The data design process is a balancing act between asking enough of the right types of questions to gather the data you need, but not so many that respondents lose interest and drop out. It can feel overwhelming but that's where the Datasight® team can help, and the earlier in the process the better. With decades of data design experience under our belts, we'll look at your overall design with fresh eyes, spotting design issues that could require extensive data cleaning later or lead to key information being missed altogether. By catching these issues before the data collection phase kicks off, and helping you fix them, we can save you a lot of time and money down the track.
We're experienced with using a wide range of survey design options including Qualtrics XM, Alchemer, Google Forms and Survey Monkey, which means that we can hit the ground running once we're on board. Our initial data design consultation is absolutely free, so the sooner you lock in a time, the sooner we can get your data design back on track.
Quality data and insights are essential for people to make well-informed decisions, and data design is the foundation of the entire process. What do we mean when we say data design? We're talking about data design in the context of conducting quantitative research, and it's essentially the process of planning how to collect, organise, and use data to meet specific goals.1 When it's done well, you end up with a data collection tool (e.g. a questionnaire) that collects the exact data you need to meet your goals, in the format you need it, with the least amount of error. It's like cutting a magical key that unlocks the door to reliable and actionable insights.2
The process involves weighing up which data collection options are the best fit for your target respondents and research objectives. Having an in-depth knowledge of analytical techniques helps here, since questions that ask participants to rank multiple options can't be analysed in the same way as questions where only a single category response can be selected. Likewise, the kind of scales you use, whether Likert or numeric, will also have an impact on the types of data insights available. You might want to include several open-ended questions to get a deeper understanding of quantitative trends and to use as quotes in your marketing campaigns, not realising that they take longer to answer and may lead to people exiting the questionnaire before finishing it.3
Writing questions that are easy to understand and answer is another vital skill in the process, along with crafting response options that make sense while being mutually exclusive of each other and collectively exhaustive so all possible response options are covered. The structure and rotational options are also a consideration, since the order of the questions and their response options creates bias in the way people respond and introduces error to the data.
References
1 Babbie, E. (2016). The Practice of Social Research. 14th ed. Boston, MA: Cengage Learning.
2 Routledge.Sue, V. M., & Ritter, L. A. (2012). Conducting online surveys. Sage publications.
3 Fan, W., & Yan, Z. (2010). Factors affecting response rates of the web survey: A systematic review. Computers in Human Behavior, 26(2), 132-139.