 bestowed upon Day et al on January 5, 1999 for "System and Method for Offering Targeted Discounts to Customers . "

04. United States Utility Patent 5,687,322 published in the names of Deaton et al on November 11, 1997 for "Method and System for Selective Incentive Poin -of-Sale Marketing in response to Customer Shopping Histories . "

03. United States Utility Patent 5,612,527 presented to Victor Ovadia on March 18, 1997. for "Discount Offer Redemption System and Method"

02. United States Utility Patent 5,515,270 earned by Lee einblatt on May 7, 1996 for "Technique for Correlating Purchasing Behavior of a Consumer to Advertisements" 01. United States Utility Patent 4908,761 honorably given to Roland Tai on March 13, 1990 for "System for Identifying Heavy Product Purchasers who Regularly Use Manufacturer's Purchase Incentives and Predicting Consumer Promotional Behavior Response Patterns."

OBJECTIVES

Unfortunately none of The prior art devices singly or even in combination provide for all of the objectives as established by the inventor for this system as enumerated below.

01. It is an objective of this invention to provide methods, devices and system for profit optimization of a business through relationships enhancement and/or motivational messages via direct mail communications such as e-cards, greeting cards, thank you notes, audio-visual cards etc.

02. Another objective of this invention is to provide a method for measuring impact on a business before and after the implementation of direct mail communications of this system.

03. Another objective of this invention is to avoid sub- optimization.

04. Another objective of this invention is to reduce or eliminate all non-value added or marginal value added steps so as to reduce the life cycle costs . 05. Another objective of this invention is to take the long term view in implementation of this invention'.

06. Another objective of this invention is to utilize all types of direct mail communications including but not limited to postcards, electronic cards (cards), talking cards thank you cards and/or greeting cards designed to increase trust, make people feel special and/or motivate people to take next steps in business.

07. Another objective of this invention is to generate opportunities, trends and or weaknesses of a business.

08. Another objective of this invention is to match these identified opportunities, trends and/or weaknesses with a specific DER strategy( ies ) which have been designed to solve and/or improve these identified issues.

09. Another objective of this invention is that its design is simple and even elegant.

10. Another objective of this invention is that its use is intuitive which requires no further training.

11. Another objective of this invention is that it can measure and compare the results generated after a specific DER strateg (ies ) has been implemented.

12. Another objective of this invention is to assist staff within a business (es) prepare management report(s) and/or presentations to management to identify opportunities, trends and/or weaknesses within a business. 13. Another objective of this invention is to assist staff within a business (es) prepare management report(s) and/or presentations to management to identify a strategy designed to improve these identified criteria and then to report changes in these criteria after a targeted DER strategy(ies ) has been implemented.

14. Another objective of this invention is that it enhances personal relationships with all types of business population including customers, clients, prospects, employees, stock holders, suppliers, distributions, retailers etc.

15. Another objective of this invention is to provide for a fast response time (almost real time) so as to minimize the delay between opportunity action and results .

16. Another objective of this invention is that it be reliable such that it practically never fails and requires little or no maintenance.

17. Another objective of this invention is that it be easy to follow with on-line documentation.

18. Another objective of this invention is that it meet all federal, state, local and other private standards guidelines, regulations and recommendations with respect to safety, environment, energy consumption.

19. Another objective of this invention is that the software component of this system be easily upgrade-able. 20. Another objective of this invention is that it be suitable for promotional give aways complete with message of the sponsor.

21. Another objective of this invention is that it be capable of multiple concurrent distribution.

22. Another objective of this invention is that it be suitable for business system profit configuration management.

23. Another objective of this invention is that it can measure and include the effect of intangibles such as direct mail communications on the bottom line of a business.

24. Another objective of this invention is to create a fully customer driven strategy for long term profit maximization.

25. Other objectives of this invention reside in its simplicity, elegance of design, ease of manufacture, service and use and even aesthetics as will become apparent from the following brief description of the drawings and the detailed description of the concept embodiment. Prior art embodiments may also lack the elegance of design of this invention in terms of compact size, fewer procedural steps.

BRIEF DESCRIPTION OF THE DRAWINGS

The objects, features and advantages of the present invention and its application will be more readily appreciated when read in conjunction with the accompanying drawing, in which: a) FIG 1 is a flow diagram of the 7 step process of this invention. b) FIG 2 is a flow chart showing review and analysis of key data to identify opportunities for mail out in greater detail. c) FIG 3 shows interface flow chart from mail out to DERs . d) FIG. 4 shows the interface between the mailouts and the desired end results. e) FIG. 5 delineates the interface between DER (Desired End Result) , KPI (Key Performance Indicators) and the results oriented reports . f) FIG. 6 shows the essential attributes of a prior art applications software computer program in order to use optimize the impact of this invention. g) FIG. 7 shows the flow-chart for evaluation of prior art application software (such as accounting, spreadsheet, customer, management, database) capabilities to record, measure, correlate and analyze data for results oriented reports . DETAILED DESCRIPTION OF THE BEST MODE PREFERRED EMBODIMENT

As shown in the drawings wherein like numerals represent like parts throughout the several views, there is generally disclosed in Figure 1 a 7 step process of this invention which entails many different criteria within each step which can potentially be identified and analyzed. Businesses can choose to apply any parts of this invention to their business (es) as they feel appropriate and/or beneficial, on a case by case basis. The seven steps are:

1. A diagnostic analysis of key data. Each business extracts, reviews and analyses current relevant key data to identify opportunities, trends and/or weaknesses.

2. Matching opportunities, trends and/or weaknesses (identified in step one) to specifically chosen DER strateg (ies) designed to improve the data analyzed.

3. Evaluating existing software (eg accounting, spreadsheet, customer management, database) capabilities to record, measure, correlate and analyze required data, and then tabulate this information into report format(s).

4. Selecting and/or setup and label appropriate records and/or fields in the application program to record, store, tag, import/export and sort the required data for each desired end result (DER) mail-out(s). 5. Send the DER mail-out to tagged individuals, group(s) or sub group(s) and record behavioral^' and transactional results against each record, group and/or subgroup in the application program after each DER mail-out.

6. Extract, compile, calculate and tabulate data to generate results oriented reports for each desired end result (DER) mail-out.

7. Evaluate the reports generated for each DER mail-out in step six and then use this knowledge to manage that business ( es ) . The 7 steps may be decreased, increased or regrouped without deviating from the spirit of the inventipn.

Over the seven steps identified above, this invention identifies and targets specific individuals and/or groups of individuals within a database, for a specific DER mail-out strategy and then determines the effectiveness of that piece (or pieces) of DER mail in generating results, including as compared to other methods . These results can then be compared to the cost of the mail-out and/or other data (such as before and after the mail-out) to determine the effectiveness of each mail-out in achieving the desired end result.

The process also entails measuring the results generated after a specific DER strategy(ies ) has been implemented and then comparing these results against: (i) industry benchmarks, and/or

(ii) previous data from that business (es) before a DER strategy(ies) was implemented, and/or

(iii). data from alternative strategy(ies) , and/or

(iv). data from other businesses, and/or

(v) the cost of implementing each DER strategy(ies )

FIG 2 is a flow chart showing review and analysis of customer data to identify trends and/or opportunities for mail out in greater detail. FIG 3 shows interface flow chart from mail out to DERs . FIG. 4 shows the interface between the mailouts and the desired end results. FIG. 5 delineates the interface between DER (Desired End Result) , KPI (Key Performance Indicators) and the results oriented reports.

