VOC Data collecting tools

VOC Data collecting tools

To identify the key drivers of customer satisfaction. It is only through understanding your customers’ thought processes while they are making their purchasing decisions and while they are using your products or services that you can effectively design, deliver, and improve them. The term voice of the customer, or VOC, is used to describe your customers’ needs and their perceptions of the quality of your products or services. What does it do?

• Properly focuses your improvement project
• Provides data to help you develop appropriate measurements
• Helps the team decide what products and services to offer
• Identifies critical features for those products and services, known as Critical-To-Quality characteristics, or CTQs
• Provides a baseline measure of customer satisfaction against which to measure improvement
• Identifies the key drivers of customer satisfaction

Step involved in collecting Data For Voice of Customer (VOC)

1. Identify your customers and what you need to know about their needs.
   • In a SIPOC (Suppliers, Inputs, Process, Outputs, and Customers) context, a customer is anyone who uses or benefits from the output of your process.
     • One of your customers is the next step that occurs in a process after the process delivers an output.
     • Only your customer can define what a defect is.
   • In a marketing context, the term customer is usually restricted to the people and groups outside an organization who purchase and/or use a company’s products or services.
   • Ask yourself the following questions:
     • What are the outputs of our process? Who are the customers of that output?
     • Are there particular groups of customers whose needs are especially important to our organization?
2. You must decide which of the above definitions of customer makes more sense for your project. Often it helps to use both definitions—that is, you work primarily with the people involved with the next process step, but you check to ensure that their needs are consistent with the needs of the final customer. Keep in mind the following points:
   • The final customer, or end user, might be far removed from your particular job, but their needs are still important to you (and to everyone else in your organization).
   • You might have multiple customers (and thus multiple needs to consider).
   • If you work on administrative processes, your  customers might include your suppliers. For example, a supervisor who supplies you with information that you incorporate into a report for him/her is your customer.
3. As you work to identify your customers, check with your sponsor(s) and your marketing staff to see if there are large or influential customers whom you should make sure not to overlook.
4. Often there is no single VOC. Different customers or types of customers usually have different needs and priorities. You should include a wide variety of customers in your initial customer- research efforts. Different types of customers are often referred to as market segments.
5. Decide what you need to know about your customers.
   • Revisit your charter. What is the purpose of your project?
   • How does this purpose relate to the needs of the customers you have identified? What do you need to know about these customers’ needs to make sure your project purpose is on track?
6. Collect and analyze reactive system data; then fill any gaps with proactive approaches. There are two types of data-collection systems: reactive and proactive.
   1. Reactive systems involve information that you receive whether or not you take any action to obtain it.
      • Reactive systems are customer-initiated. Some examples are complaints, returns, credits, and warranty claims.
      • It is best to start your data-collection process with reactive data because it is usually easier to get and can give you a basic understanding of customer concerns, allowing you to better focus
        your proactive work.
      • Reactive systems generally gather data about the following:
        • Current and former customer issues or problems.
        • Current and former customers’ unmet needs.
        • Current and former customers’ interest in particular products or services.
      • Sometimes customers communicate with you when they have a problem, but other times they let their behavior do the talking. Also, they often don’t think of a problem they have as a problem that your organization can solve. Rather, they might blame themselves for the product or service not working right, think they have the wrong product or service, or simply take their business elsewhere. Reactive systems help you capture all the ways in which customers communicate their needs. It is important to explore this often-underused source of information before making an effort to gather new information. You can learn a great deal about improving your existing products and services if you put extra effort into categorizing and analyzing data from reactive systems and reviewing them periodically to identify patterns, trends, and other opportunities. Tip Feedback from customers is easily lost. Extra effort must be made to preserve as much of this information as possible.
   2. Proactive systems involve taking action to gather information.
      • Proactive systems are not customer-initiated. Some examples are market research, customer interviews, and surveys.
      • Follow up on the information you obtain to expand your understanding of your customers’ needs and to quantify the importance they place on various product/service characteristics.
      • Proactive systems are those in which you initiate contact with customers. Ideally, they involve some face-to-face interviews or customer-site visits. Typically they also involve telephone interviews or surveys and/or questionnaires that customers fill out and return to your organization. You will likely have to design and initiate targeted customer contact to gather information specifically related to your project. Look for ways to integrate your efforts with ongoing customer contact done by your organization. For example, request that customer service or marketing staff ask additional questions during their regular contacts
        with customers, or see if your customers will allow you to observe their workplace during a scheduled visit.
7. Analyze the data you collect to generate a key list of customer needs in their language. Much of this data will be verbal. It is helpful to summarize this information in a meaningful way, perhaps by using an Affinity Diagram.
8. Use an Affinity Diagram, a CTQ Tree, and the Kano Model to prioritize the CTQs for your project.

