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en_US Englishfr_FR French
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Survey Features

Time-based segmentation

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What do you mean by Time-based segmentation?

As the name suggests, time-based segmentation of survey responses refers to grouping of survey responses based on a timeframe when the respondents completed the survey. You can specify the time interval in which you would like to categorize the responses into groups. Based on these groups, you can capture the data and analyze it further. 

Researchers decide to segment survey responses based on the time they were completed so that they can quickly start analyzing the data in case of changing and volatile market trends.

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Uses of time-based segmentation in surveys

The first use of applying time-based filters on your survey responses is to keep up the pace with changing and volatile market trends. Along with that organizations can keep track of customer performance and through that, get to know the latest market trends and factors that affect customers’ behavior. 

A brand can measure its effect on the market through sales pitch and marketing campaigns organized for new products and services and see customer reactions to it. Time-based segmentation also enables the brands to keep track of customer engagement.

Example of time-based segmenting for survey responses

Consider a company who sells products to its customers. Upon conducting a feedback survey, they get to know what customers are expecting from their new product and services. Due to time-based filters applied on survey responses, brands can control the marketing ads and campaigns and its effect on the target audience. 

Apart from this, researchers can also use time-based segmentation to measure customer behavior and personality.

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Advantages of time-based segmentation

  • Time-based filters are used in medical studies so that researchers can measure the effects of specific drugs on patients. 
  • It also helps researchers by dividing the study in time and having a sequence of events which makes it easier to measure results.
  • Dividing results into time frames allows you to focus on the particular time of results and study them thoroughly. 
  • With segmenting data and analyzing them separately, you can derive meaningful and reliable conclusions.

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