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Cross Tabulation Analysis

Today’s businesses need to find every opportunity within their data that they possibly can in order to drive competitive advantage. Cross-tabulation analysis has been an increasingly popular method to help organizations accurately identify patterns and trends within their data and gain meaningful, business-applicable results. The cross-tabulation analysis provides a comparison of the relationship between variables using quantitative research methods. It’s ideal for surveys and market research studies because it helps companies find connections in their research and surveys. By using cross-tabulation to siphon through massive quantities of data, organizations can better pinpoint the information that is most useful to their objectives, goals, and queries.

This analytics technique is vital in promoting the growth, strategies, and development of core business research initiatives.

Cross Tabulation Analysis and its Applications

The cross-tabulation analysis is essential to testing hypotheses and probabilities in statistical analysis. Cross tabulation is designed to display data in a table, making that data much easier to read and interpret.

Independent events that contain specific, independently defined characteristics, are tabulated, or organized, into a contingency table. A model is created based on the laws of probability to determine what the cell values would be if the unique variables were independent. The correlation between the variables can then be measured, compared, or tested against predicted values.

Though this technique sounds like it resides solely within the realm of high-level scientific exploration, it’s, in fact, a real-world business asset that helps with targeted goals such as market segmentation, or organizational road-mapping.

Illustration and Practical Applications of Crosstab Analysis

A simple example of Crosstab analysis can be a 2x2 contingency table, where one variable is Age Group, and the other is the preference for Denim or Cotton Trousers.

 

Below 30 years

Above 30 years

Total 

Preference  

 

 

 

Denim 

14 

22 

Cotton Trousers 

12 

18 

Total 

20 

20 

40 

This displays that while 70% of respondents below the age of 30 prefer denim, only 40% of respondents above 30yrs of age prefer denim as compared to cotton trousers. This information can be easily used by a company manufacturing both products to target the right age group for the appropriate product.

So if you are a marketer wanting to increase your brand’s visibility through better promotions aimed at the factors influencing sales in your target segment, Crosstab analysis will provide you deep insights on customer profile and relevant purchase behavior. This enhanced understanding of your target market’s requirements will help you design a better and more targeted branding and promotion strategy to achieve the end objective of higher sales.

Crosstabs are widely used in quantitative market research and surveys. They help identify trends. Further, they help identify the type of response of a particular category of respondents. This often helps us in understanding what effects an action will have on a category of our target segment. So, an FMCG company might be able to analyze what effect a price change might have on its urban vis-à-vis its rural consumers, or a survey might be used to gauge the effectiveness of a particular advertising campaign on its male vis-à-vis its female user groups.

Cross Tabulation Analysis in Business

Businesses can use cross-tabulation to display data in easy to understand ways and come to accurate conclusions by more simply discovering patterns, trends, and opportunities in their data.

  • Modern businesses are fueled by data, and data scientists can display data in tables in order to quickly compare and derive meaningful results. This makes it easier for data scientists to talk about their data in a simple to understand formats when they need to communicate results to business leaders.
  • Business leaders have to use research to drive decision making, and they can use Cross Tabulation for comparing information that leads to effective results.
  • Cross tabulation is often used in survey analysis to determine the results of survey responses and compare how groups answered certain questions.
  • Businesses can investigate the relationships between data sets that might have otherwise been overlooked.
  • Cross tabulation helps communicate information across the business in a way that is easy to understand so that everyone across an organization can review and comprehend the meaning behind data and put it to the purpose.

Cross Tabulation Analysis Process

Chi-square analysis is used to test cross-tabulation tables so that you can discover if you should reject or not reject the null hypothesis. This means that when you are testing independent variables, you can determine if there is a relationship between them.

  • Relationships Between Products, Pricing, and Transactions: If an organization wanted to compare and better understand the connection between a specific product and the payment type used to purchase that item in relation to the actual number of transactions, this technique would provide reliable, usable findings. This helps inform product pricing, customer preferred payment methods and product trends.
  • Connection Between Customer Habits and Demographics: Companies that want to obtain an in-depth analysis of customer activity and behaviors to help shape their marketing strategies often depend on cross-tabulation analysis. They can then compare specific consumer behavior based on narrow or broad demographics, such as certain age groups and genders that purchase particular products.

Benefits of Cross Tabulation in Research

Cross tabulation augments an organization’s research and analysis capabilities by helping them derive insights and meaning into their research data.

  • Reduces Errors: Large data sets can be daunting and seemingly unmanageable, but with cross-tabulation analysis, data can be broken down into a smaller scale, effectively reducing errors.
  • Makes Information Easy to Understand: Even more complex statistical information can be more well-understood, and complications that arise from difficult to interpret information can be drastically reduced.
  • Reveals Important Insights: Research data can be numerous, and when information is displayed in a table, businesses are more organized and better prepared to uncover the meaning behind data and come to accurate conclusions.
  • Drive Business Results with Data: Businesses are using data to drive decision making, reach their goals, create opportunities, reduce risks, and create value. Many modern business processes and initiatives can be supported through Cross Tabulation in research.

Business-Tailored Cross Tabulation Analysis from Research Optimus

Research Optimus (ROP) provides completely tailored, innovative, and consistent research and analysis services making use of Cross Tabulation Analysis and on-demand market research and financial research services.

Our skilled analysts are adept at identifying business problems and analyzing market data to arrive at key insights. Banking on years of research and analysis experience, ROP can assist organizations in any industry vertical with their most complex marketing and financial research objectives.

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    After carefully reviewing the documents you provided, we are suitably impressed with the meticulous details and extracted data which is truly high-quality

    Lynn Kowalczyk
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    Even though most of our communication was done via email, it was extremely easy to work with Research Optimus. Superbly quick turnaround time which was quicker than needed. They were there when I needed them!

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