Well, these are all important things to consider, but it’s just as important that we know how to interpret the results we’ve gathered. Here are some top tips and tricks for making the most of your findings…
Make a plan
First, make a data analysis plan. This is a blue print or a roadmap that demonstrates how you’re going to organise and analyse all the information in front of you. It’s worth doing as it means you’ll be able to answer your top research questions without getting lost in a sea of numbers. A good plan might also prompt you to consider dividing up your respondents into different demographic groups, giving you a more meaningful and useful way to use your data. Here’s how to write a data analysis plan so that you can make the most of your findings.
Identify your top research questions
If you gathered data by asking respondents a series of questions (by mailing out a questionnaire via Smart Survey, for example), there could be a lot of information to analyse. Therefore, identify the three questions or goals that are most important to understand. This will give structure to your analysis and ensure you’re drilling into the data the most useful way possible.
Use tables
Once you have created a plan and identified your top research questions, spend time putting the results into cleverly formatted tables. By using software applications such as Microsoft Excel, you can produce tables that will allow you to analyse and compare the data you’ve gathered. Here’s a handy guide so you can learn Excel tips and tricks quickly.
Once you’ve got the hang of using this kind of tool, why not produce a table that divides respondents into age groups? That way, you’ll be able to see what various demographics think of your research, hypothesis, service, business or product, and help you narrow in on results.
Use filters
Furthermore, consider using filters to limit your focus even further. For instance, you could filter by gender to see how many people over 55 years old responded, compared to those under 30. However, keep in mind that filtering reduces your sample size. A higher sample size is often preferable to a smaller one, so be careful not to filter data too far, else your results may no longer be statistically significant.
Finally, make sure you can trust your results
For your results to be of any use to you, they need to be reliable. For instance, if 95% of the people who completed your survey were female, but only 50% of respondents you sent the survey to were women, you have a problem: your results are not representative of both genders. Therefore, the data isn’t trustworthy. Fix this by repeating your survey or research again if necessary to ensure that the results are statistically significant.
