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Online Research – How to interpret country differences in your data

Our handy guide on interpreting international data will show you how to compare results from one country to another.

Looking to find out which countries in EMEA are interested in your product? Want to show how UK office habits differ to the US? Keep reading! Our handy guide on interpreting international data will show you how to compare results from one country to another.

The data isn’t always as it seems

Comparing data from multiple countries can be pretty tricky. Cultural and language differences mean that respondents answer questionnaires in different ways.

We conducted a survey in the UK and India. The questionnaire asked employees yes/no questions about their working life. On average, 47% UK respondents answered “yes” compared to 79% of Indian respondents. Does this just mean India are more favourable to our concepts? Or, is there another reason behind the sizeable difference?

We’ve seen in many of our research studies that some countries are more likely to say “yes” than others. This is because of the cultural/language definition of the word “yes” rather than the subject of the questions. We’ve seen that Asia and USA tend to have higher percentage answers, and Europe score lower. The same sort of patterns can be found in the averages of scale questions – in 1-10 scales for example, India and China often score high 8’s or 9’s whereas the UK or France will score 7’s. Because of this, country data is often not directly comparable.

How to beat the bias

You may be thinking – well, that makes my research useless doesn’t it? Certainly not! There IS a way to find valuable insights from country by country data. Instead of comparing directly, look at the order that the results come in for each country. Imagine we asked the question: “Which of the following colours do you like? Please tick all that apply” and the results were as follows:

Given the cultural context, it’s debatable whether to say “China like Blue more than the UK”. However, by looking at the order of the results we can make different, and arguably more relevant, assumptions. The real learning from this data is that “The UK’s favourite colour is blue, whereas China’s favourite is red”. This insight avoids the real percentages and focuses on the ranking of colours for each country.

Using conditional formatting in Excel row by row (or column by column) can be useful in highlighting where differences in order occur.

Making sure that your survey is conducted in the correct languages and translations are undertaken by native speakers is another way to minimise the bias. Keep an eye out for advice on survey translations, coming soon.

If you have any questions about how to analyse your country data, or have a country research project you need a hand with, get in touch! andrew.white@sapioresearch.com

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