FIG. 6 shows the essential attributes of a prior art applications software computer program in order to use optimize the impact of this invention.

FIG. 7 shows the flow-chart for evaluation of prior art application software (such as accounting, spreadsheet, customer management, database) capabilities to record, measure, correlate and analyze data for results oriented reports .Reference is made to various types of data in this application. Some of the data types used- in this application include:

1) Key data (KD) which includes, core basic contact data, customer data, employee data and business data.

2) Evaluation data (ED)

3) KPI (Key Performance Indicator) data

4) DER (Desired End Result) data

As stated earlier, greeting cards and postcards are a great way to nurture customer or client relationships, but businesses also need to know how effective each mail campaign is in generating results . This invention provides a method of business to solve this issue.

STEP ONE

A diagnostic analysis of key data. Each business extracts, reviews and analyses current relevant key data to identify opportunities, trends and/or weaknesses. Extraction of data includes gathering/reviewing said information from data collecting media and/or sources (including CD, DVD and/or computer software) as well as asking people questions to gather and record said information. Extraction and review of current key data can include customer related (CR), business specific (BS), employee related (ER) or core data (CD) as follows : a) Customer related data, such as:

(i) Total annual $ sales made to all customers and/or groups of customers within the past year(s) = ($ sales total before)

(ii) Total annual $ sales made to each customer within the past year(s) = ($ individual sales before)

(iii) The total number • of customers (and/or groups of customers) of each business (es) per annum = (total # customers before)

(iv) The frequency or number of times sales were made to each customer by a business (es) within the past year(s) = (# sales before)

(v) The average sales $ per customer per annum, being the ($ sales total before) divided by the (total # customers before), by individual, group and/or sub group = (ave $ sales before) .

(vi) The average number of times a customer (and/or groups of customers) purchases goods and/or services from a business per annum, being the sum total (# sales before) for all customers divided by the (total # customers before) in that sample in that year = (ave # sales before)

.(vii) The number of customers and/or groups of customers who have not paid their invoice(s) in full and/or part thereof within a specified time frame = (# customers unpaid before) (viii) The average number of customers and/or groups of customers who have not paid their invoice(s) in full and/or part thereof within a specified time frame = (ave # customers unpaid before) = (# customers unpaid before) divided by the number of customers in that sample.

(ix) The total dollar value of invoices that remain unpaid in full and/or part thereof within a specified time frame = ($ unpaid before)

(x) The percentage of total invoiced customers who have not paid their invoice(s) either partially and/or in full within a specified time frame = (% customers unpaid before) = (# customers unpaid before) multiplied by 100 and divided by (total # customers before)

(xi) The number of customers and/or groups of customers who have paid their invoice(s) in full and/or part thereof within a specified time frame = (# customers paid before)

(xii) The percentage of total invoiced customers who have paid their invoice(s) either partially and/or in full within a specified time frame = (% customers paid before) = (# customers paid before) multiplied by 100 and divided by (total # customers before)

(xiii) The number of days within a specified time frame that invoiced customers have taken to pay for goods and/or services which have been invoiced by a business, calculated from the date each and every invoice was sent to those invoiced customers through to the date each customer actually pays for said goods and/or services purchased from that business. = (# days taken before)

(xiv) The average number of days that invoiced customers, who have subsequently paid their outstanding invoice(s), have taken to pay these previously outstanding invoices = (ave # unpaid days). Calculate this (both by individual and/or by group) for a specified time frame, by taking the total (# days taken before) for all invoiced customers within a specified time frame who have subsequently paid their invoice(s), divided by the number of customers in that sample

(xv) the total number of new customers, prospective customers and/or entities referred by customers and/or business associates to a business within the past year = (# referred before)

(xvi) (# referred new customers before) = the total number of referred new customers gained by a business (es) within the past year

(xvii) The total number of customers and/or business associates who have referred a prospective customer(s), customer(s) and/or entities to a business within the past year(s) = (# customers who have referred before), and/or (xviii) (ave % customers who refer before) = (# customers who have referred before) multiplied by 100 and then divided by [(total # customers before) minus (# referred new customers before)] = the percentage of customers and/or business associates who have referred customers and/or prospective customers to a business within the past year(s)

(xix) The sum total number of times per annum that every customer and/or business associate who has referred a prospective customer(s) and/or new customer(s) to a business within the past year(s), actually does refer prospective customers and/or new customers to that business within the past year(s) before any DER mail-out to them = (# times referred before)

(xx) The average number of times customers who refer new customers and/or prospective customers to a business each year, actually do refer those said prospective customers and/or new customer(s) over the past year = (# times referred before) divided by (# customers who refer before) in that same year = (ave # times referred before)

(xxi) . The total $ sales made by a business to referred new customers and/or entities in the past year = ($ sales to referred before)

(xxii) (ave $ sales to referrals before) = ($ sales to referred before) divided by (# referred before).

NOTE: This ratio gives the average dollar value of sales made to each referred customer within the past year(s) (xxiii) the number of years (or part thereof) that each customer has continued to purchase goods and/or services from a business within a specified time frame= (# years loyal before)

(xxiv) the total number of years (or part thereof) that every customer has continued to purchase goods and/or services from a business within a specified time frame = (total # years loyal before)

(xxv) the average number of years (or part thereof) that customers have continued to purchase goods and/or services from a business within a specified time frame = (ave # years loyal before) = (total # years loyal before) divided by the total number of customers in that sample

(xxvi) The total number of customer complaints received annually, differentiated into groups as appropriate for example the ratio between resolved and unresolved complaints = (# complaints before and after)

(xxvii) The current number of sales a business expects to make to a customer or group of customer(s) per year = (ENS)

(xxviii) Total $ sales invoiced by a business (es) within the past year(s) = ($ total invoiced before)

(xxix) The total number of invoices issued by a business (es) within the past year(s) = (# invoices issued before) (xxx) The average $ sales per annum, being the ($ total invoiced before) divided by the (# invoices issued before), by individual, group and/or sub group = (ave $ sales invoiced before) .

(xxxi) The current gross profit margin per sale = (ave $ sales value invoiced before) less the average $ value of direct costs attributable to a sale = (MPS)

(xxxii) The current expected number of years (and/or parts thereof) that a business would expect a customer to continue purchasing goods and/or services from that business, based on previous trends and future predictions = (ENY)

(xxxiii) The current lifetime value of a customer = (LTV) = (MPS) x (ENS) x (ENY) For example, if (MPS) = $10 and (ENS) = 4 times per year and (ENY) = 3 years, then LTV = $10 x (4x3) = $120 Note that LTV can also be based on the net profit margin per sales (instead of gross profit margin per sales) if a business prefers.

(xxxiv) The total number of customers who had previously purchased goods and/or services from a business(es) , but have not purchased goods and/or services from that same business (es) within the past year(s) = (# not purchased before) (xxxv) The average percentage of customers who had previously purchased goods and/or • services from a business (es ) , but have not purchased goods and/or services from that same business (es) within the past year(s) = (ave % not purchased before) = (# not purchased before) multiplied by 100 and then divided by (total # customers before) at that time

(xxxvi) The average number of days it takes for a prospective customer, who then becomes a customer by purchasing of goods and/or services from a business, to become a customer. ' First, identify the prospective customers who subsequently purchased from a business and therefore became customers. Next, add up the total number of days each one of these customers took to purchase, from the date of first contact with the business to the date a sale was made to them. Then take the sum total of all these days for these customers to purchase and then divide this by the number of customers in that sample, = (ave # days to purchase before).

