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Millions of businesses rely on customer surveys to learn more about their customer base, their products, and their options for the future. Aspiring entrepreneurs use them for initial market research and business development opportunities. Marketers use them to polish their branding strategies and advertising campaigns. And, of course, engineers and product developers use them to enhance their products and services.
But none of these applications is inherently valuable unless the data you garner through these surveys is accurate. In fact, inaccurate data could lead you in an entirely wrong or counterproductive direction. And the tragedy is that most customer surveys are inherently inaccurate, unreliable, or misleading due to one or several missteps in their planning and execution.
That doesn’t mean surveys aren’t valuable for entrepreneurs — it just means founders have to be deliberate in how they survey.
Sampling and Reliability
First, you need to think about how you’re sampling — a key element some companies don’t even consider. Sampling is the process of using a small group of participants to create an accurate interpretation of a wider group, and it plays a massive role in the reliability of your results. Larger samples can help increase the accuracy of your results to an extent (for example, surveying 10,000 people is likely to get you closer to the truth than surveying 100 people), but simply going bigger isn’t enough.
You also have to consider what type of sampling to employ (e.g., random sampling, weighted sampling, etc.) and which techniques you should use to generate those samples. Most businesses won’t have the budget to follow strict scientific standards when launching a survey, but there’s a budget-friendly middle ground that most companies end up ignoring.
Questions and Inherent Bias
If you’re the one writing your customer surveys, you can bet at least some of your questions are inherently biased, which can skew your results in a misleading direction. All it takes is one or two words to completely change the bias of a given question, compromising your results. For example, phrasing a question like “How often are you frustrated with the quality of your internet service?” leads people to negative emotions they may not experience with a more neutral question, like “How do you feel about the quality of your internet service?”
Questions can be biased in a number of ways, including leading your respondents, loading questions with meaning, including multiple questions in a single entry, phrasing questions unclearly, or providing limited response options. Any of these can sabotage the reliability of your results.
Allowing Logistical Hurdles to Disrupt Participation
You can’t always rely on customers to provide you with accurate information, even if your questions are straightforward, neutral, and easy to understand. Most survey respondents have limited patience and want the survey to be as convenient as possible. If it drags on too long, they may start getting lazy, picking quick answers instead of thinking things through. If there are too many similar questions in a row, they may stop reading them in full, instead trusting their instincts and jeopardizing the accuracy of your research.
Conflating Attitudes and Behaviors
Many market surveys justifiably ask participants about their attitudes and preferences. This is valuable, but it’s not safe to assume that attitudes or philosophies always lead to certain behaviors. For example, if your target demographics care deeply about recycling, that doesn’t necessarily mean they recycle avidly or that they would be more likely to purchase from your business if it supports recycling. To prove a link between attitudes and behaviors, you’ll need some other piece of information, either because you asked customers directly or because you can justify the link with other scientific evidence.
Ignorance of Outliers
Most survey data analysts focus on averages and overall trends — which is, for the most part, how you should operate. If 85 percent of your customer base believes your product is better than a competitor’s, it’s safe to assume you have a competitive advantage. However, it’s a mistake to completely ignore the outliers — sometimes, these minority fringes carry the most valuable information of the entire survey.
For example, you might learn why the other 15 percent prefers your competitor or sees you as equals. If even one person out of 100 hates a certain feature of your product, she may be able to offer valuable information you can use to improve the product for the other 99.
Other Common Errors
These are just a few of the many biases, methodological errors, and outright mistakes that can lead you to false conclusions when conducting customer surveys. Confirmation bias can easily skew your results in the direction of your assumptions. Mistaking correlation for causation can lead you to false beliefs. Any number of slip-ups in your approach could jeopardize your final results.
The bottom line here is that your customer surveys — as they are — are likely much less accurate than you give them credit for, and only a rigorous and critical look can definitively improve your results.
April 27, 2019 at 05:50AM
Forbes – Entrepreneurs