I have seen a lot of articles recently stating that \u201cCustomer surveys are dead\u201d. However, when you scratch beneath the surface, you often find the real story isn\u2019t quite as dramatic as the headline.<\/p>\n
\u201cThe rumours of my demise have been greatly exaggerated<\/em>\u201d \u2013 Mark Twain<\/p><\/blockquote>\n
This is, of course, true of the Mark Twain quote. Twain actually said, \u201cThe report of my death was an exaggeration<\/em>\u201d, and so it seems the report of the report of his death was exaggerated too.<\/p>\n
As humans, we have this tendency to exaggerate problems, especially if you\u2019re trying to sell something, or even if you just want people to read your LinkedIn post! So, what is the real problem with surveys, are they becoming redundant, is their demise real?<\/p>\n
Overcoming Common Survey Pitfalls for More Accurate Results<\/h2>\n
As someone who has received many surveys, I notice a common problem. People often overthink or underthink the questions. When the questions are poor, the data is also poor.<\/p>\n
Survey data analysis is also a major challenge, even when the data is of sufficient quality. These problems inevitably lead to the exaggerated conclusion that surveys don\u2019t work and thus are \u2018dead\u2019. This is because they fail to help achieve actionable insight.<\/p>\n
Factors contributing to this perceived demise of surveys include:<\/p>\n
Irrelevant Metric Questions<\/strong><\/h3>\n
Have you ever been asked if you\u2019d recommend a customer service centre? Under what circumstance am I making this recommendation? Either the person needs your help or they don\u2019t, it isn\u2019t optional.<\/p>\n
Undefined Question Subjects<\/strong><\/h3>\n
A common example is \u2018Ease\u2019. Most surveys ask if you found the process \u2018easy\u2019, but what does \u2018easy\u2019 mean, does it have one consistent definition?<\/p>\n
It could be a slow or long process, it could be complexity of information, and so on. During survey analysis, how do you know what the respondent meant? Simple answer, you don\u2019t.<\/p>\n
If you don\u2019t define the question, you cannot define their answer. Therefore, you cannot confidently or accurately develop actions from the results.<\/p>\n
Excessive Use of ‘Survey-Speak’<\/strong><\/h3>\n
Too often questions are framed in a way that you would never choose if you were speaking directly to a person. Talking to people as if they are human is more likely to get a human response. This response shows how they felt about their experience.<\/p>\n
For example, have you ever been asked to \u2018in your own words, tell us’<\/em>. Who else\u2019s words were they expecting? Do they get a barrage of Gandhi or Socrates quotes, maybe lots of King-esque \u201cI have a dream<\/em>\u201d feedback?<\/p>\n
We shouldn\u2019t be seeking a statement-like response. Ask a human question, get a human answer.<\/p>\n
Over-Indexing the Value of Metric Scores<\/strong>:<\/h3>\n
Often the goal is seen as \u201cIncrease the NPS\/CSAT Score\u201d. This should not be the goal; we should be seeking to improve the actual experience.<\/p>\n
The score increasing is a consequence of the goal, not the goal itself. The metric helps us understand that change may have occurred, providing the starting point of the analysis, not the end. The score is a \u2018what\u2019 not a \u2018why\u2019.<\/p>\n
Failure to Find the \u2018why\u2019<\/strong><\/h3>\n
Quantitative data can only ever tell you the \u2018what\u2019 – you must investigate the qualitative data to find the \u2018why\u2019.<\/p>\n
Actionable insights come from understanding the ‘why.’ However, the value of expert qualitative analysis is often ignored. Because of this, actions are based on the ‘what’ instead of the ‘why.’<\/p>\n
As a practice, we could call this \u2018guessing\u2019, which is why actions taken are often ineffective. Establish the \u2018why\u2019 and you remove the need for guessing, with actions driven by evidence rather than opinions.<\/p>\n
What is the Survey for, what am I trying to Achieve?<\/em><\/h2>\n
To choose the right tool for your goal, you need to understand your objective. This way, your survey can be aligned effectively. This enables the question setter and the respondent to focus on the subject without distraction or confusion.<\/p>\n
Good output requires good input. By improving how you collect survey data, you can use that data to take action.<\/p>\n
When it comes to customer surveys, I see one overarching objective split into two sub-objectives:<\/p>\n
\n
- Gather opinions and views from customers to create actionable customer experience insights. This will lead to improvements in their customer experience journey.<\/li>\n<\/ul>\n
1.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Seek customer opinions on key business questions \u2013 Customer Research.<\/p>\n
2.\u00a0 \u00a0 \u00a0Seek customer insight on what they value (NOT their opinions on what you value) \u2013 Voice of the Customer.<\/p>\n
Crafting Effective Survey Questions for Targeted Research<\/h2>\n
It is important to understand this delineation between \u2018Research\u2019 and \u2018Voice\u2019. Both processes are valuable, but only when aligned to the correct objective. They can also be used in unison.<\/p>\n
Maybe your VOC survey draws your attention to a developing issue, but you want to gather more knowledge before acting. A targeted Research survey can help evidence the issue and define the action.<\/p>\n
For either method, it is vital to ensure that we get the questions right. Therefore, we must create the survey with an eye towards the final analysis.<\/p>\n
\n
- Make sure questions are relevant to your objectives.<\/li>\n
- Make sure questions are defined. To the earlier point, if we conclude that \u2018Ease\u2019 is a mixture of \u2018Time\u2019 and \u2018Info Clarity\u2019, then ask about those subjects separately instead. Make life easy for the respondent and the analyst, a win-win.<\/li>\n
- Get to the point and offer valuable guidance. For free text, instead of \u2018in your own words\u2019, encourage them to elaborate and explain the value of doing so. For example, \u201c\u2026 if you can provide details around processes, timeframes, etc. this will help us to understand and improve the service\u201d. Getting to the point isn\u2019t always about reducing the number of words used.<\/li>\n
- Align your quantitative and qualitative analysis and ensure that the skills and methods required for high-quality qualitative analysis are prioritised.<\/li>\n<\/ul>\n
The idea that “Surveys are Dead” often focuses on replacing reactive ‘Listening’ with ‘Predictive’ methods, i.e. can we predict future NPS or CSAT scores? This aligns with some of the key issues highlighted, above.<\/p>\n
People often give too much importance to the metric score. On its own, it does not offer useful insights. This focus on metrics shows a false goal of \u201cincreasing the score\u201d. Our real goal should be to improve the customer experience. Then we can see how to optimise all the customer feedback tools.<\/p>\n
Although bad surveys should be dead, by clarifying our survey goals, we can create better questions. We also need to spend time and resources to analyse the survey data. This will help us generate actionable insights. Effective surveys are important for improving the customer experience.<\/p>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
Rather than falling into the trap of meaningless metrics, the impact of surveys lies in their ability to extract actionable insights through well-crafted questions and informed analysis. <\/p>\n","protected":false},"featured_media":27912,"parent":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false},"practices":[85],"industries":[],"capabilities":[104,111,112],"class_list":["post-27806","blog","type-blog","status-publish","format-standard","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"\n
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