(xxxvii) The current annual $ sales to customers, who had previously not purchased goods and/or services from that business in the year prior, but have now been reactivated and/or converted into current customers in this year = ( $ converted sales) . (xxxviii) The percentage of total annual $ sales, which is attributed to sales made to customers who had previously not purchased goods and/or services from that business in the year prior, but have now been reactivated and/or converted into current customers in the current year = ( % converted sales). This is calculated by taking ($ converted sales), multiplied by 100 and then divided by ($ sales total before) at that time

(xxxix) The annual number of sales to customers, who had previously not purchased goods and/or services from that business in the year prior, but have now been reactivated and/or converted into current customers in this year = (# converted sales)

(xl) (# converted customers before) = the total number of new customers in a given time frame who were prospective customers who had not purchased goods and/or services from a that business (es) within the past year, but have now purchased goods and/or services from a business

(xli) . (% conversion before) = the percentage of prospective customers in a given time frame who had not purchased goods and/or services from a business (es) within the past year, but have subsequently purchase goods and/or services from a business = (# converted customers before) multiplied by 100 and then divided by total number of prospective customers at that time. (xlii) The conversion rate, being the number of prospective customers (and/or sample number of prospective customers) who subsequently choose to purchase goods and/or services from a business, as compared to the total number of prospective customers approached by a business (in that sample) = (conversion before)

(xliii) The total number of visitors who visit a website within a specified time frame before DER #1 mail-out (s) = (# visitors before)

(xliv) The number of times each visitor visits a website within a specified time frame before DER #7 mail-out (s) = (# times visited before)

(xlv) (total # times visited before) = add up the (# times visited before DER #7) for all visitors

(xlvi) The average number of times each visitor visits a website within a specified time frame before DER #7 mail- out (s) = (ave # times visits before) = (total # times visited before DER #7) divided by (# visitors before DER #1 )

(xlvii) The total number of hours and/or parts thereof that each visitor visits a website within a specified time frame before DER #7 mail-out (s)= (# hours visited before)

(xlviii) The average number of hours and/or parts thereof that a visitor visits a website within a specified time frame before DER #7 mail-out(s) = (ave # hours visited before) and/or (xlix) Other data may also be extracted and calculated to match specific DERs.For example the quantity and quality of communications received from a customer through phone, mail, e-mail, web etc. and/or b) Business specific data which inter alia may include:

(i) Expected industry standards for the above customer related data

(ii) Financial budgets, cash-flow forecasts and historical financial information determined by a business (es)

(iii) The annual $ spent by a business on advertising, and the number of new prospects/customers generated by that advertising, including the sales $ made to new customers (arising from that advertising) with that business, both individually and/or as a group/sub group.

(iv) The desired improvement criteria set by a business based on the above customer related data and business specific (BS) data, and/or c) Employee related data which inter alia may include:

(i) The annual percentage of staff defections, being the number of staff who have resigned from a business (es) in the last year multiplied by 100, and then divided by the total number of staff employed by that business (es) (including those who have resigned) in that year = (annual % staff defections before) (ii) The average number of years (and/or parts thereof) that employees remain employed by a business = (ave # years employees remain before) is an indication of staff loyalty to that business. This value can be calculated by individual, group or department as desired. Add up the total number of years (and/or parts thereof) that all employees in the sample have remained employed by that business (es) and then divide this by the total number of employees in that sample

d) Core data which inter alia may include:

(i) Each individual's name

(ii) The company or business they represent

(iii) Their postal address

(iv) Their E-Mail address

(v) Their contact phone number

(vi) Their contact fax number

(vii) The group or sub group that the individual has been assigned to (eg high sales dollar value customers versus low sales dollar value customers)

(viii) The names and/or number of individuals and/or entities that each customer has referred to a business

(ix) The sales history of each individual, group and/or sub group, including but not limited to: a) the type of purchases made in the past, and/or b) the differing needs or areas - of product/service interest, and/or c) the dollar value of sales made to each customer within the past year(s) = ($ sales total before) d) the dollar value of sales made to all customers within the past year(s) = ($ sales total before) e). Each and every reference to individuals or customers in this invention includes clients and prospective customers/clients alike. f ) Any reference made to "mail-outs" includes posted mail and/or electronic mail (E-Mail). g) Tag and or tagging = differentiating customers and/or prospective customers and/or employees (and/or groups of the same) which are or have been targeted for a specific DER mail- out (s), and then labelling those targeted customers and/or employees and/or prospective customers (and/or groups of the same) with a code for that DER strategy( ies ) . Each code must be separately identified and all records pertaining to that code must be able to be identified, separated from other records, compiled, analyzed and exported into report format as required in steps six and seven.

(h) A prospective customer is any individual and/or entity(ies) which has never purchased from that particular business (es) before, but that particular business (es) wants them to purchase goods and/or services from that business. The Analysis of data involves reviewing appropriate key data in step one above, to identify opportunities for improvement .

This step entails matching opportunities, trends and/or weaknesses (identified in step one) to specifically chosen DER strateg (ies) designed to improve the data analyzed.

Each business then matches these identified opportunities, trends and/or weaknesses identified in stage one with specific desired end results (DER's) as defined later in this application, which are devised to improve each identified opportunity, trend and/or weakness. Customers, employees and/or prospective customers within each defined opportunity, trend and/or weakness are then identified, tagged and then targeted with a specifically chosen DER mail-out strategy or strategies .

Each business (es) then selects cards, electronic cards and/or postcards which it believes will implement the selected DER strategy( ies ) .

STEP THREE

Evaluation of existing software (eg accounting, spreadsheet, customer management and/or database) capabilities to record, measure, correlate and analyze required data, and then tabulate this information into report format(s).

Check that all customer and/or employee information held within the application program is accurate and includes or can include and/or calculate relevant: a) Key data (as described in step one supra) b) Evaluation data (ED) as specified for each desired end result (DER). Including before and after mail-out(s) ED required to calculate key performance indicators (KPI's) for each DER. c) Key Performance Indicators (KPI's) for each DER strategy(ies) .

Ensure that the application program can, where appropriate : a). Run queries, extract, differentiate, sort and analyze records by:

(i) Key data (as described in step ONE) and/or

(ii) KPI and ED (Key Performance indicators and evaluation data as defined for each DER) , and/or b) "Tag" individual records, groups and sub groups within an application program for the particular DER mail-out(s) that will be or has been sent to them. c) Store, extract, calculate, run queries, differentiate, sort, correlate and analyze the necessary data (within an application program) for individual records, groups and sub groups tagged for each DER strategy. d) Compile, sort, calculate, analyze and differentiate data, then generate appropriate ED and/or KPI reports for each DER mail-out, after each DER mail-out(s), showing the effectiveness of each mail-out(s) in achieving the DER for individuals, groups and sub groups. e) Compile, sort, calculate, analyze and differentiate data, then generate key data (as per step ONE) reports, showing the effectiveness of each mail-out(s) in improving CR, ER, CD and BS data for individuals, groups and sub groups.

