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Customer satisfaction analysis

What is it?

Customer satisfaction analysis is the process of assessing whether your customers are getting what they want and expect from your business, product or service. In essence, are they satisfied or unsatisfied with their experience of buying from you, or your product or service?

Measuring customer satisfaction is one of the most common forms of business analysis that companies engage in beyond financial analysis. It allows you to find out exactly what parts of your product or service are most appreciated by your customers. Too many businesses have got into financial trouble because they have made inaccurate assumptions about what their customers want, need or love.

Done properly, customer satisfaction analysis can be an extremely insightful management tool because it helps to illustrate any gaps that may exist between current delivery and customer expectations. As such, it allows a business to close that gap more quickly and improve customer satisfaction in the process.

Why does it matter?

Customer satisfaction matters because, generally speaking, customers who are happy with your product or service and have enjoyed a smooth and problem-free buying experience are much more likely to buy from you again and become a loyal and profitable customer.

Maintaining plenty of satisfied customers also helps to keep costs down because it’s significantly more expensive to attract new customers than it is to keep the ones you already have. It makes sense therefore to measure customer satisfaction so you know what your customers think and feel about your business, product and brand so you know whether or not you are on track or you are losing too many customers to your competitors.

Plus, in the past if you managed to irritate the odd customer you might receive the occasional angry phone call or terse letter, but it wasn’t the end of the world. Not any more! An unsatisfied customer can wreak havoc with your brand and post derogatory reviews that will and do have an impact on future sales. You need to know how happy or otherwise your customers are in real time so you can take action to ensure as many as possible are as happy as possible.

When do I use it?

Measuring customer satisfaction should be an ongoing process because the insights represent a huge potential opportunity or threat depending on how effective the analysis is and how often you engage in the analysis.

Having an unhappy customer is not necessarily a bad thing. It’s part of business life and should be expected. How you as a business then handle that customer, however, can determine whether or not that customer turns into a threat or an opportunity.

I have a colleague who bought a modern but retro record player as a Christmas present. It was one that could also play CDs, plug in an MP3 player as well as play and record vinyl. It arrived on time and looked fantastic. The problem was that it would turn itself off every now and again. It was quite easily fixed and would start again immediately but it wasn’t ideal. My colleague was obviously disappointed and contacted the seller. The seller told her that there were no replacements, she would be issued with a full refund including postage and could keep or dispose of the product as she saw fit. That’s customer service! My colleague went from being very dissatisfied to be a raving fan of this company in a heartbeat. The business may have lost that sale but she will buy from them again, and she has since posted glowing reviews on their website and provides feedback that will appear on Amazon which will almost certainly drive additional future sales to that business.

Dissatisfaction is not in itself bad. The key is being aware of it quickly enough so that you can take the necessary action to turn dissatisfied customers into satisfied customers and ensure that more are the latter instead of the former. That can only be achieved if you engage in customer satisfaction analytics regularly.

What business questions is it helping me to answer?

Customer satisfaction analytics helps you answer business questions such as:

  • Are we providing what our customers want?
  • Are they happy with the products and services we offer?
  • Are our customers satisfied with the service we provide?
  • How well are we satisfying our customers?

How do I use it?

Satisfaction is a subjective term which means that not everyone will be satisfied by the same things. This can make the analysis of satisfaction tricky. The most common ways are a combination of quantitative and qualitative surveys (Chapter 19 and 20). The quantitative element, i.e. ‘on a scale of 1–5 (1 being very dissatisfied and 5 being very satisfied) how satisfied are you with X’, provides data which will allow you to indicate the customer satisfaction trend over time, whereas the qualitative element will dig deeper into those ranked scores to help you better understand the dynamics of satisfaction.

It is also possible to create a customer satisfaction index (CSI). A CSI is simply an average of all the attributes that you believe contribute to customer satisfaction. It is always advisable not to assume what those attributes are and focus groups (Chapter 21) and factor analysis (Chapter 16) can be particularly useful in figuring out all the various aspects of your product and service that a wide variety of your customers appreciate.

Once you know the various factors you then weight them. For example, customer satisfaction for an airline may include on-time departure, quick transit through security, aircraft safety and on-board snacks. Clearly the quality of on-board snacks adds to the sense of satisfaction a customer may experience, but it’s probably not considered as crucial as on-time departure or aircraft safety! As a result, the attributes need to be weighted to account for their varying importance.

The customer satisfaction index can therefore be a single score generated from your own unique index of factors you’ve identified influence satisfaction for your customers, or you can use an existing index.

The widely used American Customer Satisfaction Index (ACSI) or the National Customer Satisfaction Index-UK generates a single score based on drivers of satisfaction such as customer expectations, perceived quality, perceived value, customer complaints, customer retention, customer loyalty and price tolerance.

The beauty of these existing tools is that they ask the same questions (tailored slightly to each industry), which means that you can compare your business to others in your sector and to your nearest competition.

In addition to these traditional tools there are now many new, often relatively inexpensive, ways to analyse customer satisfaction using the plethora of new data sets that now exist. For example, you probably post reviews, post on product forums, create Facebook posts about your product or tweet about your product, service or business. Not only is this data already out there but it’s also untainted by research conditions – what your customers say about you online is probably the closest you’ll get to the truth. As a result, that text data can be retrieved and analysed to gauge sentiment (Chapter 8 and 9).

Practical example

Many large companies such as Gatorade and Dell track what their customers are saying about them in real time. They monitor social media including Facebook and Twitter, blogs and all types of online discussions. In the same way the CIA can monitor conversation traffic to identify key words of phrases that may alert them to a potential threat we can now monitor whenever anyone mentions a particular product, brand or business. Even something as accessible and simple to use as Google Alerts can tell you whenever someone mentions your name online or mentions a product or brand!

By accessing data that is already in existence you can then use text analytics to analyse customer satisfaction and sentiment analysis to gauge whether the sentiment towards your product or service is generally positive or negative. Plus, there is also some very exciting predictive capabilities with this data.

As already mentioned, researchers at the Microsoft Research Labs in Redmond, Washington, discovered that it was possible to predict which women were at risk of postnatal depression just by analysing their Twitter posts (see Chapter 9, sentiment analysis). Instead of using an algorithm that looked at searches or purchases of the mother, the research focused on the language and words the mother used in social media posts prior to giving birth.

If this can be done to identify those at risk of postnatal depression before it occurs and therefore offer additional support to prevent it occurring, then there is no reason why it can’t be used to identify customers at the risk of leaving a business or bailing out to the competition.

Being able to track customer satisfaction in real time is now possible through the vast amount of data that is being created and shared online. These insights can help you stay one step ahead of your customers so that you consistently deliver what they want and need.

Tips and traps

There really is no need to invest in potentially expensive surveys when there is probably already a plethora of qualitative data that exposes your customer satisfaction. Encourage your customers to interact with you via your Facebook page or Twitter – that data can then be used to improve your business and increase revenue.

The main trap to be mindful of with customer satisfaction is that even if a customer is satisfied – even very satisfied – that satisfaction does not always convert into profit. And it certainly doesn’t necessarily translate into loyalty.

Further reading and references

To understand more about customer satisfaction analysis see for example:

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