Instruments to Gather Data

There are instruments or tools available to everyone for the purposes of collecting customer information. Some of the common instruments are described below:

• Surveys:  A properly designed questionnaire gathers data using a consistent set of standardized questions. Usually, a sample is selected for use. Interviewers can be used or it can be self-administered.
•  Focus groups: A small group (3 to 12 typically) of individuals is assembled to explore specific topics and questions. A time period of 1 to 2 hours is normally required.
• Face-to-face interviews: Individual interviews of 30- 60 minutes in length may be used. This can be very time-consuming.
• Satisfaction/complaint cards: The return of a card prompts a reaction by the company. These could function as feedback forms.
• Dissatisfaction sources: Some methods that voice dissatisfaction include: complaints, claims, refunds, recalls, returns, repeat service work, litigation replacements, downgrades, warranty work, mis-shipments, etc.
• Competitive shoppers: Shoppers evaluate a company and competitors. CEOs may call their own offices to measure the ease of customer access.

SURVEYS AND FOCUS GROUPS

There are a number of reasons why a firm may wish to communicate with its customers. A primary reason is the evaluation of the customer’s perception of the firm’s product and service quality and its impact on customer satisfaction. The purpose may be to get an idea of the general condition of quality and satisfaction, or a comparison of the current levels with the firm’s goals. A firm might wish to conduct employee surveys and focus groups to assess the organization’s quality structure. There are four primary strategies commonly used to obtain information from or about customers and employees: sample surveys, case studies, field experiments, and available data.
With sample surveys, data are collected from a sample of a universe to estimate the characteristics of the universe, such as their range or dispersion, the frequency of occurrence of events, or the expected values of important universe parameters. This is the traditional approach to such surveys. However, if survey results are collected at regular intervals, the results can be analyzed using quality control tools to obtain information on the underlying process. The process excellence leader should not be reticent in recommending that survey budgets be allocated to conducting small, routine, periodic surveys rather than infrequent ‘‘big studies.’’ Without the information available from time-ordered series of data, it will not be possible to learn about processes that produce changes in customer satisfaction or perceptions of quality.
A case study is an analytic description of the properties, processes, conditions, or variable relationships of either single or multiple units under study. Sample surveys and case studies are usually used to answer descriptive questions (‘‘How do things look?’’) and normative questions (‘‘How well do things compare with our requirements?’’). A field experiment seeks the answer to a cause-and-effect question (‘‘Did the change result in the desired outcome?’’). Use of available data as a strategy refers to the analysis of data previously collected or available from other sources. Depending on the situation, available data strategies can be used to answer all three types of questions: descriptive, normative, and cause-and-effect. Original data collection strategies such as mail questionnaires are often used in sample surveys, but they may also be used in case studies and field experiments. Research on customer satisfaction can be worthwhile in helping the company’s efforts. Customer satisfaction research was a $2 billion industry in the United States. The objectives of customer research very, but a few major themes are noted below:

• To determine what quality is
• Find out what competitors are doing
• Define quality performance measures for use
• Identify factors to give a competitive edge
• Identify urgent problems

Customer Surveys

In the evaluation of customer information, not all attributes and transactions should be treated equally. Some are much more important than others. As customers’ needs change, the evaluations will change. Griffin conducted a study on the best customer satisfaction practices and recommended the use of multiple instruments to collect customer satisfaction data. Validation of the initial results can be accomplished via multiple measurements.
Perceived quality and satisfaction must be measured. Perceived quality is evaluated through experience (cumulative) and value received (including costs).

Customer survey sample sizes and frequency can have significant cost implications and should be chosen to balance business resources and the need to monitor changes in the business environment. Breyfogle suggests dividing the customer survey sample into 12 monthly sub-samples that are conducted on a rotating basis. This can provide both good long-term precision and good short-term sensitivity to changes in customer attitudes. Surveys can be developed in questionnaire form. An adequate number would range from 25 to 30 questions. For an L-Type matrix survey, the use of a numerical scale. from 1 (very dissatisfied) to 10 (very satisfied) can make it easier to quantify the
results, as shown in Figure below. Breyfogle recommends using questions that measure relative changes in customer attitudes from one survey period to the next, or from one product to another. He suggests using a Likert scale to evaluate changes in customer attitudes and determine shifts in the business environment.

