# Analyzing Survey Data

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After conducting surveys the last step left is to analyze the collected data. Your statistical survey data does not have any meaning if left without analysis. You need to analyze the data to draw meaningful and useful results. The conclusion you draw will help you in the decision-making process to implement changes for a successful business.

When analyzing Survey data you need to have knowledge of the types of survey data and the four levels of measurement.

Types of Survey Data: Close-ended questions and Open-ended questions

Four Levels of Measurement: Nominal Scale, Ordinal Scale, Interval Scale, and Ratio Scale

01

## Steps to Analyze Survey Data

When you begin to design your survey you must have set a top research question. This is the research question that you are trying to solve. You are collecting the data to draw the ultimate conclusion for this research question.

If your survey focuses on your Brand Image, your main research question should be “How do our customers rate our Brand?”

Now, look through your survey to find the questions that answer the main research question. For example, “Would you recommend our brand to your peers?”

Now you can collect the responses for this question and analyze them to see the percentage of people who said ‘yes’, ‘no’, or ‘not sure’. You can also segment other relevant questions that align with the survey goal.

### Cross-tabulation of results:

When you were developing your analysis plan you must have decided the subgroups you were aiming to compare the results to. For example, maybe you wanted to see how different states would respond to the survey. You can analyze and compare survey data of different states with cross-tabulation.

Cross-tabulation is a statistical tool that is used for categorical data. It gives extensive information about the relationship between the variables. Using cross-tabulation you can narrow down survey data to specific groups. You can analyze how your target market is responding to your survey in comparison to other groups.

### Benchmark and Compare with Previous results:

Are you satisfied with your survey result? To answer this question you need to compare your current result with the results of your past survey which shares the same goal. This way by comparing your survey results you can make a trend comparison.

By comparing you can figure out how much you have improved. Did the customer survey result increase or decrease? Set the result you consider your best as the benchmark and compare the new result with it.

If this is your first survey then make the survey result of this year as your benchmark. By benchmarking your survey data, you establish a baseline number. This way you can see if the results are changing.

### Analyze Quantitative Survey Data:

If you are using scales you can easily and statistically measure how customers feel about your products and services. Using the scale method is the best way to examine customer satisfaction and experience.

You can create a bar chart to analyze your data. The bar chart makes it easy to show the frequency of responses. You can either calculate the mode or mean of the survey data. The calculating mode can help you identify the most common response in the survey data.

Which means you can determine how customer response to the same question changes over time. You can calculate the mean of the survey data by adding all the scores and dividing the sum by the number of responses collected.

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02

## Tips to Analyze Survey Data

### Statistical Significance

It is important to remember that to gather accurate results from your survey you need a large sample size. The larger the sample size, the more likely the result is to represent the population. This also ensures that your survey data is reliable and prevents you from making assumptions.

Your respondents should be an accurate representation of the target market. For instance, if your target customers fall under the age group of 20 to 35, but you receive most responses from age groups beyond 35, it indicates that your survey data is not statistically significant.

### Remove incomplete responses

Your respondents may skip some questions and leave them blank. Incomplete responses can throw off your survey data. Before you analyze the responses you should remove the incomplete answers.

### Use Qualitative Data to understand the Quantitative Data

Qualitative data helps you understand the ‘why’ behind a customer’s thought or decision-making process. Quantitative data helps understand the trend and preferences of customers.

For instance, you surveyed your customers on why customers were not becoming paid customers even after using the product during a free trial period.

Asking close-ended questions gives you the quantitative data that 65% of users claim that they are satisfied with the product. The data does not tell you why they are still not converting if they find the product satisfying. To figure this out, you can ask open-ended questions such as “What is stopping you from becoming our paid member?”

### Sample Size

Always keep in mind that sample size is important. A large sample size ensures that your data is reliable and accurately represents the target population. It reduces bias and margin of error.

### Don’t confuse Correlation with Causation

Marketers often confuse correlation with causation when they are trying to draw conclusions from the survey data. It is the most common mistake you can make by jumping to the conclusion that only because two data are correlated, one is causing the other.

To avoid making this sort of error look through all the factors that could be responsible for the result. Use qualitative data to understand the survey data.

For example, you are surveying product satisfaction after updating your product features this year.

• You compare your current result with your previous result when you launched the product, and you see that
• Customer satisfaction with your product has increased by 5% in comparison to the previous year.
• You conclude that after updating the product your customer satisfaction has increased.

However, your conclusion may not be entirely true. The two factors may have a clear correlation; it does not mean that customer satisfaction increased with product development. It could also be the case that your customer service, website/app performance, etc. had a positive influence on customer’s purchase decisions. Other factors can be the reason that caused the increase in customer satisfaction.

Summarizing,

You need to analyze your survey data to understand how your company is performing and customer experience. Use survey software to work through the large volume of data and get accurate results free of human error.

Survey organizations around the world have maximized their phone survey ROI with the advanced features, hosting options, seamless telephony integration, and flexible pricing of our CATI software.

03

## Why should you use Voxco Survey Software to analyze your Survey data?

Voxco’s Survey Analytics can help you convert your survey data into actionable insights. You can use cross-tabulation to analyze the data. Also, you can build visual stories with your collected data.

### Cross-tabulation feature:

Voxco’s drag-and-drop function helps you to create cross-tabulation fast and easily. The feature includes automatic stat-testing which allows you to color-code cells where statistical significance is found.

### Visual Analytics:

Voxco Analytics allows you to turn cross-tabulation into visual charts. The charts are always up-to-date because new data is added in real-time.

### Dashboard:

You can see trends and relationships between survey data. Voxco’s dashboard includes crosstabs, charts, videos, images, and your own branding tools.

### Secure Portal:

The analytics software includes a secure portal you can use to share important findings with your colleagues and clients. You can organize your folders. You have the control to decide what others see and do in their account.

### Want to know how to increase your survey response rates?

Learn how to meet respondents where they are, drive survey completion while offering a seamless experience, Every Time!

04

## FAQs

Survey Data is the data that is collected from respondents who participated in a survey. The data includes comprehensive information. It is collected from a target market about a specific research topic.

For statistical analysis of survey data using survey software, it is used to analyze quantitative data. Quantitative data can be compared and counted on a numerical scale which helps in quantifying the research question.

Data collection and Analysis tools involve charts, maps, and diagrams. These help to collect, interpret and present the data.

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