How to streamline data collection through surveys

BeginnerApplicationQualityData Management 5 StepsLast updated: March 27, 2024
This guide aims to help organizations streamline their surveys to collect better and, more importantly, necessary data.

Guide Objectives

  • Create streamlined and more effective surveys
  • Learn and understand survey design best practices
  • Align your survey with your logic model and overall mission


Surveys are a commonly used and important data collection tool. Unfortunately, for many surveys, response rates are low, answers are inconsistent, and analyses are not possible. These setbacks make survey data ineffective in improving programs and supporting communities and organizations.  

This guide aims to help organizations streamline their surveys to collect better and, more importantly, necessary data. It will make surveys easier to complete, leading to higher response rates, improved data quality, and more valuable insights.

Define survey objectives 

Before creating your survey questions,  identify your for that survey. Only once you have articulated these objectives should you start writing questions. Not identifying these objectives as a first step often leads to repetitive questions and lengthy surveys, ultimately impacting the quality of the data collection. 

In this step, download the Survey Design & Objectives Template and fill out the Survey Objectives section as a starting point.

Align your survey questions to the objectives 

After identifying your survey objectives, it is now time to write your survey questions. 

On the Survey Design & Objectives template, you can write your questions in the Question Column. For each question, identify the related objective(s). This will ensure that there are no extraneous, unnecessary questions that do not fit your needs. If a question does not align with an objective, it would likely add undue burden to your respondents. 

After identifying the objectives for each question,  fill out the Data Points to Collect column with the type of data you anticipate collecting through the survey questions. These could be of all types, such as educational qualifications, employment status, etc.  

Review and implement survey design best practices 

Before launching your survey, review how it aligns with design best practices. By following the provided tips, you can create your survey with the respondents’ experience in mind and ensure the collection of good quality data.  

Meeting Organizational Needs: 

  • Define clear objectives: Before creating the survey, clearly outline the objectives you want to achieve. This will help in determining the questions to ask and the audience to target (as explained in Step 2.) 
  • Test the survey: Before distributing the survey, pilot test it with a small group of respondents to identify any issues with question clarity, survey flow, or technical problems. 
  • Avoid leading questions: Leading questions can guide respondents towards a particular response and can bias and influence answers.  
  • Provide response options: Offer clear and exhaustive response options for multiple-choice questions, ensuring that all possible answers are covered. 

Improving Response Rate: 

  • Keep it concise: Long surveys can lead to respondent fatigue, decreased response rates, and respondents rushing through questions.   
  • Design for mobile: With an increasing number of people taking surveys on mobile devices, ensure that the survey is mobile-friendly and easy to navigate on smartphones and tablets. 
  • Consider question order: Place demographic and non-sensitive questions at the beginning of the survey to engage respondents before moving on to more personal or complex questions. 

Minimizing Response Omissions and Errors: 

  • Use simple language: Ensure that the language used in the survey is clear, simple, and easy to understand for your target audience. 
  • Check for data quality: Implement data quality checks during and after data collection to identify and address errors, inconsistencies, or outliers. This may include range checks (data falls in an acceptable range of values), logic checks, and verification of respondent eligibility criteria. 
  • Arrange questions logically: Organize questions in a logical flow to maintain coherence and make it easier for respondents to progress through the survey. 
  • Localization: Adapt the survey to the cultural, linguistic, and contextual characteristics of the population being surveyed. This may involve translating it into different languages, using culturally appropriate terminology, and accounting for cultural norms and sensitivities. 


  • Informed consent: Obtain informed consent from survey participants by clearly explaining the purpose of the survey, how their data will be used, and any confidentiality or privacy protections in place. Respect respondents’ autonomy and ensure voluntary participation.

Pilot survey with test audience & revise survey accordingly 

Once you have designed your survey,  test it with an audience before its wider release and, if possible, ask for reactions and feedback. Through this process, key areas to document are: 

  • The length of time it takes for respondents to complete the survey 
  • Whether respondents did not answer certain questions as intended and, if they did not, what part of the question or its phrasing was confusing 
  • If the questions are clear, concise, and ordered in a logical way (from the respondents point of view)  
  • If there are any technical bugs or typos in the survey 
  • Whether there were any frustrating elements of the survey questions or its design  

After completing the steps above and improving on the survey based on the feedback given, you can launch the survey and collect your results!  

‘So what’ and next steps 

Like with any tool, we recommend an iterative approach. After collecting the survey responses, it is important to analyze the quality of the data collected and see whether the data aligns with the initial objectives. There is always room for improvement, and often we can only find these opportunities after one or several iterations.  

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