GUIDELINES FOR DEVELOPING QUESTIONS

The axiom that underlies the guidelines shown below is that the question writer(s) must be thoroughly familiar with the respondent group and must understand the subject matter from the perspective of the respondent group. There are eight basic guidelines for writing good questions:

1. Ask questions in a format that is appropriate to the questions purpose and the information required.
2. Make sure the questions are relevant, proper, and qualified as needed.
3. Write clear, concise questions at the respondent’s language level.
4. Give the respondent a chance to answer by providing a comprehensive list of relevant, mutually exclusive responses from which to choose.
5. Ask unbiased questions by using appropriate formats and item constructions and by presenting all important factors in the proper sequence.
6. Get unbiased answers by anticipating and accounting for various
   respondent tendencies.
7.  Quantify the response measures where possible.
8. Provide a logical and unbiased line of inquiry to keep the reader’s attention and make the response task easier.

There are several commonly used types of survey responses.

• Open-ended questions: These are questions that allow the respondents to frame their own response without any restrictions placed on the response. The primary advantage is that such questions are easy to form and ask using natural language, even if the question writer has little knowledge of the subject matter. Unfortunately, there are many problems with analyzing the answers received to this type of question. This type of question is most useful in determining the scope and content of the survey, not in producing results for analysis or process improvement.
• Fill-in-the-blank questions: Here the respondent is provided with directions that specify the units in which the respondent is to answer. The instructions should be explicit and should specify the answer units. This type of question should be reserved for very specific requests, e.g., ‘‘What is your age on your last birthday?_____________ (age in years).’’
• Yes/No questions: Unfortunately, yes/no questions are very popular. Although they have some advantages, they have many problems and few uses. Yes/no questions are ideal for dichotomous variables, such as defective or not defective. However, too often this format is used when the measure spans a range of values and conditions, e.g., ‘‘Were you satisfied with the quality of your new car (yes/no)?’’ A yes/no response to such questions contains little useful information.
•  Ranking questions: The ranking format is used to rank options according to some criterion, e.g., importance. Ranking formats are difficult to write and difficult to answer. They give very little real information and are very prone to errors that can invalidate all the responses. They should be avoided whenever possible in favor of more powerful formats and formats less prone to error, such as rating. When used, the number of ranking categories should not exceed five.
•  Rating questions: With this type of response, a rating is assigned on the basis of the score’s absolute position within a range of possible values. Rating scales are easy to write, easy to answer, and provide a level of quantification that is adequate for most purposes. They tend to produce reasonably valid measures. Here is an example of a rating format:

• Guttman format: In the Guttman format, the alternatives increase in comprehensiveness; that is, the higher-valued alternatives include the lower-valued alternatives. For example,

• Likert and other intensity scale formats: These formats are usually used to measure the strength of an attitude or an opinion. For example:

Intensity scales are very easy to construct. They are best used when respondents can agree or disagree with a statement. A problem is that statements must be worded to present a single side of an argument. We know that the respondent agrees, but we must infer what he believes. To compensate for the natural tendency of people to agree, statements are usually presented using the converse as well, e.g., ‘‘The customer service representative was not knowledgeable.’’
When using intensity scales, use an odd-numbered scale, preferably with five or seven categories. If there is a possibility of bias, order the scale in a way that favors the hypothesis you want to disprove and handicaps the hypothesis you want to confirm. This way you will confirm the hypothesis with the bias against you will give you a stronger result. If there is no bias, but the most undesirable choices First.

• Semantic differential format: In this format, the values that span the range of possible choices are not completely identified; only the end points are labeled. For example,
• 

Example-of-survey-questions

Surveys are a method to gather data, but care should be taken with that data. A well-designed and properly executed survey can be a help to the company. The survey can show what resources do not satisfy customers, identify opportunities for growth or correction, and focus on customer issues. However, there can be problems with the use of surveys:

• Improper survey form design
• Poorly defined survey issues
• Sampling errors or poor sampling techniques
•  Ignoring non responses
• Treating customer perceptions as objective measures
• Using incorrect analysis methods
• Treating surveys as an event, not a process
• Asking nonspecific questions
• Failing to ask the right questions
• Ignoring the results or using them incorrectly
• Failing to provide feedback when necessary
• Using too many questions (25-30 questions are typical)
• Using a temporary employee to conduct interviews

