2.8. Use the Correct Technology to Make the Survey Process Efficient

Many companies can provide a range of services to assist with the implementation of a customer satisfaction program. Choosing the right supplier is crucial to ensuring that such an initiative is carried out with business value objectives as the primary focus.

A quality survey solution should be able to streamline the integration of many of the aforementioned best practices into your current business processes.

Some things to look for in a survey solution:

• An actual database of customer knowledge that dynamically serves as a central repository for all your customer information (survey history, transactional history, etc.)
• Real-time email alerts to address customer issues immediately
• Question scoring to use variable weighting on different dimensions of customer satisfaction
• An easy-to-use interface with a manageable learning curve
• Pre-survey consultation with real consultants and survey experts—not just software—that will ensure your deployment is on the right track

Once you have conducted your customer satisfaction survey, you need to collect and collate customer satisfaction data into a report according to organisational requirements.

When dealing with a stack of survey responses, it can be difficult to draw conclusions from your findings by simply reading through each survey in the pile. Using a filter system to break up responses by particular criteria can save time and effort when analysing data. 

• Determine the underlying purpose of your survey. Without this information, you cannot choose the correct lens through which to examine your survey results. If you are a business conducting a customer survey, you might look for feedback on your customer service, additional products your customers would be interested in, or areas in which you can improve an existing product. If your group runs a follow-up survey after an event, you’ll want to check the results to see how you did, what you can add, and what you can improve upon. Of these commonly requested feedback areas, identify which is most important to you, whether you simply want to see if people would use your service again or if you are actively looking for new features to add.

• Identify which, if any, questions on your survey directly address your purpose. If you want to focus on customer satisfaction, look for a question such as “Would you buy this product again or recommend it to a friend?” If your survey includes several questions related to your purpose, determine which is the most simple statement of your purpose.

• Divide your survey results based on respondents’ answers to your most purpose-connected question, as identified above. For multiple-choice questions, simply separate the results into a different pile for each answer choice. Short-answer or long-response questions should be divided into categories based on the general theme of the answer–positive, negative, or middling–or by different suggestions if you are focused on new products or features.

• Identify the demographic division that bears the most weight on the purpose of your survey. It can be related to age, income, or geography, or an issue more specific to your product or service, such as whether the customer is a first-time or repeat user.

• Find a question related to the demographic of your survey audience on your survey. This is often the first question of a customer or event attendance survey: asking respondents whether this is their first or repeat experience. Otherwise, you may find demographic questions grouped at the end of a survey, asking respondents to choose a box for their age or income range or city or state of residence.

• Subdivide your first set of piles by responses to the demographic question identified in the previous step. This allows you to see whether a particular set of respondents overwhelmingly falls into a certain response category for your main purpose-oriented question.

Marketing and management are prone to looking at things like mean, median, confidence intervals, and so on. They’re – presumably – looking at data analysis, trying to discover within the data if there is anything they can do to help the customers become more satisfied.

However, the data averages are not as important to the employees who work at the lower levels – the ones that deal directly with the customer. These employees don’t understand how things like averages affect them, and may not really get the gravity of the data. It is for that reason you may want to change the way you present data when you are bringing it to the employees, turning it into data that is easily understood and can help shape their opinions of managing the customers.

How to Present the Data – An Example

One of the ways that was suggested was to present data using explanations of the numbers, and breaking it out into categories. Such as “34% of all customers indicated that their current satisfaction levels were “slightly dissatisfied or worse.” This will help give them a baseline for where they need to improve, and something to shoot for when it comes to improving their satisfaction efforts. You can also break out those numbers further, explain what you would like them to do to improve those numbers, and indicate goals that may help them improve (as well as rewards for their efforts).

Making the Data Easy to Understand – in Ways that Can Be Replicated

There are many different ways to present data, but when you are showing it to the employees who deal directly with the customers, it is important to find a way that is extremely easy to understand and can also be replicated to show employees whether or not they have reached their goals. That is the best way to get noticeable changes within the company and make the data important to anyone who reads it.

The following types of measures are expected to be reported regarding customer satisfaction: 

• Overall satisfaction: Report the average overall satisfaction rating from all respondents of a customer satisfaction survey. Management would derive this from an “overall satisfaction” question, for example, “Overall, how satisfied are you with this service?” In addition, agencies should present the distribution of overall satisfaction scores across the scale – of all responses, what percent were equal to 1, 2, 3, 4, and 5. 
• Key drivers of satisfaction: Determine key drivers of satisfaction for their products or services – those aspects of the customer experience that most influence overall satisfaction – through customer research such as focus groups and surveys, or through historical program information. Businesses should then use their customer satisfaction survey to get customer feedback on key drivers of satisfaction. As with overall satisfaction, agencies should report results as average ratings and distribution of responses across the scale. 
• Key performance measures: These measures are additional objective data selected by the business to provide context to the data gathered via surveys. They should relate to the key drivers of satisfaction identified by the agency. These measures are not derived from their customer satisfaction surveys but come from company records, documentation, and performance management systems.

Some examples of key performance measures include:

• Objective data on actual reported safety incidents vs. perception of safety derived  from surveys 
• Objective data on timeliness vs. perception of timeliness derived from surveys

Once data have been collected and analysed, departments will compare against performance targets for each measure and show trends when possible. 

After the customer survey has been designed and administered and the survey results analysed to provide insight into customer beliefs, the most important part of the customer satisfaction process can begin:  Finding ways to use the survey results and insights throughout your operational and management practices.