As customer demand for better service increases, businesses are truly being put under the microscope and scrutinised as to how well they listen to their customer base. This is prompting more companies to actively collect customer feedback and use it to improve their customer service. One method of doing this is Voice of the Customer (VoC) surveys. While these might seem a simple means of collecting customer feedback, knowing what to ask, when to ask it, and how to ask it, can be confusing for some. As can knowing what to do with the data once collated.
Too frequently, there is over-focus on the metric scores produced by a survey but then minimal further analysis to generate actionable insights. The primary goal of VoC surveys and analysis is to generate customer-led actionable insights. Wearing an NPS or CSAT score as a badge of honour but not really understanding what underpins or changes that score limits the chances of changing the customer experience for the better. In this scenario, VoC is ending with only data capture. How do we dig deeper? Here, we’ll be exploring the core components required to leverage our survey data into deeper and actionable insights.
Performance-tracking metrics
For each section of your survey, the opening question must be “what do we use this for?”. The metric you choose performs one primary function—it takes a pulse of how customers are feeling about their interactions with you. If the score goes up, things have probably improved, if the score goes down, things have probably deteriorated. The score merely directs you towards the possibility that something has happened, but it never tells you what has happened, and certainly not why it happened.
When identifying the right VoC survey metric, you need to ensure it’s relevant to the interaction and your goals. For example, recommendation (NPS) is not always relevant. Your metric should also be all-encompassing, enabling the customer to reflect on all elements of the experience, giving you that overall pulse and directing you towards the start-line of your analysis. Pick one—and only one—metric. Just as two pulses in one person would be problematic, the same is true of surveys.
Key driver questions
The additional questions that sit beneath the metric question are often where a survey can lose its power. Too often we see the use of stock questions that offer minimal insight into a customer’s perceptions. A common culprit here would be ‘Ease’. When we ask how easy an experience was, what do we mean? Is this a definable question, or is there potential for ambiguity? We may see feedback saying “that was quick and easy”, so ‘ease’ can certainly reflect ‘time’. The primary antonym of ‘easy’ is ‘difficult’, so ‘ease’ can reflect things like ‘complexity’. We now have two varying definitions. For analysis purposes, if you have two definitions then you have no definitions.
A useful rule-of-thumb is to consider “does the question (and scale) mean the same thing to the person asking the question and the person(s) answering it”—if no, don’t ask the question. Avoid ambiguity as it means your Voice of Customer analysis must make assumptions—which are often incorrect about the motivations of the respondent.
To the question of “what do we use this for?”, ‘key driver’ questions are for what their name suggests; to assess the impact of the key drivers of the experience. Firstly, what do we mean by ‘key drivers’? These are the definable constituent parts of the interaction. Ask yourself “what is anything relevant to the experience that a customer could possibly feed back to us on?”. Think of it as a diagnosis task. If you have a sore knee and visit a physio, their first task is to understand which component part of the knee is causing your problem. Only when that is identified can they assess the cause, e.g., if it is a muscular issue, is it a strain, sprain, tear, etc. Once the cause is diagnosed, treatment can be designed. Critically, the physio already knows the components of a knee, and all the potential ailments of each, before they begin their assessment.
The same pre-existing knowledge is vital for VoC surveys. Take something that we’ve all encountered as a customer like a contact centre—what could we feed back about; the agent, the time taken, elements of communication (info clarity, etc.), and the outcome of the call? All feedback we could give that is directly about the experience with a contact centre would fall into one of these four boxes — they are distinct, and can be adequately defined. As such, these are our ‘key drivers’, and these become the questions on our survey. By acquiring scores for these elements, and by analysing them against the overall metric score, we can begin to establish how impactful these drivers are, giving us the ‘what’ associated with changes in performance.
Free text – qualitative analysis
VoC surveys should always have a free text question. Whilst the final part of the analysis, this survey question should come immediately after the all-encompassing metric question, where the respondent is still thinking about the whole experience. Placing it after the ‘key drivers’ may focus their attention on specific subjects and influence their answer.
This part of the survey allows the respondent to set the agenda, they can—and will—use this option to discuss what matters most to them, whether good or bad. Connecting this with the other results enables us to establish the ‘why’ behind both the positive and negative experiences. It is important to phrase this question in such a way that the response will tell us both the subject and the reason why it was either good or bad.
The analysis follows the same diagnostic lines outlined in the key drivers section but requires us to go that one level deeper. Taking the same contact centre example, where the key drivers were Agent, Time, Communication and Outcome, qualitative analysis requires each of these to be further deconstructed. For example, Agent feedback could be about their ‘knowledge’, ‘attitude’, and ‘empathy’, while Communication is made up of topics like ‘breadth/depth of information’, and ‘bad phonelines’.
Feedback received can then be distributed into these categories — automatically if you have text analytics software— enabling an immediate view of the spread of customer conversation, what themes are driving their view of your performance, and what are the specific issues at play. This provides us with the ‘why’ for improvement or deterioration in the experience.
Summary
Before we ‘listen’, we must first ‘think like an analyst’ to build out the framework of feedback categories, based on the specifics of the business and its customer interactions. This is ultimately the first step towards understanding feedback from your customers.
It is a common misconception that constructing your data capture comes before constructing your analytical methods. By considering what feedback data will look like, and how we can understand, interpret and analyse it, we can generate intelligent data capture that aligns quantitative and qualitative survey analysis methods. This leads to accurate, powerful and actionable insights.
Use a metric to take the pulse of performance, connect it with key drivers to break the experience down into its constituent parts to establish the ‘what’, then use qualitative free text analysis to drill deeper into these areas to establish the ‘why’. We can then use customer-led actionable insights to develop the ‘how’, to fix the problem and improve the experience.
Understanding how to accurately determine and leverage insights through Voice of the Customer analysis can be complex, and timely. That’s why we aim to make it simple for you.
With our smart customer experience technology solutions, and the help of our customer experience consultants, we can help you reinvigorate your CX analysis process. From designing and sending out customer surveys, to collating and analysing your customer data and turning it into actionable insights, we can help you every step of the way. Get in touch to find out more.
