Abstract:
An instrument for measuring and presenting customer impressions of a company uses weighted response values of survey questions to develop a customer experience score and a customer interaction score. The two scores are added to produce a composite score. The three scores for a company may be presented with other score sets for other companies to provide a simple and consistent comparison of companies. When different businesses or even different industries have different customer experiences and interactions, weighting of response values can be adjusted to more accurately reflect the importance of that factor on the overall customer experience, which models customer satisfaction.

Description:
TECHNICAL FIELD 
     This disclosure is directed to a system and method for compiling, weighting, and displaying a compilation of consumer business metrics, specifically, customer experience metrics. 
     BACKGROUND 
     This Background is intended to provide the basic context of this patent application and it is not intended to describe a specific problem to be solved. 
     Measuring customer satisfaction in a business presents a number of challenges, including selection of what areas to query, what level of subjectivity to request of survey-participants, and selecting a weighting criteria that reflects the business impact of a particular topic. In a large business, where many business units contribute to the company&#39;s success, these customer satisfaction measures may vary by business unit, further complicating the task of properly evaluating customer experience. 
     SUMMARY 
     This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. 
     In order to consistently evaluate consumer impressions of a product or service in an industry, even across widely disparate business lines, an evaluation tool recognizes several fundamental topics that affect consumer impressions and builds business-specific factors to measure each topic for that business. Further, recognizing that some factors are more important to certain businesses than others, each factor may be weighted for a particular business and topic. 
     For almost any industry, these topics may include price, brand reputation, reliability, and responsiveness/customer service. In an insurance industry, these topics may include a customer&#39;s view of getting personalized products or services, their claims activity, and whether the company cares about them as an individual. However, the impact of these factors for products such as car insurance vs. life insurance may vary based on the number of interactions, price competition, and the difference in claims activity. Developing different questions for each topic by business lines allow for the collection of metrics for a common topic, e.g., reliability, that reflects that particular business&#39;s marketplace. Applying different weights when calculating scores provides a mechanism to adjust for the relative impact of that topic to customers in a particular business or industry. 
     In one embodiment, a method of accumulating, weighting, and presenting customer experience data, receives, at a server, information related to i) a customer&#39;s experience with a company, the information comprising data associated with the customer&#39;s perception of price, responsiveness, reliability, availability, brand reputation, expertise, accuracy, and a factor based on an unequally weighted combination of simple to do business with, caring, and personalized, and ii) the customer&#39;s specific customer interactions with the company, the information comprising data associated with interactions between the consumer and the company for a purchase, a quote, a new policy, a policy change, a new bank account, a change to a bank account, a new loan, a change to a loan, a loan payment, a new credit card, a change to a credit card account, a credit card payment, a new mutual fund, a change to a mutual fund, a new money market, a change to a money market, a new retirement account, a change to a retirement account, billing and payment, a deposit, a withdrawal, a fraud report, claims activity or any other interaction regarding an insurance product/account or a financial product/account, for example. 
     The method further uses an algorithm executed on the server to unequally weight the customer experience data to develop an experience score for the company and using an algorithm executed on the server to equally weight the customer specific interaction data to develop an interaction score for the company. The method further uses an algorithm executed on the server to calculate an average of the experience score and the interaction score to develop a composite score for the company and renders an image of the experience score, the interaction score, and the composite score for the company for presentation of the image via a computer. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a flow chart illustrating compilation and presentation of an exemplary customer satisfaction dashboard; 
         FIG. 2  is a rendering of an exemplary customer satisfaction dashboard; 
         FIG. 3  is a flow chart illustrating a process for developing a customer satisfaction dashboard; and 
         FIG. 4  is a simplified and exemplary block diagram of a system supporting processing and display of a customer satisfaction dashboard. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Although the following text sets forth a detailed description of numerous different embodiments, it should be understood that the legal scope of the description is defined by the words of the claims set forth at the end of this patent. The detailed description is to be construed as exemplary only and does not describe every possible embodiment since describing every possible embodiment would be impractical, if not impossible. Numerous alternative embodiments could be implemented, using either current technology or technology developed after the filing date of this patent, which would still fall within the scope of the claims. 
