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Survey methodologies

There are a number of methods of contacting customers to offer them the opportunity to complete a satisfaction survey:

Type Pros Cons
Outbound Phone
  • Easy to complete
  • Strong response rate
  • An expensive approach
Inbound Phone
  • Immediate response – Feedback tends to be more accurate
  • Good response rate
  • Inexpensive after initial cost to set up
  • Technical expertise required to programme IVR
  • Offering survey process needs to be automated to prevent staff ‘cherry-picking’ good calls
SMS
  • Immediate response – Feedback tends to be more accurate
  • Good response rate
  • Inexpensive after initial cost to set up
  • Can usually only ask a small number of questions (generally around 3)
  • Not great for collecting feedback
Email
  • Relatively cheap and easy to establish
  • Cost-effective to run continuously
  • Lower response rate than telephony options
  • Dependant on accurate email address captured
Direct Mail
  • Generally cheaper than telephony options
  • Can capture good, detailed feedback
  • More expensive than email
  • The response rate is very low
Web
  • Often used to ‘rate’ content
  • Useful for understanding the value of a website
  • Often used for email-based surveys
  • Requires internet awareness and may skew sample to a younger demographic
App-based
  • An emerging approach to surveys
  • Technically savvy
  • Cost-effective to run continuously
  • Still in its infancy but gaining popularity
  • Low take up with the older generation
  • Can be expensive to set up
In-Store
  • Paper-based survey (typical) or device-based survey (emerging)
  • Immediate and relevant feedback
  • Requires a store/retail outlet
  • Can be expensive to run and collect if paper-based

Lean Consulting recommends using the same communication method your customer used to contact you, where possible or practical.

Customer Survey

Survey Rating Approaches

There are a number of approaches for rating customer responses in a customer satisfaction survey. The most common error associated with survey ratings are imbalanced rating scales that skew the results in favour or against the survey unintentionally.

For example:

  • Above Expectations
  • Met Expectations
  • Below Expectations
  • No Opinion

In this example. there are 2 positive answers (Above Expectations & Met Expectations) and only 1 negative answer (Below Expectations). As a result steers customers to a positive answer, even when the reality may not be positive.

Perhaps the most common flawed scale in use today is:

  • 4 – Excellent
  • 3 – Good
  • 2 – Fair
  • 1 – Poor

Again, this creates an unbalanced scale by allowing 2 positive responses (Excellent and Good) 1 neutral response (Fair) and 1 negative response (Poor). Customers using this scale are more likely to feedback a positive score than negative, purely based on how the scale is created.

Customer Survey

Many surveys use a 1 to 10 scale but this does not provide a respondent with a clear neutral response as there are 5 negative and positive responses equally. A better alternative would be 0 to 10 scale with 5 being the neutral midpoint. Whilst this is a better approach, the excessive choice afforded by an 11 point scale can lead to inaccurate results.

Neither the 1 to 10 nor the 0 to 10 scale typically offer a ‘Not Applicable’ option which allows customers to opt-out of responding to a question that they are unable or unwilling to answer. This ensures they are not forced to select an unsuitable answer, which could otherwise affect the integrity of the results.

The following rating system is recommended for both the accuracy of the results and the ease of understanding for the customer:

Highly Satisfied

Satisfied

Neither Satisfied or Dissatisfied

Dissatisfied

Highly Dissatisfied

Not Applicable

A robust survey will also measure the relative importance of each question asked. This is best done with a 4 point scale:

Very Important

Important

Unimportant

Very Unimportant

Survey questions

Survey questions

There are many questions that could be posed in a customer satisfaction survey. The basic rule for creating a survey is to keep it relevant and condense. The following is an example of a basic survey approach.

Regarding your recent experience with our customer service team, how satisfied or dissatisfied are you with:

  1. the time to reach a consultant?
  2. the time spent with the consultant responding to your enquiry?
  3. the politeness and friendliness of the consultant?
  4. the knowledge and understanding of the consultant?
  5. the accuracy of information provided
  6. the confidentiality of information provided
  7. the company’s customer service overall

Regarding the company as a whole, how satisfied or dissatisfied are you with:

  1. the reputation and image of the company
  2. the competitiveness of the company’s products and services
  3. the company overall

Please provide any additional feedback regarding customer service, products, or other services provided by the company…

Survey Sample Size

When using a sample to represent overall performance, it is important to understand both the Confidence Level and Confidence Interval of your sample size.

Confidence Interval

The confidence interval is the plus-or-minus figure usually reported in newspaper or television opinion poll results. For example, if you use a confidence interval of 4 and 47% of your sample picks an answer you can be “sure” that if you had asked the question of the entire relevant population between 43% (47-4) and 51% (47+4) would have picked that answer.

Confidence Level

The confidence level tells you how sure you can be. It is expressed as a percentage and represents how often the true percentage of the population who would pick an answer lies within the confidence interval. The 95% confidence level means you can be 95% certain; the 99% confidence level means you can be 99% certain. Most researchers use the 95% confidence level.

