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Cross-tabulation analysis cross-tabulation

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Cross-tabulation analysis

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Cross-tabulation is the most used functionality in data analysis in the market research industry. Also called contingency table analysis, you can use this method when comparing one survey result with another. 

Cross-tabs are data tables that help you visualize the entire data of the whole group and the subgroups. You can use the data table to determine the presence of any relationship within the data.

What do you mean by cross-tabulation analysis?

You must have come across tabular layouts of information. Just like the one you see on a report card or the ingredients behind a chips packet. You can see two-dimensional tables spreading out information. In short, the cross-tab states the relationship between variables. 

The cross-tabulation analysis is nothing but studying the tabulated information to derive conclusions from it. The cross-tab analysis uses terms like banners, stubs, chi-square statistics, and expected values.

Example of cross-tabulation analysis

Cross-tabulation analysis cross-tabulation

Let’s assume you have recently launched a range of eco-friendly travel bags. You conduct a product experience survey after 3 months of sales on 200 customers to gather feedback. 

In this scenario, you can use cross-tabulation to get an in-depth and insightful report. Moreover, you can add an independent variable, such as age, to understand how different age group views your product. 

With the data table, you can clearly determine which age group prefers your eco-friendly travel bag more. Moreover, you can identify patterns and trends by comparing the two variables – age and product satisfaction. 

Using these insights, you can create targeted campaigns and improve product quality to cater to different age groups.

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How to use cross-tabulation analysis in surveys?

Surveys can be cross-tabulated only when you have categorized variables or data. Meaning that your data needs to be able to divide into groups having something in common. Let us look at some areas where you can use cross-tabulation analysis for your survey:

Employee engagement and satisfaction surveys 

You can get to know what employees feel and think about working in your workplace and their job profiles. You can compare variables such as gender or age group and conduct employee engagement survey in various departments. 

Employee exit surveys 

Conduct surveys when employees are exiting your company. You can tabulate the information and try to figure out the reason behind their exit. You can also examine the correlations between job satisfaction and employees leaving. 

Customer behavior 

You can keep track of customer experience in your business and compare it with their feedback to identify patterns in their behavior. As we explained in the example above, you can use one or more variables and find patterns and relationships between data. 


Use cross-tabs to evaluate the likelihood of recommendations between long-term and new customers. Or find out the level of satisfaction between younger and older customers.  

Market research 

Using demographic factors, you can see differences in how people feel about your brand and serve them accordingly. 

You can use data tables to visualize large data sets and draw insightful data. You can compare the data against the entire population or specific subgroups.

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What are the advantages of cross-tabulation analysis?

Cross-tabulation analysis cross-tabulation

To define the advantages of cross-tabs, it can help you identify that your products are not performing well only for a specific region. This means that it can help you find patterns, relationships, and trends between variables. 

Here are the major advantage of using cross-tab analysis in the survey.

1. Reducing error – It is not always easy to analyze large data and represent them accurately to derive conclusions from them. 

Although, with cross-tabulation analysis, your data sets become more manageable, thus reducing any errors. You can interpret the data on a smaller and more manageable scale by dividing the total population into subgroups.

2. Accurate insights – Relationships between variables are represented accurately in cross-tabulation. This allows a straightforward data analysis making it an easy method to gather insights from.

With cross-tabs, it is easier to gain granular data. By creating sub-groups, you can uncover insights that would otherwise go undiscovered if analyzed as a whole data. 

3. Quality information – You get a simplified version of your data, only the part that matters the most. By analyzing important data, you get information that is reliable and actionable too.

Conclusion

Cross tabs can help you identify hidden patterns in your survey data. When you use this data analysis functionality with customers’ survey responses, you can create a detailed picture of your target audience. Moreover, the functionality also helps you segment your audience based on recurring patterns, enabling you to develop targeted marketing strategies. 

Voxco’ survey software enables you to create and conduct surveys on multiple channels. The platform offers advanced survey analytics software so you can uncover insights and drive change across all areas of your business.

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