     It should also be understood that, unless a term is expressly defined in this patent using the sentence “As used herein, the term  ——————  is hereby defined to mean . . . ” or a similar sentence, there is no intent to limit the meaning of that term, either expressly or by implication, beyond its plain or ordinary meaning, and such term should not be interpreted to be limited in scope based on any statement made in any section of this patent (other than the language of the claims). To the extent that any term recited in the claims at the end of this patent is referred to in this patent in a manner consistent with a single meaning, that is done for sake of clarity only so as to not confuse the reader, and it is not intended that such claim term be limited, by implication or otherwise, to that single meaning. Finally, unless a claim element is defined by reciting the word “means” and a function without the recital of any structure, it is not intended that the scope of any claim element be interpreted based on the application of 35 U.S.C. §112, sixth paragraph. 
       FIG. 1  is a flowchart of a method, routine, or process  100  for compilation and presentation of a customer satisfaction dashboard. The method  100  may be performed on one or more computers, such as the computer system illustrated in  FIG. 3 . A system may receive survey data for a particular company (block  102 ). The survey data may be the result of telephone surveys performed by an outside agency, live interviews for example, at a mall, surveys administered by a company&#39;s internal personal or administered via a web session. The data is most commonly in the form of responses to questions, where each question contributes to understanding the customer or consumer&#39;s perspective on a particular topic. Exemplary questions may be targeted to areas such as price, responsiveness, brand reputation, etc. 
     While the survey data may include customers of a particular company, that is, persons purchasing a product or service from a company (e.g., an insurance or financial service company), that is not always the case. For example, in an automobile insurance business, a victim of a car accident may interact with an insurance company other than her own during the course of getting her car repaired. For the purpose of this description, the terms customer and consumer are interchangeable and are assumed to include these ‘casual’ or one-time business relationships. 
     After the survey results for a particular company are received, the results data may be broadly separated into two or more general areas. In an embodiment, the broad subject areas may be an experience area and an interaction area, with each area intended to reflect different aspects of a customer&#39;s impressions of the company. 
     In one embodiment, categories in the experience area may include price, responsiveness, reliability, availability, brand reputation, simple to do business with, caring, and personalized. The last three categories, simple to do business with, caring, and personalized, represent more or less subjective personal feelings about the customer&#39;s experience and may, in some cases, be combined separately into a single factor before being consolidated with the other experience data. 
     In the exemplary embodiment, the interaction area may include categories reflecting specific instances when the customer interacted with the company, and may include purchase, quote, policy change, billing/payment, and claims activity. 
     Each category may have several contributing factors to which questions may be directed during the survey process. In the experience area, each category may gather data based on the customer&#39;s impressions of following characteristics. 
     Price: Price compared to others, Satisfaction with price 
     Responsiveness: Responsive to questions or concerns 
     Reliability: Provides quality service, Follows through 
     Brand: Likelihood to be a customer in a year, Likelihood to recommend, Trustworthy, Good reputation as an auto insurer 
     Expertise: Ability to answer any question consumer may have Accuracy: Does things right the first time, Provides accurate information 
     Availability: Conduct business how I want, Conduct business when I want 
     A special factor is separately calculated and has the categories: 
     Simple: Easy to do business with, Easy to understand explanations 
     Caring: Listens to me and my concerns, Values and appreciates my business, Treats me with respect, Sees me as a person—not a number 
     Personalized: Knows me as a customer, Provides personalized service, Knows how to best communicate with me, Provides coverage to meet my needs 
     The interaction categories may have similar characteristics, but are generally more self explanatory. Typically, responses for both the experiences categories and the interaction categories are rated on a numerical scale, e.g., 1-5. The collected responses for a company, which may involve many thousands of surveys, may be averaged for each factor in its respective category, interaction (block  106 ) and experience (block  112 ). For example, 750 individual values for responsiveness may be averaged and given a 3.9 rating. Categories where more than one question may provide additional factor data, such as the two contributors to the price category in the exemplary embodiment above, may be averaged together. However, in other embodiments, they may be averaged separately and weighted before being combined into a single value for price. Weighting is discussed in more detail below. 
     When each interaction category has a value calculated, the interaction category values may be weighted to reflect each category&#39;s relative impact on customer satisfaction (block  106 ). In an exemplary embodiment, the interaction categories may be equally weighted, that is, all five categories are given equal weight. The interaction category values may be combined to develop an interaction score (block  110 ). 