Focus groups

The focus group is a special type of group in terms of purpose, size, composition, and procedures. A focus group is typically composed of seven to ten participants who are unfamiliar with each other. These participants are selected because they have certain characteristics in common that relate to the topic of the focus group. The researcher creates a permissive environment in the focus group that nurtures different perceptions and points of view, without pressuring participants to vote, plan, or reach consensus. The group discussion is conducted several times with similar types of participants to identify trends and patterns in perceptions. Careful and systematic analyses of the discussions provide clues and insights as to how a product, service, or opportunity is perceived. A focus group can thus be defined as a carefully planned discussion designed to obtain perceptions on a defined area of interest in a permissive, non-threatening environment. The discussion is relaxed, comfortable, and often enjoyable for participants as they share their ideas and perceptions. Group members influence each other by responding to ideas and comments in the discussion. Focus groups are useful in a variety of situations:

• prior to starting the strategic planning process
•  generate information for survey questionnaires
•  needs assessment, e.g., training needs
•  test new program ideas
•  determine customer decision criteria
•  recruit new customers

FOCUS GROUP ADVANTAGES

The focus group is a socially-oriented research procedure. The advantage of this approach is that members stimulate one another, which may produce a greater number of comments than would individual interviews. If necessary, the researcher can probe for additional information or clarification. Focus groups produce results that have high face validity, i.e., the results are in the participant’s own words rather than in statistical jargon. The information is obtained at a relatively low cost and can be obtained very quickly.

FOCUS GROUP DISADVANTAGES

There is less control in a group setting than with individual interviews. When group members interact, it is often difficult to analyze the resulting dialogue. The quality of focus group research is highly dependent on the qualifications of the interviewer. Trained and skilled interviewers are hard to find. Group to group variation can be considerable, further complicating the analysis. Finally, focus groups are often difficult to schedule.

Complaint handling

When a customer complaint has been received it represents an opportunity to increase customer loyalty, and a risk of losing the customer. The way the complaint is handled is crucial. The importance of complaint handling is illustrated in Figure below. These data illustrate that the decision as to whether a customer who complains plans to repurchase is highly dependent on how well they felt their complaint was handled. Add to this the fact that customers who complain are likely to tell as many as 14 others of their experience, and the importance of complaint handling in customer relations becomes obvious. Despite it’s impressive nature, even these figures dramatically understate the true extent of the problem. Complaints represent people who were not only unhappy, they notified the company. Research indicates that up to 96% of unhappy customers never tell the company. This is especially unfortunate since it has been shown that customer loyalty is increased by proper resolution of complaints. Given the dramatic impact of a lost customer, it makes sense to maximize the opportunity of the customer to complain. Complaints should be actively sought, an activity decidedly against human nature. This suggests that a system must be developed and implemented to force employees to seek out customer complaints. In addition to actively soliciting customer complaints, the system should also provide every conceivable way for an unhappy customer to contact the company on their own, including toll-free hotlines, email, comment cards, etc.

Other customer information systems

•  Complaint and suggestion systems typically provide all customers with an easy-to-use method of providing favorable or unfavorable feedback to management. Due to selection bias, these methods do not provide statistically valid information. However, because they are a census rather than a sample, they provide opportunities for individual customers to have their say. These are moments of truth that can be used to increase customer loyalty. They also provide anecdotes that have high face validity and are often a source of ideas for improvement.
• Customer panels are composed of a representative group of customers who agree to communicate their attitudes periodically via phone calls or mail questionnaires. These panels are more representative of the range of customer attitudes than customer complaint and suggestion systems. To be effective, the identity of customers on the panel must be withheld from the employees serving them.
•  Mystery shoppers are employees who interact with the system as do real customers. The identity of the mystery shopper is withheld from employees.

Customer Data Analysis

Once customer feedback has been obtained, it must be used to improve the process and product quality. A system for utilizing customer feedback is as shown

1.  Local managers and employees serve customers’ needs on a daily basis, using locally modi¢ed procedures along with general corporate policies and procedures.
2. By means of a standardized and locally sensitive questionnaire, determine the needs and attitudes of customers on a regular basis.
3.  Comparing financial data, expectations, and past attitude information, determine strengths and weaknesses and their probable causes.
4.  Determine where and how effort should be applied to correct weaknesses and preserve strengths. Repeat the process by taking action as in step 1 and maintain it to attain a steady state or to evolve in terms of customer changes.
5.  A similar process can take place at higher levels, using aggregated data from the field and existing policy flows of the organization.

