How to Perform Survey Data Cleansing

by | Published on Jul 27, 2018 | Data Entry Services

Surveys are conducted to collect important data regarding various topics and aspects, and this data has to be cleansed and analyzed to obtain valuable insights. Preparing the survey data for analysis can be challenging and requires professionalism. Data cleansing companies can support you with their superior data cleansing resources. Data cleansing makes the data more useful and reliable, thereby helping the management in their decision-making process.

Data Cleansing

If you are planning to perform the data cleansing in-house, consider the following steps.

  • Make a copy of original data and cleanse it – It is always advisable to preserve your original file in case you need to put something back in. For cleansing the data, make a copy of your data and use that version.
  • Perform a few small data cleansing trial runs – To conduct data cleansing trial runs, export smaller subsets of your data. This will help refine your process.
  • Identify crucial variables – It is essential to identify crucial variables in your survey efforts and define what constitutes a complete data set.
  • Eliminate speeders and flat-liners – With the help of an internet survey tool, place a date/time stamp on each response and find out how much time it took each person to complete it. Speeders are respondents who finish the survey too quickly (less than 30%-50% of median time) and are most likely not reading or answering the questions appropriately. Flat-liners mark each answer the same. They might have read the questions, but don’t really think about their answers. Therefore, it is wise to remove speeders and flat-liners from your data to eliminate a lot of meaningless data.
  • Eliminate duplicate responses – Eliminating duplicate responses is one of the best methods to achieve a cleaner and more accurate data set. For that you have to match the entry information with your survey list, and then use the date/time stamp to identify and delete duplicate entries later. It may be recommended to keep the first response and delete any subsequent responses.
  • Remove non-clients in your customer satisfaction survey – It is vital to update your lists frequently to ensure the right people are receiving the right feedback surveys. It is best to remove non-clients in your customer satisfaction survey to prevent skewing the data.
  • It is best not to ask feedback from new customers – A new client may not be able to provide the most valuable and insightful feedback. If you ask for any feedback too soon, the opinions shared by them will be based on an incomplete picture which in turn can contaminate your data. So, it is recommended to invite only customers who have been on board for at least a month or 90 days to participate in a “relationship” survey.
  • Eliminate wrong customer contacts – A database may contain customer contacts that were added incorrectly or left on even though their role within the company has changed. Offering incentives can increase the corrupted data, as someone who really does not know the product, service or value may responds simply in the hope of winning.
  • Use reliable sources of information – It is essential to use reliable sources of information for getting clean data.
  • Split the data into smaller subsets – Once the data reliability is assured, it has to be divided into smaller chunks for smoother as well as more efficient checking. The entire data can be divided into equal number of records or on the basis of some categorization such as location or age. These steps have to be repeated for every set of data to ensure that the survey data is clean and accurate.
  • Examine the data for relevance – Check for data relevance from the smaller chunks of data. It is also essential to ensure that your survey data does not have ambiguous or irrelevant information. A reliable survey data entry company can ensure that only relevant data is maintained.
  • Check relevant data for correctness and redundancy – It is essential to check relevant data for correctness and redundancy. These can create a lot of incorrectness when consolidated. Therefore, it is crucial to remove redundancy.
  • Make data corrections – Data corrections should be done and cross-checked. This should be done for every chunk of data to ensure that the entire survey data can be used for decision-making purposes.

Partnering with an experienced data entry company can ensure efficient entry and processing of survey information, thereby helping you save resources and manpower, and streamline your company’s operations.

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