A Normal or a Gaussian Distribution personifies many of the natural phenomena – However, its use in Social Sciences needs to be taken with a pinch of salt. However, we have always taken liking to the bell curves in Product Life Cycle, Customer Adoption.
A Customer Satisfaction is very much an ‘attitude’ that the customer possess. We will be making a conjecture of plotting attitude on Normal Distribution. With this assumption, we can bracket the customers in Very Sad – Neutral – Very Happy. Traditionally, we have seen that there is a Silent Majority (the Bulk) – The Strong Advocates (Very happy customers) or The Heavy Detractors (very sad customers).
The Extreme ends are where the bulk of proactive reviews and feedback lies. A Customer has to be super pleased to share the feedback or has to very displeased to rant about the brand. The moderately pleased or slightly irritated never come out vociferously. Hence, the natural bias is towards the extreme. The point to note is that – Even though the expected customer satisfaction across the sample is normally distributed; the voiced opinions are only bipolar. This IMPORTANT observation from this thought experiment brings us to question the proactive feedback method. A forced/ stratified sample is likely to be less biased. We can reach out to random sample of your customers to get more accurate representation of your customer satisfaction state.
- Are your business decisions geared towards satisfying the extreme ends of customers or the silent majority that actually drive your revenues?
- Are you mixing up an agitated customer and an important customer?
Your most important customers are the ones who contribute the most to your bottom line. If your customer feedback system is turning blind on this set – Your business is in trouble?
Social Listening is perceived to be another potent source of customer insight – However, it is a classic case of self selecting bias. The people who rave or rant on social media have self-selected them in the sample. I am NOT questioning the need or urgency to address this set – But, just asking, “Are they Your Most Important Customers?”
To summarize, the voice of customer should reflect the proportional stratified sample across the customer sets – Let us not get swayed by the extremes – Let us listen to the bulk.
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