Although this system was developed by marketing specialists, note that it incorporates a variation of the classical Shewhart quality improvement PDCA (Plan-Do-Check-Act) cycle

The customer data is analyzed in order to determine when and where customer attitudes are different or are changing. Comparing customer attitudes over time or between groupings can provide insights into market niches and changes. The results of customer feedback data collection can be analyzed using a variety of tools:

Statistical tests: A large number of non-parametric tests and contingency tables can be used to determine, with identified confidence levels, whether customer preferences have shifted. In addition, most normal statistical tests may be used on many of the numerical survey results such as the Likert scale (0-5 or 0-10 ranking) surveys described earlier.

1. Line graphs: Line graphs can graphically show whether either discrete or continuous characteristics of a product or service are changing. In most cases, a visual assessment can be made to determine if the product or service is getting better, worse, or staying the same.
2. Control charts: A variety of variable or attribute charts can also be used to display  customer feedback data. This tool offers an advantage over line charts because the addition of calculated control limits facilitates the ability to detect special or assignable causes of variation.
3. Matrix diagrams: A variety of matrix diagrams can be used for examination of customer defects or complaints. Data from matrix diagrams can be used to create a Pareto chart or can be used directly for project selection, where a large number of occurrences are noted.
4. Pareto analysis:  Snapshots of customer defects or rejects (Pareto charts) can be  displayed at selected time intervals to answer such questions as: Are reject categories still of the same magnitude? Are reject categories still in the same sequence of magnitude?
5. Other comparative analyses: The comparative Pareto analysis illustrated above is a powerful tool for analyzing customer data. In the same way, other charts (control charts, line graphs, histograms, and even matrix diagrams) can be compared from one time period to another, from one supplier to another, etc. to provide real insight into the needs of the customer and the changes in the market. Visual comparisons, however, are risky. A significance test may be required.

KANO MODEL OF CUSTOMER EXPECTATIONS

Customer expectations, priorities, needs, and  ‘‘voice’’. Although customers seldom spark true innovation  (for example, they are usually unaware of state-of-the-art developments), their input is extremely valuable. Obtaining valid customer input is science itself. Market research firms use scientific methods such as critical incident analysis, focus groups, content analysis, and surveys to identify the ‘‘voice of the customer.’’ Noritaki Kano developed the following model of the relationship between customer satisfaction and quality. The Kano model shows that there is a basic level of quality that customers assume the product will have. For example, all automobiles have windows and tires. If asked, customers don’t even mention the basic quality items, they take them for granted. However, if this quality level isn’t met the customer will be dissatisfied; note that the entire ‘‘Basic Quality’’ curve lies in the lower half of the chart, representing dissatisfaction. However, providing basic quality isn’t enough to create a satisfied customer. The ‘‘Expected Quality’’ line represents those expectations that customers explicitly consider. For example, the length of time spent waiting in line at a checkout counter. The model shows that customers will be dissatisfied if their quality expectations are not met; satisfaction increases as more expectations are met. The ‘‘Exciting Quality’’ curve lies entirely in the satisfaction region. This is the effect of innovation. Exciting quality represents unexpected quality items. The customer receives more than they expected. For example, Cadillac pioneered a system where the headlights stay on long enough for the owner to walk safely to the door. When first introduced, the feature excited people. Competitive pressure will constantly raise customer expectations. Today’s exciting quality is tomorrow’s basic quality. Firms that seek to lead the market must innovate constantly. Conversely, firms that seek to offer standard quality must constantly research customer expectations to determine the currently accepted quality levels. It is not enough to track competitors, since expectations are influenced by outside factors as well. For example, the quality revolution in manufacturing has raised expectations for service quality as well.

Kano Model

• Helps to describe which needs, if fulfilled, contribute to customer dissatisfaction, neutrality, or delight
• Identifies the “Must Be” needs, which are those that the customer expects. If they are unfulfilled, the customer is dissatisfied; however, even if they are completely fulfilled, the customer is not
  particularly satisfied. An example of a Must Be need is airline safety.
•  Identifies the “More Is Better” needs, which are those that have a linear effect on customer satisfaction: The more these needs are met, the more satisfied customers are. An example is inexpensive airline tickets.
•  Identifies “Delighter” needs, which are those that do not cause dissatisfaction when not present but satisfy the customer when they are. An example is serving hot chocolate chip cookies during an airline flight.
•  Assists in the prioritization of needs—for example, Must Be needs are generally taken for granted unless they are absent. Take care of these needs first.

