Every organization irrespective of the industry at some time or the other wants to conduct a survey (either internally and/or externally) for various reasons around gathering information or collecting feedback. Some of the common reasons for conducting surveys are:
This entire survey deployment, data collection, data transformation, data analysis and reporting is a combination of art & science. Surveys are generally deployed for very specific objectives and are very contextual in nature.
Designing a survey is a systemic process which involves some key elements:
It is important to design questions which are focused and have potential to engage the respondents. The survey right at the start should clearly mention the objectives and also highlight the time commitment from the respondents so that they get to plan their time accordingly and may decide to get back later if required. One important factor to consider while designing individual questions is to ensure that they are not leading. The questionnaire flow and individual questions should help respondent to deep dive into stated objectives and should help them visualize the potential actions.
The objective of conducting a survey is to gather useful and reliable data in specific layouts/visuals which can help draw conclusions / take decisions about the stated key goals. It is important to clearly define what data is needed. It’s equally important to define upfront the format and layout of the output data so that the appropriate steps can be designed and implemented to transform response data into a right layout for further analysis and reporting. As part of this step, ground rules should be set on what data will be used and what will be discarded. Some key rules that need to be defined:
There are several ETL tools which can be used depending on the complexity and volume of data that needs to be dealt with. Some of the commonly used tools are Excel, Talend, Python etc.
Interactive Visualizations helps in better understanding the responses and can support the decision making process. There are different charts/graphs which can be created to visualize responses for different types of questions:
Use heading for each of the graphs and tables that capture the essence of the visual. Commonly used tools for this purpose are R, Excel, Python, Tableau, Qlikview etc
Finally, it is desirable to call out what do the survey results mean? Why do the findings matter and how are they tied to survey goals? The conclusion should answer all of these questions. The conclusion should be able to summarize the entire survey process from the formulation of survey goals up to the final actionable outcome.
There are some key elements which needs to be considered while writing an effective conclusion:
Have something to add to this post? Please share it in comments! Drop me a mail at firstname.lastname@example.org in case you would like to talk live. We at Incentius would be happy to act as a friendly, informal "sounding board". We can offer an ear and views based on our years of experience working in this area, and can also help with some ideas, contacts and solutions.
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