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18 / Oct / 17
By Colin Wheeler
Author

Benchmarking - What’s up, or down?

Benchmarking in research is both a simple concept and a challenging one. It is intuitive that how you phrase certain similar questions can produce a different response from the same participant being asked about the same product.

e.g. a Likert scale response to

“I think that this product or service represent good value for money”

“I would pay more for this product”

In general, responses tend to be more muted, less in agreement, to paying more! Well, who doesn’t like a bargain?

So, simply, benchmarking looks at the history of responses across different surveys and companies to understand what “good” looks like as a result for a particular question.

The challenge is that little happens in isolation and products and services are offered in a competitive marketplace, so companies try to achieve standout in different ways. Location, distribution etc., all go to make up a 'uniqueness' for every company.

Company culture is a factor too, how well the way a company manages employee engagement can be hugely affected by factors such as how distributed a workforce is, how visible are management to remote sites and so on.

Each company is therefore a unique and individual personality – which creates a challenge for considering performance against a benchmark. When we create our recommendations for survey questions for employee engagement or customer experience projects, we select from a range of different questions to ensure that we are accommodating the unique factors relevant to that business.

Of course, we group “similar” companies for comparison; our database of benchmarks is extensive and covers many businesses of varying sizes and sectors. But how close a comparison is relevant?

Where does this take us when trying to understand ‘good’; there are straightforward and advanced techniques to dig into this using the survey data itself – comparing ‘Promotors’ and ‘Detractors’ (from an NPS style question) and comparing responses or producing a driver analysis to show what is driving negative and positive perceptions. Similarly, employees can be classified into engaged and disengaged.

This type of analysis is a powerful tool to extract value from survey data, taking the results beyond what can be achieved from benchmark comparison. It allows the understanding of an organisations unique character and values and where there are strengths and weaknesses to focus on or enhance.

It helps move the concept of ‘good’ from an average of similar companies to a more tailored nuanced view of results from customer surveys, and provide the direction to enable targeted action that improves the customer experience in ways that the customer notices and cares about.

In a marketplace where 'product' uniqueness is quickly copied, service and experience advantages are core differentiators, and can be the defining ‘brand’ uniqueness.

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