STEP FOUR

Selecting and/or setting up and labeling -appropriate records and/or fields in the application program to record, store, tag, sort and/or import/export the required data to/from another software program(s) for each (DER) mail-out including before and after analysis as required. a) Sort customers within the application program to identify and select individuals, groups and sub groups who will be or have been targeted for a specific DER mail-out strategy(ies) . b) Can this software store, differentiate, tag, sort and analyze data by the criteria detailed in Stage Two above? Yes/ No Decision Block 330 in Figure 3. c) Enter (into the application program) the mail-out(s) description against each tagged record, group and sub group selected for that particular DER mail-out(s). d) Enter into each tagged record (in the application program) the date each DER mail-out(s) will be or has been sent to the respectively tagged individuals, groups or sub groups . e). Setup and/or label data entry fields for the Evaluation data (ED as defined in each DER) and Key Performance indicators (KPI's as defined under each DER) relating to each and every tagged individual, group or sub group within the application program. f) Setup and/or label data entry fields for relevant key data (as described in step ONE) as appropriate.

STEP FIVE

Send the DER mail-out to tagged individuals, group(s) or sub group(s) and record behavioral and transactional results against each record, group arid/or subgroup in the application program after each DER mail-out. a) Send and/or E-Mail the selected DER mail-out^' to the tagged recipients identified for that DER mail-out(s), b) Gather, calculate, record, import and/or enter appropriate post mail-out (s) transactional and behavioral data for each tagged record, group or sub group into the relevant evaluation data (ED) fields for each DER strategy(ies) . c). Gather, calculate, record, import and/or enter appropriate post mail-out(s) transactional and behavioral data for each tagged record, group or sub group into the relevant key data (as described in step ONE) fields for each DER strategy(ies) .

STEP S IX

Extract, compile, calculate and tabulate data to generate results oriented reports for each desired end result (DER) mail-out. a) With reference to the selected DER, extract, compile, calculate and tabulate ED and/or KPI data, percentages and ratios relating to tagged customers from the application program into report(s) format as required. b) Extract, compile, calculate and tabulate key data (as specified in step ONE) supra relating to post mail-out (s) transactions and/or behavior into report format(s) as required. c) Review the reports generated by 1 & 2 above (step 6), then identify and tabulate key data and findings into new report(s) to highlight change(s), trends and opportunities. These results can then be compared to previous data and/or other campaigns to evaluate the effectiveness of each DER mail-out strategy.

STEP SEVEN

Evaluate the reports generated for each DER mail-out in step six and then use this knowledge to manage that business(es) . a) Compare and contrast the results generated after each DER mail-out(s). Including, but not limited to, comparisons against:

(i) industry benchmarks, and/or

(ii) previous data and/or calculations from that business(es) before the DER strategy(ies ) was implemented,

(iii) data from alternative strategy( ies ) , and/or

(iv) the cost of implementing each DER strategy(ies )

(v) data from other businesses. b) Generate reports showing the key findings. These reports can then be used for decision making and/or strategic direction.

OPERATION

The operation is best understood by the following 7 examples for 7 different DERs, as follows:

1. To increase the number, frequency and/or monetary value of sales per customer/client or prospective customer/client per annum, both individually and/or by group/sub group. 2. To encourage customers/clients to pay for goods and/or services promptly

3. To improve customer/client loyalty and customer/client retention. Including an improvement in the number of satisfactory complaint resolutions received from customers/clients and prospective customers/clients .

4. To increase the number and/or frequency of customers, prospective customers and/or entities referred by existing customers and/or business associates to a business. To increase the number of customers who refer prospective customers and/or new customers to a business. Also to increase the $ value of sales made by a business to referred customers .

5. To increase the number of prospective customers who subsequently choose to purchase goods and/or services from a business .

6. To increase the length of time each employee chooses to remain employed by a specific business (es) and/or to decrease the number of employees who choose to resign from employment with a business(es) .

7. To increase the number of visitors to a website, and/or increase the frequency and/or length of time people choose to visit a website. EXAMPLE-1

1. Desired End Result #1

To increase the number, frequency and/or monetary value of sales per customer/client or prospective customer/client per annum, both individually and/or by group/sub group.

2. Evaluation Data (ED) for DER #1

Separate fields in the application program must exist or be setup to record, store, sort and/or analyze each of the following criteria, by individual, group or sub group, as appropriate. a) The total number of tagged records selected for this DER = (total # in DER #1), and/or b) The absolute number of sales arising within a year(s) after the mail-out to tagged customers/clients or tagged prospective customers/clients = (# sales after DER #1), and/or c) The dollar value of sales made to tagged customers/clients or tagged prospective customers/clients within a year(s) after the DER #1 mail-out (s) to them = ($ sales after DER #1) d) The frequency or number of times sales were made to tagged customers/clients within a year after a DER mail-out(s) to them = (# times sales made after) 3. Key Performance Indicators (KPI's) for DER #1

KPI's correlate and analyze data in tagged records to measure the effectiveness of each DER mail-out in achieving each DER. Such KPI's include but are not limited to: a) Sorting tagged records into groups and sub groups to look for patterns of transactional and behavioral trends relating to and within each group or sub group. For example, sort all tagged records for DER #1 into groups and/or sub groups by sales dollar value over the past year ($ sales total before), to identify and separate high sales dollar value customers/clients from low sales dollar value customers/clients. The business then subtracts the ($ sales total before) from the ($ sales after DER #1) to identify any change and the dollar value of that change in sales = ($ sales change) , and/or

^' b) (Ave $ sales after DER #1) = ($ sales after DER #1) divided by (total # in DER #1). This gives the average dollar value of sales per tagged customer/client and/or tagged prospective customer/client after DER #1 mail-out (s), and/or c) Take the same size sample of each set of customers, one group was sent DER #1 mail-out and the other group was not sent any DER mail-out. Compare the results arising after DER #1 mail-out to the results before that mail-out (for the same specified time frame, sample size and comparable circumstances) as follows: (i) (% change in # sales after DER #1) = (# sales after DER #1) minus (# sales before), then multiplied by 100 and then divided by (# sales before). This will give the percentage increase or decrease in the number of sales made to tagged individuals, groups or sub-groups after DER #1, and/or

(ii) (% $ sales change) = ($ sales change) multiplied by 100 and then divided by ($ sales total before). This will give the percentage increase or decrease in the dollar value of sales to tagged individuals, group and sub groups after DER #1 mail-out(s) as compared to before DER #1 mail-out, and/or

(iii) (% change times) = [(# times sales made after) minus (# sales before)] multiplied by 100 and then divided by (# sales before).

This is the percentage change in the number of times per annum that a tagged customer purchases goods and/or services from a business after a DER mail-out, and/or d) ($ sales change per $ spent) = ($ sales change) divided by the dollar cost of DER #1 mail-out, shows the $ sales change per $ spent on DER #1 mail-out.

