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How to Protect Surveys from Bot-Generated Responses

Customer Support avatar
Written by Customer Support
Updated over 2 weeks ago

Bot-generated responses are a problem that may occur in surveys distributed via email.
Automated mechanisms designed to check the safety of links can enter the survey and fill in the first question visible in the message.
Such responses are artificial and can reduce the quality of your survey results.

At Webankieta, we continuously work on solutions to limit the impact of bots, but there is no security measure that can eliminate this issue completely.
However, you can easily minimize the risk by following a few simple steps.

1. Change the content of the survey invitation

The problem most often occurs when the content of the first question (for example, an NPS question) is placed directly in the email invitation.
In such cases, the bot selects an answer in the message and automatically registers a completed response.

To prevent this:

  • Include only a link to the survey in your email message, instead of the text of the first question and its answers.

  • Add a short introduction on the first page of your survey.

  • Place the NPS question or other key questions on the following page.

This way, the bot will stop at the introduction page, and only a real respondent will be able to move forward to the actual questions.

2. Add a control question

Another way to reduce false responses is to add a control question right after the NPS or single-choice question.
This can be a simple logic or math question, such as “What is 2 + 2?”

Such a question works as a simple form of captcha.
A human respondent will easily provide the correct answer, while a bot will most likely fail to do so.


Summary

Bots typically generate responses when the first survey question is placed directly in the email invitation.

The most effective ways to limit this problem are:

  • modifying the invitation content and adding an introduction page,

  • using a control question.

By applying these methods, you can significantly reduce the number of artificial responses and improve the quality of your collected data.

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