Steps involved  preparing  Kano Model

1. Gather sorted customer needs from the Customer – Data Affinity Diagram.

2. Review the themes from the Affinity Diagram and sort them into the three categories in the Kano Model (Must Be, More Is Better, and Delighters)
3. If there are very few or no needs listed in one of the categories, collect additional customer data. Customers generally cannot articulate what their basic expectations are or what would delight them. Therefore, when you prioritize customer needs based on what they say is important, you must remember that generally, they will identify only More Is Better characteristics. You must use other means—such as direct observation of customer use—to identify and set priorities for Must Be characteristics and Delighters.
4. After you have collected additional data, return to the Kano categories and complete the sorting of customer needs
5. Prioritize the customer needs you will use when you develop CTQs
6. First work on any Must Be characteristics that, if absent, would create customer dissatisfaction. Consider the importance of More Is
Better characteristics to provide steady and strong increases in satisfaction, and include in your priorities a few Delighters that will increase satisfaction dramatically. Also, consider how these categories relate to your company’s competitive advantage. Customer needs change over time. A Delighter today might be a Must Be tomorrow. In addition, different customer segments might have different needs.

For example, a business traveler might consider a hotel-room iron a Must Be and the size of the desk’s work surface a More Is Better. A family traveling on vacation, on the other hand, might consider free movies and video games a More Is Better characteristic.

Critical to Quality (CTQ) Tree

Critical to Quality(CTQ) focuses on the key metrics of customer satisfaction. A CTQ tree will translate the initial customer requirements to numerical or quantified requirements for the product or service. These are the detailed critical requirements for the organization to satisfy. These can be regarded as key results of the process. The development of a CTQ tree would go from the general requirement to the specific, or from “hard to measure” to “easy  to measure.”It helps identify Critical To Quality (CTQ) characteristics, features by which customers evaluate your product or service and that can be used as measures for your project. A useful CTQ characteristic has the following features:

•  It is critical to the customer’s perception of quality.
•  It can be measured.
•  A specification can be set to tell whether the CTQ characteristic has been achieved.
• CTQ Tree links customer needs gathered from your voice of the customer (VOC) data-collection efforts with drivers and with specific, measurable characteristics
• CTQ Tree enables the project team to transform general data into specific data
•  CTQ Tree makes the measuring process easier for the team

The creation of CTQ involves the following steps

1. Gather sorted customer needs from your data collection process. The needs you use in the CTQ Tree can include the themes or  specific needs from a Customer-Data Affinity Diagram
2. List the major customer needs from the Customer-Data Affinity Diagram on the left side of the CTQ Tree
3. . Try to view each need from the customer’s point of view. As you consider each need, ask, “What would that mean?” from the customer’s standpoint. Each answer becomes a driver for the CTQs. Keep asking, “What would that mean?” until you reach a level where it would be absurd to continue. Your answers at this level are the CTQs.
4.  Validate the requirements with the customer to ensure that key requirement are know to them

Example:

•  “Good customer service” means “knowledgeable reps.”
• “Knowledgeable reps” means the answers they give are correct.
•  It would be absurd to ask what “correct answers” means, so you should stop at this point. “Correct answers” is an appropriate CTQ.

Perceptual Maps

The following steps describe how to determine the appropriate questions to help quantify and prioritize the needs of the customer.

• Conduct brainstorming sessions to identify a wish list of features and/or problem resolutions.
• Rank the brainstorming session items and consider the highest ranking items for possible customer survey questions.
•  Construct the set of questions, being careful not to bias responses on customer satisfaction or customer importance with the wording.
•  Collect a numerical ranking (e.g. 1-5 on both satisfaction and importance) for each item and plot them on a perceptual map.

In the Figure below, nine items are ranked from 1 to 5 in both customer importance and satisfaction and plotted on a perceptual map. In this example, items 3 and 7 are rated as very important but satisfaction is low. These items clearly need attention. Item 2 is not important, so the high satisfaction levels will not likely influence a customer’s purchase decision. Items 5, 6, and 9 appear to be relatively strong points that may influence purchase decisions.

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