Sampling bias in VOC research affects post-purchase experience

Explain how sampling bias in Voice Of Customer research could adversely affect a marketing analysis of customers’ post-purchase experience with a product.

As post-purchase feedback is critical to keeping customers satisfied within the “Loyalty Loop” along their journey, sampling bias is a danger to avoid in both traditional mass media and modern digital contexts.

Sampling bias occurs when the selected participants in a study are not random and not fully representative of the wider population of interest, and therefore their feedback and perceptions skew results and recommendations.

Sampling bias in VOC research is to be expected but should be recognized and controlled to avoid poor decision-making. How it can negatively impact marketing analysis:

  • Restricting the sample to customers eliminates the voice of non-customers, those who may have actively considered purchase but did not complete the transaction
  • Customers who agree to participate in studies are willing to be interviewed and likely enjoy giving feedback and voicing their opinions. These are not representative of the majority of customers, who may be more timid or less vocal
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I recently purchased a USB-powered desk fan through Amazon. A few days after delivery, the vendor emailed asking for product feedback using Amazon’s review system. I obliged, using the opportunity to complain that the fan didn’t meet expectations: it was single-speed and noisy. My 3/5 rating and comments were publicly published. Within a few hours, the vendor replied with instructions for how to control fan speed and noise.

While a good example of the power of social media and positive customer service, this example also demonstrates the risks of sampling bias. Had I not been contacted, I would not have voiced my negative feedback. Or, had I been using the product longer, I might have a different opinion of its performance. If such feedback were combined into an aggregate report used for marketing analysis, the insights and recommendations could be far from representative of most consumers’ experience.

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