     Similarly, when each experience category has a value calculated, the categories may be weighted (block  114 ). In an exemplary embodiment, the experience categories may be equally weighted. However, in another embodiment, the experience categories may be separately weighted to reflect each category&#39;s contribution to a customer&#39;s perception of the company. 
     One of many possible weightings of these categories applies weights as follows: 
     Price in a range of 0.15 to 0.25 (15%-25%); 
     Responsiveness in a range of 0.10 to 0.20 (10%-20%); 
     Reliability in a range of 0.10 to 0.20 (10%-20%); 
     Availability in a range of 0.05 to 0.15 (5%-15%); 
     Brand in a range of 0.05 to 0.15 (5%-15%); 
     Expertise in a range of 0.05 to 0.15 (5%-15%); 
     Accuracy in a range of 0.05 to 0.15 (5%-15%); and 
     Special factor in a range of 0.05 to 0.15 (5%-15%). 
     When calculating the special factor, its component categories may first be weighted where: 
     Simple-to-do-business-with in a range of 0.4 to 0.6 (40%-60%); 
     Caring in a range of 0.15 to 0.35 (15%-35%); and 
     Personalized in a range of 0.15 to 0.35 (15%-35%). 
     When selecting range values, the sum of the percentages should equal 100%, although that is not strictly necessary, as long as the weighting is done consistently across all companies that are to be compared. In practice, whether the data for each category is weighted first and then averaged or averaged first and then weighted is simply a design choice. 
     When the experience categories have been weighted, the weighted values may be combined to develop an experience score (block  116 ). In an embodiment, the interaction score and the experience scores may be a simple sum of the weighted category values. In other embodiments, the scores may be averages. However, by summing the category values, the scale is spread so that differences between companies can be noted without the use of multiple decimal places in the numerical scores and so is simply a convenience to make comparison easier. 
     To develop a composite score for a company, the experience score and the interaction score may be combined (block  118 ). Similar to above discussion, the composite score may be an average of the experience scores and the interaction scores. In other embodiments the composite score may be a simple sum of the two, or the composite score may be the result of a weighted combination of the two. 
     If there is data for another company (block  120 ), the process returns via the ‘yes’ branch from block  120  and repeats for each company for which there is data. If there is no data for any other company, the ‘no’ branch from block  120  is followed. 
     The experience scores, the interaction scores, and the composite scores, by company, may be rendered into a graphical form suitable for presentation (block  122 ), for example, via a web browser. In an embodiment, the composite score for each company is separately shown in a shape including a company identifier. The experience score and the interaction score may be illustrated in separate shapes with a connector to the composite score. When scores for a plurality of companies is available, a final metric may be developed as the average of experience scores, interaction scores, and composite scores to reflect an industry or segment average. A single image with all companies and industry scores may be rendered or each company may be rendered separately. 
     When requested, the rendered image or images may be displayed via a computer (i.e., a server, a laptop computer, an iPad or other tablet, a smart phone or any other computing device) (block  124 ). See, e.g.,  FIG. 2 ,  FIG. 2  illustrates an image rendered for display, for example, at block  122  showing an exemplary customer satisfaction dashboard  140 . The customer satisfaction dashboard  140  may include company-specific composite scores  142   a ,  142   b , and  142   c . Each company-specific composite score may be illustrated with its respective component scores, in this example, experience scores  144   a ,  144   b ,  144   c  and interaction scores  146   a ,  146   b ,  146   c . Also illustrated in  FIG. 2  is an industry composite score  148  and its component experience score  150  and interaction score  152 . As illustrated in this example, the industry score is the average of the scores for the other three companies, although more or less than three companies may be represented in some industries or business segments. The customer satisfaction dashboard  140  provides a single-look comparison between companies and a summary breakdown of the major factors contributing to the company and overall scores. When used over time, the dashboard  140  provides a mechanism to track changes in customer sentiment and to evaluate the impact of customer-facing programs, such as advertising. 
