Using statistical tools to understand your target audience

According to recent research conducted by commercial insurer, RSA, 55% of all small and medium sized enterprises (SMEs) do not survive beyond five years, with the volume of competition they face cited as a primary reason for failure.

Given that today’s marketplace is increasingly busy, it is crucial for a business to have a strong understanding of what its customers want in order to make its mark and get ahead of the crowd. Statistical research can play a powerful role in helping organisations to drill down to the heart of what their target audience needs, providing invaluable information which can form part of a new product development process or refine a brand’s USP, for example.

Getting a grip on customer satisfaction

When asked to state what is important to them, there is a tendency for customers to focus on the rational aspects of their relationship with a company, such as prices.

Derived Importance can help to uncover correlations that unearth more nuanced issues that have an impact on satisfaction, such as supplier relationships, which often end up being disregarded in stated importance.

Derived Importance is primarily used in quantitative customer studies, and works by correlating responses to help organisations figure out how happy their customers are and fine tune particular elements that directly impact satisfaction or loyalty.

The method works by asking respondents to rate their overall satisfaction with a brand on a monadic rating scale (a one-to-ten measure), which can be used to rate performance.

For example, a company might ask its customers: How satisfied are you with [BRAND]? Please use a scale of 1 to 10, whereby 1 is ‘not at all satisfied’ and 10 equals ‘completely satisfied’. Equivalent questions are then used to measure satisfaction of other areas relating to the customer journey, such as satisfaction with a specific product, prices, customer service and the business relationship.

Generally, a sample size of at least 100 is required to uncover relationships that are statistically significant, though correlation can still be performed on smaller sample sizes in the right circumstances. By plotting the data on a scale from minus-1 to 1, whereby minus-1 represents a totally negative correlation and 1 indicates a totally positive correlation, you can reveal areas where improvements can be made to help boost performance.

Discovering what customers need

Alongside measuring customer satisfaction, it’s also important to gauge what customers need in order to promote loyalty.

MaxDiff analysis complements the derived importance technique by enabling a large amount of attributes to be tested at once by asking respondents to trade off items or attributes on a list according to what they deem most or least important. The method can then be used to measure preferences – a regular feature of customer segmentation.

Once the results are gathered, the findings should be presented as a score out of 100. Researchers can then draw comparisons, which can help a business analyse the main priorities for its customers.

This method provides a number of benefits. Firstly, by asking respondents to make simple choices, rather than repetitively rating different options, the process becomes easier to navigate. In addition, by providing a greater number of items to be tested at once the results allow for more in-depth judgements to be made, which can help businesses conduct a deeper dive into their customers’ needs.

A deeper understanding

Both Derived Importance and MaxDiff are vital tools for a market research exercise. Combining the two approaches into a comprehensive market research study is an extremely effective way to gather valuable data in order to paint of full picture of both customer needs and satisfaction.

By attaining his information, firms can then use it to differentiate products, services, branding and customer service to ensure their offering stands out in the market. In all, by meeting customers’ increasingly complex needs this can have a lasting effect on satisfaction and, ultimately, loyalty.

Kyle Cockett is head of statistics at B2B International