EXAMPLE -2

1. Desired End Result #2 '

To encourage customers/clients to pay for goods and/or services promptly

2. Evaluation Data (ED) for DER #2

Separate fields in the application program must exist or be setup to record, store, sort, identify and/or analyze each of the following criteria and/or results after DER #2, by individual, group or sub group, as appropriate. a) The total number of tagged records selected for DER #2 = (total # in DER #2), and/or b) The absolute number of invoices unpaid within a specific time frame after the mail-out to tagged customers/clients = (# invoices unpaid after DER #2), and/or c) The absolute number of invoices paid within a specific time frame after the mail-out to tagged customers/clients = (# invoices paid after DER #2), and/or d) The dollar value of unpaid invoices relating to each tagged individual, sub group and group after the DER #2 mail- out (s) that remain unpaid in full within a specified time frame after due date = ( $ unpaid invoices af er DER #2 ) , and/or e) The dollar value of payments received from tagged customers within a specified time frame after the DER #2 mail- out (s) = ($ paid invoices after DER #2), and/or . f) The absolute number of customers who have paid some and/or all of their previously unpaid- invoices within a specified time frame after DER #2 mail-out = (# paid after DER

g) The number of customers or groups of customers who have not paid their invoice(s) in full and within a specified time frame after DER #2 mail-out (s) = (# customers unpaid after DER #2), and/or h) The total number of days after DER #2 mail-out (s) that tagged customers have taken to pay in full for goods and/or services purchased from a business, calculated from the date the business first charges and/or invoices each customer to the date each customer actually pays in full for said goods and/or services purchased from that business = (total # days taken after DER #2 ) i) The number of days after DER #2 mail-out(s) that tagged customers have taken to pay for goods and/or services which they purchased from a business, calculated from the date DER #2 mail-out (s) was sent to those tagged customers through to the date each customer actually pays (in full) for said goods and/or services purchased from that business = (# days taken after DER #2 ) 3. Key Performance Indicators (KPI's) for DER #2

KPI's correlate and analyze data in tagged records to measure the effectiveness of each DER mail-out in achieving each DER. Such KPI's are calculated separately for individuals, group(s) and sub group(s) on criteria and/or results after DER #2 and include but are not limited to: a) Sorting tagged records into groups and sub groups to look for patterns of transactional and behavioral trends relating to and within each group or sub group. For example, sort all tagged records for DER #2 by historical sales dollar value, to identify and separate high sales dollar value customers/clients from low sales dollar value customers/clients. The business can then count the number of records within each group and/or sub group and identify which group(s) or sub group(s) has a higher number of unpaid invoices, and/or b) Take the same size sample of each set of customers, one group was sent DER #2 mail-out and the other group was not sent any DER mail-out. Compare the results arising after DER #2 mail-out to the results before that mail-out (for the same specified time frame, sample size and comparable circumstances) as follows:

(i) The average number of days that tagged .customers, who have subsequently paid their outstanding invoice(s) after DER

#2 mail-out (s), have taken to pay these previously outstanding invoices = (ave # unpaid days after). Calculate this (both by individual and/or by group), by taking the total (# days taken after DER- #2) for all tagged customers who have subsequently paid their invoices, divided by the number of customers in that sample, and/or

(ii) The average total number of days after DER #2 ail- out(s) that tagged customers have taken to pay goods and/or services from the date of invoice to the date that payment was received in full = (ave total # unpaid days after). Calculate this (both by individual and by group), by taking (total # days taken after DER #2) divided by (total # in DER #2), and/or

(iii) The percentage of tagged customers who have paid their invoice(s) within a specified time frame after DER mail- out #2 = (% customers paid) = (# paid after DER #2) multiplied by 100 and then divided by (total # in DER #2), and/or

(iv) The percentage change in the number of customers or groups of customers who have not paid their invoice(s) in full within a specified time frame after DER #2 = (# customers unpaid after DER #2) minus (# customers unpaid before), then multiply this number by 100 and divide by (# customers unpaid before) = (% change in # unpaid customers), and/or

(v) . The percentage change in the total dollar value of invoices that remain unpaid in full within a specified time frame after DER #2 = ( % change in unpaid $ ) = ( $ unpaid invoices after DER #2) minus ($ unpaid before), then multiplied by 100 and divided by ($ unpaid before), and/or c) ($ received per $ cost of DER #2) = ($ paid invoices after DER #2) divided by the $ cost of DER #2 mail-out, will identify the $ value of invoices paid after DER #2 mail-out, per $ cost of DER #2 mail-out, and/or d) (# paid per # sent DER #2) = (# paid after DER #2 ) divided by (total # in DER #2), identifies the ratio of tagged customers who have paid some and/or all of their outstanding invoices within a specified time frame after DER #2 mail-out, relative to the number of tagged customers who were sent DER #2 mail-out .

EXAMPLE - 3

1. Desired End Result #3

To improve customer/client loyalty and customer/client retention. Including an improvement in the number of satisfactory complaint resolutions received from customers/clients and prospective customers/clients.

2. Evaluation Data (ED) for DER #3

Separate fields in the application program must exist or be setup to record, store, sort, identify and/or analyze each of the following criteria as appropriate, by individual, group or sub group. a) The total number of tagged records selected for DER #3 = (total # in DER #3), and/or b) The tvotal number of tagged customers who gave favorable feedback after DER #3 mail-out was sent^' to them = (total # favorable), and/or c) The total number of tagged customers who gave unfavorable feedback after DER #3 mail-out was sent to them = (total # unfavorable), and/or d) . The dollar value of sales made to tagged customers within a year(s) after the DER #3 mail-out (s) to them = ($ sales after DER #3), and/or e) the sum total number of sales made to all tagged customers within a year(s) after DER #3 mail-out was sent to them = (# sales after DER #3) , and/or f) The number of years that tagged customers continue to purchase goods and/or services from a business after that business has sent them any DER mail-out(s) = (# years loyal after) g) The total number of tagged customers who have purchased goods and/or services from a business within a year(s) after a DER mail-out to them = (# purchased after) h) ($ cost to get a sale) = total $ cost of DER #3 mail- out divided^' by (# sales after DER #3) = the $ cost of DER #3 mail-out to get one sale 3. Key Performance Indicators (KPI's) for DER #3

KPI's correlate and analyze data in tagged records to measure the effectiveness of each DER mail-out in achieving each DER. Such KPI's are calculated separately for individuals, group(s) and/or sub group(s) and include but are not limited to: a) (% favorable after DER #3) = (total # favorable) multiplied by 100 and then divided by (total # in DER #3), will give the percentage of tagged customers who reacted favorably to DER #3 mail-out, and/or b) (% unfavorable after DER #3) = (total # unfavorable) multiplied by 100 and then divided by (total # in DER #3), will give the percentage of tagged customers who reacted unfavorably to DER #3 mail-out, and/or c) ($ sales per tagged customer in DER #3) = ($ sales after DER #3) divided by (total # in DER #3). This gives the average dollar value of sales made per tagged customers after DER #3 mail-out(s), and/or d) Take the same size sample of each set of customers, one group was sent DER #3 mail-out and the other group was not sent any DER mail-out. Compare the results arising after DER 3 mail-out to the results before that mail-out(s) (for the same specified time frame, sample size and comparable circumstances) as follows: (i) (% sales $ change after DER #3) = ($ sales after DER #3) minus ($ sales total before) then multiplied by 100 and then divided by ($ sales total before). This will give the percentage increase or decrease in the dollar value of sales made to tagged customers after DER #3 mail-out (s) as compared to before DER #3 mail-out(s), and/or

(ii) (% change in § sale^'s after DER #3) = (# sales after DER # 3 mail-out) minus (# sales before), then multiplied by 100 and then divided by (# sales before) . This will give the annual percentage increase or decrease in the number of sales made to tagged customers within a year after DER #3 mail-out. e) Calculate the lifetime value of a customer (LTV as described in Stage One) after DER #3 including the components of LTV, for the same size sample of customers, both before and after DER mail-outs . Then compare the results . f) (% purchased after DER #3) = (# purchased after) multiplied by 100 and then divided by (total # in DER #3), gives the percentage of tagged customers who subsequently purchased from a business within a year after DER #3 was sent to them.