       FIG. 3  is a flow chart illustrating a method, routine, or process  170  for developing a customer satisfaction dashboard, such as customer satisfaction dashboard  140  of  FIG. 2 . The process  170  may involve identifying categories relevant to a business or industry that is to be measured (block  172 ). The consumer or customer attitudes or impressions may be identified or developed based on the responses to the various survey instruments (block  174 ). For example, to determine a consumers impression of a company&#39;s responsiveness, a series of questions may be developed such as, the company: 
     responds to questions and requests quickly. 
     follows through on what they say they will do. 
     is committed to serving customers&#39; needs. 
     follows through on promises made to customers. 
     completes tasks successfully. 
     The development of this kind of instrument is a science of its own and is beyond the scope of the current disclosure. When the categories are defined, additional studies may be performed that evaluate how a particular category contributes to the customer&#39;s overall view of the company. Based on those studies, weighting factors for each category may be developed (block  176 ). These weighting factors may be applied during the generation of the customer satisfaction dashboard, as discussed above. 
       FIG. 4  illustrates various aspects of an exemplary architecture  200  implementing a customer satisfaction dashboard. The high-level architecture includes both hardware and software applications, as well as various data communications channels for communicating data between the various hardware and software components. In an embodiment, survey results  224  may be received from a third party survey company or an internal department responsible for customer and consumer research. The survey results storage  224  may be a part of a data server  222  or may be a separate server with independent memory. 
     In another embodiment, survey results may be received from a number of web-enabled devices  210  via a web server  202  connected over a network  204 . These devices may include by way of example, a smart-phone  212 , a web-enabled cell phone  214 , a tablet computer  216 , a personal digital assistant (PDA)  218 , or a laptop/desktop computer  220 . In some instances, the web enabled devices  210  may communicate with the network  204  via wireless signals  208  and, in some instances, may communicate with the network  204  via an intervening wireless or wired device  206 , which may be a wireless router, a wireless repeater, a base transceiver station of a mobile telephony provider, etc. In most cases, the network  204  may be the Internet, using an Internet Protocol, but other networks may also be used. 
     The web server  202  may be implemented in one of several known configurations via one or more servers configured to process web-based traffic received via the network  204  and may include load balancing, edge caching, proxy services, authentication services, etc. 
     The data server  222  may be connected to the web server  202  via a network  226  and may implement the processes described above for compiling, weighting, and displaying the customer satisfaction dashboard. 
     The data server  222  includes a controller  228 . The controller  228  includes a program memory  232 , a microcontroller or a microprocessor (μP)  238 , a random-access memory (RAM)  240 , and an input/output (I/O) circuit  230 , all of which are interconnected via an address/data bus  244 . In some embodiments, the controller  228  may also include, or otherwise be communicatively connected to, a database  242  or other data storage mechanism (e.g., one or more hard disk drives, optical storage drives, solid state storage devices, etc.). The database  242  may include data such as customer questionnaires, if not implemented in the web server  202 , etc. The database  242  may also include customer/consumer profile information for use in segmenting data, questions, categories, weighting by business and/or industry. It should be appreciated that although  FIG. 4  depicts only one microprocessor  238 , the controller  228  may include multiple microprocessors  238 . Similarly, the memory  232  of the controller  228  may include multiple RAMs  234  and multiple program memories  236 ,  236 A and  236 B storing one or more corresponding server application modules, according to the controller&#39;s particular configuration. The data server  222  may also include specific routines to render the data into an image for display by a client computer (not depicted) or any of the web devices  210  via web server  202 . 
     Although  FIG. 4  depicts the I/O circuit  230  as a single block, the I/O circuit  230  may include a number of different types of I/O circuits (not depicted), including but not limited to, additional load balancing equipment, firewalls, etc. The RAM(s)  234 ,  240  and the program memories  236 ,  236 A and  236 B may be implemented in a known form of computer storage media, including but not limited to, semiconductor memories, magnetically readable memories, and/or optically readable memories, for example, but does not include transitory media such as carrier waves. 
     To the extent that any meaning or definition of a term in this document conflicts with any meaning or definition of the same term in a document incorporated by reference, the meaning or definition assigned to that term in this document shall govern. The detailed description is to be construed as exemplary only and does not describe every possible embodiment since describing every possible embodiment would be impractical, if not impossible. Numerous alternative embodiments could be implemented, using either current technology or technology developed after the filing date of this patent, which would still fall within the scope of the claims. While particular embodiments of the present invention have been illustrated and described, it would be obvious to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. It is therefore intended to cover in the appended claims all such changes and modifications that are within the scope of this invention.