Survey Sample Size

For example:

A company had 10,000 customers contact them in a month. To achieve a confidence level of 95% and a confidence interval of +/- 5, you would need to survey 370 customers.

Another company had 100,000 customers contact them in a month. To achieve a confidence level of 95% and a confidence interval of +/- 5, you would need to survey 383 customers.

Key Performance Indicators

The following measures and target selection methods are proposed for controlling and improving customer satisfaction. Scoring of a satisfaction survey that was designed using a 5 point scale with a neutral midpoint is by calculating the percentage of responses were the ‘top two’ boxes. Both these responses are positive (Highly Satisfied & Satisfied). Conversely, Dissatisfaction can be calculated as the percentage of responses that were the ‘bottom two’ boxes. Both these responses are negative (Highly Dissatisfied & Dissatisfied).

All questions should be scored in this manner to determine the level of satisfaction or dissatisfaction for each question asked in the survey. However, there are only two major Key Performance Indicators being the two ‘overall’ questions.

  • The company’s customer service overall
  • The company overall
Key Performance Indicators

These two questions ultimately determine the performance of your business. The other questions are signposts identifying where a business is performing well or where a business needs improvement.

Some Customer Satisfaction survey approaches aggregate all the responses to all the questions to determine the ‘overall’ score. This approach is flawed as it assumes that the questions cover every possible issue or scenario.

For example; A customer can respond favourably to all the questions but score the overall question poorly as there may be another mitigating circumstance for the customer’s dissatisfaction.

Benchmarking against similar operations is important. Generally, 80% to 85% top two box response to the Overall Satisfaction question is indicative of high performance.

Survey Reporting

Lean Consulting recommends the following reporting criteria for measuring and analysing customer satisfaction (assuming you are using a 5-point scale with a neutral mid-point):

  • total number of customer contacts per month
  • total number of surveys offered per month
  • total number of surveys completed per month
  • “top box” monthly performance chart for customer service overall
  • “bottom-two box” monthly performance chart for customer service overall
  • “top box” monthly performance chart for the company overall
  • “bottom-two box” monthly performance chart for the company overall
  • Confidence Level and Confidence Interval for each month
  • summary of findings from all other questions responses

Raw data containing individual customer comments should also be reviewed monthly.

Other approaches to measuring Customer Satisfaction

It would be remiss of us not acknowledge some alternative methods of measuring customer satisfaction

Survey Reporting
NPS

Net Promoter Score (NPS) is collected using an 11 point scale (0 to 10) to answer the simple question “How likely are you to recommend The Company?”. However, rather than calculating the percentage of top 4 response results for Satisfaction and bottom 4 response results for Dissatisfaction, it uses a different calculation altogether.

People who respond 0 to 6 are Detractors, People who respond with 7 & 8 are Passive and people who respond with 9 or 10 are Promoters. Net Promoter Score is simply calculated as:

% of Promoters – % of Detractors

So if you had 15% of your responses as a 9 or a 10 (Promoters) and 25% of your responses were 0 to 6 (and the remaining 60% of responses were either 7 or 8), this would generate an NPS score of -10% (being 15% – 25%).

An NPS score greater than 0 is considered to be positive. An NPS higher than 50% is excellent.

It should be noted that there is little or no academic evidence to support the claim that this measurement system is a more accurate predictor of business growth compared to other customer-loyalty questions. Furthermore, the unbalanced scale means that it runs the risk of reporting a lower customer satisfaction score than the actual reality.

Furthermore, it is an ‘all things considered’ type question. For example, a customer could be very satisfied with the customer service performance, but not the company overall. In this instance, it does not matter how well your customer service is performing, you will be unable to make this customer a ‘promoter’ unless you address other factors.

KANO

The Kano model (developed by Professor Noriaki Kano) is used commonly to classify customer requirements as well as customer satisfaction. However, it is more commonly used for the former, rather than the latter. The model classifies requirements or satisfaction into the following categories:

SERVQUAL (RATER)

SERVQUAL was originally measured on 10 aspects of service quality but later consolidated to 5 key dimensions. It measures the gap between customer expectations and experience.

By the early nineties the authors had refined the model to the acronym RATER:

  • Reliability
  • Assurance
  • Tangibles
  • Empathy, and
  • Responsiveness

Customers are asked to answer numerous questions within each dimension that determines:

  • The relative importance of each attribute
  • A measurement of performance expectations that would relate to an excellent company
  • A measurement of performance for the company in question

This data provides an assessment of the gap between desired and actual performance, along with the importance. Champions (and the authors!) of this approach, claim it provides accurate information about:

  • Customer’s perception of a service
  • Performance levels as perceived by the customer
  • Customer comments and suggestions
  • Impression from employees with respect to customer expectations and satisfaction

It is important to note that this approach is very complex in how it is constructed, making it prone to error and ultimately, a fairly costly approach to implement. Statisticians would also challenge the validity of the so called 5 dimensions from a scientific standpoint.