EXAMPLE -4

1. Desired End Result #4

To increase the number and/or frequency of customers, prospective customers and/or entities referred by existing customers and/or business associates to a business and/or

To increase the number of customers who refer prospective customers and/or new customers to a business. Also to increase the $ value of sales made by a business to referred customers . 2 Evaluation Data (ED) for DER #4

Separate fields in the application program must exist or be setup to record, store, sort and/or analyze each of the following criteria, by individual, group and/or sub group, as appropriate . a) The total number of tagged records selected for this DER = (total # in DER #4), and/or b) The absolute number of customers, prospective customers and/or business associate (s)/entities referred by tagged customers and/or business associates to a business within a year(s) after DER #4 mail-out was sent to those tagged customers and/or business associates = (# referred after DER #4 ) , and/or c) The dollar value of sales made to referred customers within a year(s) after the DER #4 mail-out(s) was made to tagged customers and/or business associates = ($ referred sales after DER #4), and/or d) The sum total number of times per annum that every tagged customer and/or business associate has referred a prospective customer(s) and/or new customer(s) and/or business associate(s) to a business within a year(s) after DER #4 mail-out (s) was sent to those tagged individuals and/or entities = (# times referred after DER #4), and/or e) The number of tagged customers and/or business associates who have referred a prospective customer(s), customer(s) and/or business associate(s) or entities to a business within a year(s) after DER #4 mail-out(s) to them= (# customers who have referred after DER #4 ) , and/or f). The sum total number of days that have passed after DER #4 mail-out(s) before each tagged customer and/or business associate, who has subsequently referred a prospective customer(s), business associate(s) customer(s) and or entity(ies) to a business within a year after DER #4 mail-out, actually gives that business the contact details for said prospective customer(s) and/or business associate(s) and/or customer(s)/entity(ies) . The number of days taken by each tagged customer is calculated from the date the business first sends DER #4 mail-out to them, to the date that tagged customer gives that business the contact details for a referred prospective customer(s) and/or customer(s) and/or business associate(s) , = (# days to refer) 3 Key Performance Indicators (KPI's) for DER #4

KPI's correlate and analyze data in tagged records to measure the effectiveness of each DER mail-out in achieving each DER. Such KPI's include but are not limited to: a) Sorting tagged records into groups and sub groups to look for patterns of referral and/or behavioral trends relating to and within each group or sub group. For example, sort all tagged records for DER #4 by historical sales dollar value ($ sales total before), to identify and separate high sales dollar value customers/clients from low sales dollar value customers/clients. The business can compare the ($ sales to referrals after DER #4 mail-out) for each group or sub group, to identify the dollar value and group or sub group that has generated the most referred business, and/or b) (Ave # referrals after DER #4) = (# referred after DER #4) divided by (total # in DER #4) = The average number of new customers and/or prospective customers referred to a business by tagged customers and/or business associates within a year of DER #4 being sent to said tagged customers and/or business associates c) (Ave % customers who refer after DER #4) = (# customers who have referred after DER #4), multiplied by 100 & divided by (total # in DER #4) = the percentage of tagged customers &/or business associates who have referred customers and/or prospective customers &/or business associates (s ) to a business within a year of DER #4 mail-out (s). d) Take the same size sample of each set of prospective customers and/or customers, &/or business associate(s) one group was sent DER #4 mail-out and the other group was not sent any DER mail-out. Compare the results arising after DER #4 mail-out to the results without any DER mail-out (for the same specified time frame, sample size and comparable circumstances) as follows:

(i) (% change in # referrals after DER #4) = (ave # referrals after DER #4) minus (ave # referrals before), then multiplied by 100 and then divided by (ave # referrals before) . This will give the percentage change in the average number of referred customers and/or referred prospective customers &/or referred business associates per annum after DER #4 mail-out (s) as compared to before DER #4 mail-out, and/or

(ii) (ave % change in # customers who refer) = (ave % customers who refer after DER #4) minus (ave % customers who refer before), then multiply by 100 and divide by (ave % customers who refer before) = the average percentage increase or decrease in number of customers &/or business associate(s) who refer new customers and/or prospective customers &/or business associates to a business within a year after DER #4 mail-out, and/or (iii) (% change in # times referred) = (# times referred after DER #4) minus (# times referred befo.re), then multiplied by 100 and divided by (# times referred before), gives the annual percentage change in the number of times customers and/or business associates have referred prospective customers and/or new customers &/or business associates to a business after DER #4 mail-out e) (Ave $ sales to referrals after DER #4) = ($ referred sales after DER #4) divided by (# referred after DER #4). This ratio gives the average dollar value of sales made to each referred customer and/or business associates within a year(s) after DER #4 mail-out (s), and/or f) ($ referred sales per $ cost of DER #4) = ($ referred sales after DER #4) divided by the dollar cost of DER #4 mail- out = the dollar value of sales generated by referral business within a year(s) after DER #4 mail-out(s), per $ cost of DER #4 mail-out, and/or g) The average number of days taken for tagged customers, who have referred a customer(s) and/or prospective customer(s) and. or business associate(s) to that business (es) within a year(s) after DER#4 mail-out (s), to actually give the contact details for the referred prospective customer (s) and/or customer(s) to that business = (ave # days to refer after DER #4) = (# days to refer) divided by (# customers who have referred after DER #4) and/or .h) ($ cost to get a referral) = total $ cost of DER #4 mail-out divided by (# referred after DER #4) = the $ cost of DER #4 mail-out to get one referred customer and/or referred prospective customer and/or referred business associates for that business.

EXAMPLE - 5

1. Desired End Result #5

To increase the number of prospective customers who subsequently choose to purchase goods and/or services from a business. This includes but is not limited to:

(i) reactivating existing prospective customers, customers and/or Entities who have not purchased and/or contacted a business within the past year, and/or

(ii) converting new prospective customers into customers more often and/or more quickly

2. Evaluation Data (ED) for DER #5

Separate fields in the application program must exist or be setup to record, store, sort and/or analyze each of the following criteria, by individual, group or sub group, as appropriate . a) The total number of tagged records selected for this DER = (total # in DER #5), and/or b) The absolute number of sales made to tagged prospective customers/clients within a year after the mail- out was sent to said tagged customers/clients = (# sales after DER #5), and/or c) The dollar value of sales made to tagged customers/clients and/or tagged prospective customers/clients within a year(s) after the DER #5 mail-out (s) was sent to them = ($ sales after DER #5) d) The number of days taken by each and/or every tagged customer and/or prospective customer to purchase goods and/or services from a business after DER #5 mail-out to them = (# days prospects take after DER #5). Calculate this by identifying those tagged recipients who subsequently purchased goods and/or services after DER #5 mail-out, and then calculate the total number of days between the date DER #5 mail-out was sent to each of these tagged customers and/or tagged prospective customers to the date a sale was made to each of these tagged customers and/or prospective customers .

3 Key Performance Indicators (KPI's) for DER #5

KPI's correlate and analyze data in tagged records to measure the effectiveness of each DER mail-out in achieving each DER. Such KPI's include but are not limited to: a) (ave $ sales after DER #5) = ($ sales after DER #5 mail-out) divided by (total # in DER #5 mail-out) = the average dollar value of sales per tagged prospective customer b) Take sample groups of prospective customers and/or customers, one group was sent DER #5 mail-out and the other group was not sent any DER mail-out. Compare the results arising after DER #5 mail-out to the results without any DER mail-out (for the same specified time frame, sample size and comparable circumstances) as follows:

(i) (# converted customers after DER #5) = the total number of tagged customers and/or prospective customers who subsequently purchase goods and/or services from a business within a year(s) after DER #5 mail-out was sent to them

(ii) (% conversion after DER #5) = the percentage of tagged prospective customers &/or customers who subsequently purchased goods/services from a business within a period after DER # 5 mailout(s), begin (# converted customers after DER # 5) multiplied by 100 and divided by (Total # in DER # 5)

(iii) Compare ($ sales after DER #5) with ($ sales total before) to identify and measure any change in sales $ after DER #5 mailout(s). This shows the effectiveness of DER # 5 mailout(s) in converting or reactivating customers within a period of DER # 5 mailout in terms of the change in sales $ generated.

