Trend analysis is a methodology used in research to gather and study data for prediction-making about future customer behavior based on the analysis of observed and recorded data from past and ongoing trends.
In other words, trend analysis is the process that studies statistical data and recorded market behavior over a specific period to generate valuable insights employing this data for strategizing future business plans. It helps determine the main characteristics of the market and the consumers associated with it.
Trend analysis is the practice that gives us the ability to look at data over time for a long-running survey. It can be helpful in comparing quiz or test scores (see an increase in knowledge over the course if you manage the same survey multiple times over the matter of a few weeks or months) or identifying a trend in data sets for a regularly distributed satisfaction survey.
But, what does trend analysis mean? No need to worry! We have composed this article with everything you need to know about this type of analysis so that you can start using it in all your research projects.
With the trend analysis report, you can compare historical data and get answers to questions like:
With the trend analysis report, you can compare historical data and get answers to questions like:
Trend analysis helps to display a summary of long term data. Use it to investigate variability at different time points and capture how the customers and markets respond over time. Use trend analysis to identify the best time for demand in the market and also identify low-demand phases to take actions accordingly.
QuestionPro lets you filter results based on the below data filters:
You can view trends in survey research data using below chart formats:
Researchers and businesses run a trend analysis report after data collection for the following:
Here are the business benefits of running a trend analysis:
The most common way to classify the various types of Trend Analysis is usually based on the method used. These methods are divided into: Temporal, Geographic and Intuitive. Let's talk about it.
This type of methodology is used to analyze patterns and trends of a given group of data or objects of study in a specific cohort of time, as well as its change in that period.
A clear example of this type of study is longitudinal studies with the clear intention of detecting and analyzing trends that arise.
It is mainly used in ethnographic research and other types of event-focused studies. The great disadvantage of this type of trend analysis is that it is exposed to many variables that could affect the final result of the study.
The geographic method is generally easy and reliable; it can be the means to identify commonalities and differences between user groups belonging to the same or different geographies.
The main purpose of the geographic method is the analysis of trends that develop in groups of users identified by their geographic location.
The downside of the geographic method is consequently the geographic limitation for data analysis, which can be influenced by factors such as culture and traditions that are specific to the geographic location user groups.
The intuitive method is a type of trend analysis implemented to analyze trends within groups of users based on logical explanations, behavioral patterns, or other elements perceived by a futurist.
It is helpful for prediction-making without the need for large amounts of statistical data. However, some issues with the methodology are the overreliance on knowledge and logic provided by futurists and researchers, which makes it prone to become biased to its researcher.
The intuitive method is the most difficult type of trend analysis and might not be as precise.
The graph below explains trend analysis over a period for channel sales per country. Channels are based on four categories:
This graph is an example of a sales pattern that is analyzed on a month on month basis. The table shows the calculation of the mean to show the prediction of the trend for the coming months. The table is based on the sales figure for the last four months.
Trend Analysis example:
This module allows you to plot aggregated response data over time. It is especially valuable if you are conducting a long-running survey and would like to measure differences in perception and responses over time or prepare for trend reversals in the market.
Such analysis can be precious as an early warning indicator of potential problems and issues with product line and service level changes that impact customers.
Explore our help file on trend analysis of survey data to learn how to use this survey feature.
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