(iv) The annual percentage of in sales $ attributed to tagged customers and/or prospective customers within a year after DER #5 mail-out = (% change in annual sales $) = ($ sales after DER #5) multiplied by 100 and then divided the total annual $ sales to all customers . (v) The percentage of annual $ sales made to tagged customers and/or prospective customers who have previously not purchased goods and/or services from that business in the year prior, but have now been reactivated and/or converted into current customers in the year(s) after DER #5 mail-out was sent to them= (new % converted sales).

This can be calculated by multiplying ( $ sales after DER # 5) by 100 & dividing by the total annual $ sales at that time.

(vi) The annual number of sales to customers, who had previously not purchased goods and/or services from that business in the year prior, but have now been reactivated and/or converted into current customers in the year after DER #5 mail-out was sent to them = (new # converted sales)

(vii) The percentage of the annual number of sales made to customers, who had previously not purchased goods and/or services from that business within a year(s) before DER #5 mail-out(s), but have now been reactivated and/or converted into current customers in the year after DER #5 mail-out was sent to them = (new % change in converted sales). To calculate this, multiply (new # converted sales) by 100 and then divide by (# converted sales). (viii) The average number of days it takes for a prospective customer, who then becomes a customer by purchasing of goods and/or services from a business, to become a customer after DER #5 mail-out = (new ave # days to purchase). First, identify a sample number of prospective customers who subsequently purchased from a business after DER #5 mail-out and therefore became customers. Next, add up the total number of days each one of these customers took to purchase, from the date of first contact with the business to the date a sale was made to them.

Then take the sum total of all these days for these customers to purchase and then divide this by the number of customers in that sample. Compare this to before any DER mail-out (ave # days to purchase).

(ix) (% change in # days) = the percentage change in the number of days it takes for a prospective customer to purchase goods and/or services from a business after DER #5 = (new ave # days to purchase) minus (ave # days to purchase), then multiply this number by 100 and divide by (ave # days to purchase) c. ($ sales per $ spent on DER #5) = ($ sales after DER #5 mail-out) divided by the dollar cost of DER #5 mail-out, will identify the $ value of sales made to tagged individuals, groups and/or sub groups after DER #5 mail-out, relative to the $ cost of DER #5 mail-out, and/or d. (ave # sales per converted customer) = (new # converted sales) divided by (# converted customers after DER #5 ) = the number of sales made to each converted customer within a year(s) after DER #5 mail-out to them.

EXAMPLE -6

1. Desired End Result #6

To increase the length of time each employee chooses to remain employed by a specific business (es) and/or to decrease the number of employees who choose to resign from employment with a business(es) .

2. Evaluation Data (ED) for DER #6

Separate fields in the application program must exist or be setup to record, store, sort and/or analyze each of the following criteria, by individual, group or sub group, as appropriate . a) The total number of tagged records selected for this DER = (total # in DER #6), and/or b) The annual number of staff defections after DER #6 mail-out, being the number of staff who have resigned from a business (es) within a year(s) of DER #6 mail-out being sent to them, divided by the total number of staff employed by that business (es) (including those who have resigned) in that year, = (new annual # staff defections), and/or c) The average number of years (and/or parts thereof) that employees remain employed by a business after DER #6 mail-out to them = (new ave # years employees remain) is an indication of staff loyalty to that business.

To calculate this value, add up the total number of years (and/or parts thereof) that all employees in the sample have remained employed by that business(es) and then divide this by the total number of employees in that sample.

3 Key Performance Indicators (KPI's) for DER #6

KPI's correlate and analyze data in tagged records to measure the effectiveness of each DER mail-out in achieving each DER. Such KPI's include but are not limited to: a) Take the same size sample of each set of employees or previous employees, one group was sent DER #6 mail-out and the other group was not sent any DER mail-out. Compare the results arising after DER #6 mail-out to the results without any DER mail-out (for the same specified time frame, sample size and comparable circumstances) as follows:

(i) (new annual # staff defections) versus (annual # staff defections)

.(ii) (new ave # years employees remain) versus (ave # years employees remain) (iii) (new annual # staff defections) minus (annual # staff defections), multiplied by 100 and then divided by (annual # staff defections), will show the percentage change in defections after DER #6 mail-out(s) as compared to before any DER mail-out(s) = (% change in staff defections).

(iv) (% change per $ spent on DER #6) = (% change in staff defections) divided by the total dollar cost of DER #6 mail-out(s) = the percentage of change in staff defections per $ spent on DER #6 mail-out (s).

(v) (new ave # years employees remain) minus (ave # years employees remain), multiplied by 100 and then divided by (ave # years employees remain), will show the percentage change in the number of year(s) or parts thereof that employees choose to remain employed with that business (es) after DER #6 mail- out(s) compared to before any DER mail-out = (% change in ave years employed) .

Compare (% change in ave years employed) to the $ cost of DER #6 mail-out (s) to show the average percentage improvement for money spent on DER #6 mail-out.

EXAMPLE - 7

1. Desired End Result # 7

To increase the number of visitors to a website, and/or increase the frequency and/or length of time people choose to visit a website. Also to increase the number, frequency and/or value of sales made to website visitors either off and/or on line to the internet.

1. Evaluation Data (ED) for DER #7

Separate fields in the application program must exist or be setup to record, store, sort and/or analyze each of the following criteria, by individual, group or sub group, both before and after DER #1 mail-out as appropriate. a) The total number of tagged records selected for this DER = (total # in DER #7) b) The total number of visitors who visit a website within a specified time frame after DER #7 mail-out (s) = (# visitors after DER #1 ) c) The number of times each visitor visits a website within a specified time frame after DER #7 mail-out (s) = (# times visited after DER #7) d) (total # times visited after DER #7) = add up the (# times visited after DER #7) for all visitors e) The average number of times each visitor visits a website within a specified time frame after DER #7 mail-out (s) = (ave # times visits after DER #7) = (total # times visited after DER #7) divided by (# visitors after DER #7) f). The total number of hours and/or parts thereof that each visitor visits a website within a specified time frame after DER #1 mail-out (s)= (# hours visited after DER #7) g) The total number of hours and/or parts thereof that every visitor visits a website within a specified time frame after DER #7 mail-out (s) = (total # hours visited after DER #7) h) The average number of hours and/or parts thereof that a visitor visits a website within a specified time frame after DER #7 mail-out(s) = (ave # hours visited after DER #7) = (total # hours visited after DER #7) divided by (# visitors after DER #7)

(i) The total $ sales made to tagged customers within a specified time frame after DER #7 = ($ sales after DER #7)

(j). (Ave $ sales after DER #7) = ($ sales after DER #7) divided by the number of customers who have purchased goods and/or services from a business within a specified time frame after DER #7 k) The total # sales made to tagged customers within a specified time frame after DER # 7 mailout = (# sales after DER # 7) VARIATIONS

The inventor has given a non-limiting description of the concept. Various modifications and combinations of the illustrative embodiments as well as other embodiments of the invention will be apparent to a person of average skill in the art upon reference to this description.

Due to the simplicity and elegance of the design of this invention designing around it is very difficult if not impossible. Nonetheless many changes may be made to this design without deviating from the spirit of this invention. Examples of such contemplated variations include the following:

1. The software algorithm may be modified without substantial impact on the end result.

2. Additional complimentary and complementary functions and features may be added.

3. The number of steps may be increased, decreased, renumbered or regrouped without deviating from the spirit of this invention.

4. The program may be converted into other programming languages .

5. The program may be automated and integrated with other programs .

6. Packaging colors, materials, shapes and design may be changed without deviating from the spirit of this invention. 7. Obvious and even some non-obvious enhancements may be made without deviating from the spirit of this invention.

8. The invention may be adapted for other related uses for example optimizing the operations of a non-profit organization.

9. Complementary functions and affects may be added.

10. Other changes such as aesthetic and substitution of newer materials as they become available which substantially perform the same function in substantially the same manner with substantially the same result without deviating from the spirit of this invention may be made.

Following is a listing of the components and procedural steps used in this embodiment arranged in ascending order of the reference numerals for ready reference of the reader.

100 = The process and system of this invention generally.

110 = Key data analysis

120 = Matching opportunities with DERs

130 = Evaluation of prior art software

140 = Flagging or tagging subset of the records.

150 = Mail-out to tagged parties

160 = Prepare results oriented reports for each DER

170 = Evaluation of the reports for changes

180 = Feedback loop 200 = Review and analysis of customer data to identify opportunities for.mail-outs^' generally 210 = Review and analysis of customer data in the prior art application program used by a business enterprise. 220 = Identification of DERs for ailout 230 = Identification and design of the mailout to tagged population in the software. 300 = Mailout DER Interface flow-chart generally 310 = Record selection and tagging in application software 320 = Tagging operation for a specific DER 330 = Threshold Decision step to ascertain whether the software can store, differentiate, tag/flag, sort and analyze data about selected population. 340 = Tagging and/or flagging of all intended recipients of a particular mailout 350 = Enter or export core data into prior art application program 360 = Entry of mail out description into the prior art application program 370 = Entry into each tagged record of the prior art application program, the date each DER mailout will be or has been sent 380 = Evaluation of data 400 = Interface between the mailouts and the desired end results generally 410 = Posting of the DER mailout to tagged population 420 = Import of transactional and behavioral data for each tagged record into the relevant evaluation fields . 430 = Calculation step including recording ^• of evaluation data for each DER mailout 500 = Interface between DER (Desired End Result) ,

KPI (Key Performance Indicators) and the results oriented reports .

510 = KPI (Key Performance Indicator) Data including calculation or extraction thereof

520 = Calculation of percentages and ratios of -KPI

530 = Tabulate KPI data into results oriented reports

600 = Essential attributes of a software application generally

610 = Mapping of KPI and DER evaluation data against core data about customers or other population of employees, stockholders, suppliers etc.

620 = Tagging flagging of records for a specific mailout for a specific DER.

630 = Analysis of data

640 = KPI reports for each mailout 700 = Evaluation of prior art application software (such as accounting, spreadsheet, database) capabilities to record, measure, correlate and analyze data for results oriented reports generally

710 = Mail out including selection and/or design of

720 = Basic core data for various populations

722 = Employee data

724 = Business data

726 = Customer data

730 = Evaluation Data

740 = KPI data

750 = Results Oriented Reports

DEFINITIONS

While exacting care has been taken to avoid terms of art and use words with their conventional dictionary meaning the following definitions are included for clarification of the specification and its interpretation.

CD = Core data relating to each individual, group or sub group within a customer base or other population base.

DER - Desired end result.

DIY - Do It yourself

ED - Evaluation data required for each DER mail-out.

Interface - Matching or two or more dissimilar entities however realized

OEM - Original Equipment Manufacturer

therefore contemplated that the appended claims will cover -any such modifications, embodiments as fall within the true scope of the invention.

Claims

The inventor claims :

1. A process for optimizing the performance and profits of a business comprising the steps of: a) establishing a desired end result; b) establishing criteria for mail out; c) selecting key data according to said criteria for a mailout; d) designing a mail out piece; e) executing the mailout; f ) comparing pre and post mailout results; and g) executing said steps a) through f) for another DER.

2. The process for optimizing the performance and profits of a business of claim 1 wherein said steps are performed with the aid of computer software.

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3. The process for optimizing the performance and profits of a business of claim 1 wherein said pre and post' comparing these results includes comparison against; a) industry benchmarks; b) previous data from that business (es) before a DER strategy(ies ) was implemented; c) data from alternative strategy; d) data from other businesses; and e) the cost data of implementing each DER strategy( ies )

4. The process for optimizing the performance and profits of a business of claim 1 wherein said mailout piece is one selected from the group: a) electronic cards; b) voice greetings; c) greeting cards; and d) thank you notes.

5. A process for optimizing a business comprising the steps of: a) selecting or establishing a desired end result and concomitant strategy; b) extracting and analyzing current relevant key data to identify opportunities, trends and/or weaknesses;

65 c) matching said opportunities, trends and/or weaknesses to said DER strategy(ies) as a means _.for improving said analyzed key data. d) evaluating existing software (eg accounting, database) capabilities to record, measure, correlate and analyze required data, and then tabulate the resultant information into report format( s ) . e) selecting and/or setting up and labeling of appropriate records and/or fields in the application program to record, store, tag, import/export and sort the required data for each said desired end result (DER) mail-out(s). f) designing a DER communication; g) sending said DER communication to tagged individuals, group(s) or sub group(s) and record behavioral and transactional results against each record, group and/or subgroup in the application program after each DER mail-out. h) extracting, compiling, calculating and tabulating data to generate results oriented reports for each desired end result mail-out; i) evaluating said reports generated for each said DER mail-out; and j) using the resultant knowledge via a feedback loop to manage that business.

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6. The process for optimizing a business of claim 5 wherein said DER communication comprises .electronic cards .

7. The process for optimizing a business of claim 5 wherein said DER communication comprises voice greetings .

8. The process for optimizing a business of claim 5 wherein said DER communication comprises thank you notes .

9. The process for optimizing a business of claim 5 wherein said DER communication comprises greeting cards .

10. A computerized mail out system for optimizing the performance and profits of a business comprising means for business relationships and motivational messages through direct mail communications .

11. The computerized mail out system for optimizing the performance and profits of a business of claim 10 wherein said direct mail communications comprise electronic cards.

12. The computerized mail out system for optimizing the performance and profits of a business of claim 10 wherein said direct mail communications comprise voice greetings .

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13. The computerized mail out system for optimizing the performance and profits of a business of claim 10 wherein said direct mail communications comprise thank you notes.

14. The computerized mail out system for optimizing the performance and profits of a business of claim 10 wherein said direct mail communications comprise greeting cards .

15. The computerized mail out system for optimizing the performance and profits of a business of claim 10 which includes means for comparing pre and post mail out performance of the business.

16. The computerized mail out system for optimizing the performance and profits of a business of claim 10 wherein said direct mail communications comprise at least one of the following: a) electronic cards; b) voice greetings; c) greeting cards; and d) thank you notes.

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17. The computerized mail out system for optimizing the performance and profits of a business of claim 10 wherein said pre and post comparison is against one or more selected from the group consisting of. a) industry benchmarks; b) previous data from that business (es) before a DER strategy(ies) was implemented; c) data from alternative strategy; d) data from other businesses; and e) the cost data of implementing each DER strategy.

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