TABLE OF CONTENTS

How to analyze survey data

Feeling overwhelmed by your survey data? Don't worry! This guide breaks down survey data analysis into easy steps. Learn how to uncover valuable insights, visualize trends, and leverage built-in AI analysis with Formaloo.

TABLE OF CONTENTS

Have you ever spent a lot of time creating a survey? Did you end up with a lot of data to analyze once you received responses? You're not alone.

Surveys are a powerful tool for gathering valuable insights from customers, employees, or any target audience. After clicking "submit," the system transforms the raw data into useful knowledge. That's when the real magic happens.

The challenge lies in extracting meaningful patterns and trends from a sea of numbers and text. Fear not! This guide will equip you with the essential skills to analyze your survey data effectively. We'll walk you through a step-by-step process, from understanding your data to presenting clear and compelling insights.

By the end of this journey, you'll be well on your way to unlocking the hidden potential within your survey responses. So, turn those "yeses," "nos," and open-ended comments into actionable strategies that drive positive change.

Before you dive into analyzing...

Before diving into analyzing data and trends, make sure to gather some important information first. These initial steps will set the stage for a meaningful and insightful survey analysis.

Firstly, take a good look at your total respondent count. This number tells you the size of your sample group, which in turn influences the reliability of your results. Collecting opinions is important. However, asking only 5 out of 5,000 concert-goers may not accurately reflect the views of the whole audience.

Secondly, calculate your survey response rate. This is a simple percentage calculated by dividing the number of completed responses by the total number of people invited.

More people responding and a bigger sample size make your data more accurate and reflective of the target group.

What is survey data analysis?

Surveys are a cornerstone of research, providing a structured way to gather information and opinions from a specific group. But the true power of surveys lies not in the collection of data, but in its analysis.

Survey data analysis is extracting meaning and uncovering valuable insights from the raw responses you've collected.

Through analysis, you can:

  • Identify patterns and trends: See how different groups of respondents answered, allowing you to compare and contrast perspectives.
  • Find relationships: Discover connections between variables in your survey, revealing cause-and-effect relationships or unexpected correlations.
  • Measure satisfaction or sentiment: Gauge the overall feeling of your target audience towards a product, service, or experience.
  • Evaluate the effectiveness of programs or initiatives: Assess the impact of your actions based on how respondents perceive them.

Studying survey results helps you make smarter choices, enhance procedures, and reach your objectives by transforming data into helpful insights.

Types of survey data

Surveys can collect a variety of data, each with its own strengths and uses in analysis. Here's a breakdown of the different types you might encounter:

Quantitative data

This data consists of numerical responses, allowing easy counting and statistical analysis. Think of it as information expressed in numbers. Examples include:

  • Multiple choice questions (e.g., "How likely are you to recommend our product?" on a scale of 1-5)
  • Likert scale questions (e.g., "Rate your satisfaction with the service" on a scale of "Very Dissatisfied" to "Very Satisfied")
  • Ranking questions (e.g., "Rank the features you find most important")
  • Open-ended questions with numerical answers (e.g., "What is your annual household income?")

Quantitative data is ideal for identifying trends, calculating averages, and making comparisons between groups.

Qualitative data: Revealing the "Why" behind the numbers

This data involves text responses, offering deeper insights into thoughts, feelings, and experiences. Here, you're looking to understand the "why" behind the numbers.

Qualitative data helps you understand the reasons behind people's choices. It also helps you discover new themes and gain a deeper insight into your audience's perspectives. Examples include:

  • Open-ended questions (e.g., "What improvements would you suggest for our website?")
  • Short answer questions

"Natural Language Data" can also refer to "Open Ended Questions" in surveys. This term typically relates to a broader field in computer science that focuses on processing human language.

Categorical (Nominal) data

This type of data classifies responses into distinct categories that have no inherent order. Imagine sorting objects into different bins based on their type, not their value. Examples include:

  • Favorite color (red, blue, green, etc.)
  • Preferred brand (Brand A, Brand B, Brand C)
  • Zip code

Categorical data is useful for understanding the distribution of responses across different groups.

Ordinal data

Ordinal data consists of responses that can be arranged in a particular order. However, the gaps between each rank may vary.

Think of placing items on a podium, where 1st place is higher than 2nd, but the difference in "greatness" between them might be subjective. Examples include:

  • Customer satisfaction ratings (Very Satisfied, Satisfied, Neutral, Dissatisfied, Very Dissatisfied)
  • Movie rating systems (1-5 stars)
  • Level of education (High School Diploma, Bachelor's Degree, Master's Degree)

Ordinal data helps you understand not only which category is most popular but also the relative preference between them.

Scalar data

Scalar data is quantitative data with consistent intervals and clear meaning.

It's like measuring temperature on a thermometer, where each degree represents a specific increase in heat. Examples include:

  • Age
  • Income
  • Number of years of experience

Scalar data helps you calculate averages, medians, and ranges to understand the center and spread of your data.

Analyzing your survey data with Formaloo

Once you've collected valuable responses through your Formaloo survey, it's time to transform that raw data into actionable knowledge. Formaloo helps you analyze survey data easily with tools that make the process efficient and insightful.

Here's a step-by-step guide to navigating your data analysis journey with Formaloo:

Step 1: Accessing your data

The first step is to access your survey data within Formaloo. Log in to your account and navigate to the specific survey you want to analyze.

Every formaloo comes with a table and charts for this specific survey.

The table reveals a complete list of all submitted responses. This is where you'll find the raw data – the unprocessed answers from your participants.

Step 2: Exploring responses (Quantitative data)

With the responses in front of you, Formaloo offers several ways to delve deeper. You can review individual responses, gaining a detailed view of each participant's answers and understanding their unique perspective.

Additionally, Formaloo allows you to filter responses based on specific criteria. You may want to focus on feedback from a specific group of people. You may also want to focus on those who responded to a particular question in a specific way.

This filtering capability helps you isolate trends within your data and gain a more nuanced understanding.

Step 3: Visualizing insights in custom charts and tables

Formaloo provides visual tools to display your data clearly and effectively, going beyond just numbers and statistics.

You can get pre-built charts and tables automatically generated based on your survey questions. These visualizations translate your data into easy-to-understand formats like bar charts, pie charts, and line graphs.

Choosing the most appropriate chart type allows you to effectively communicate trends, comparisons, and patterns within your data. Formaloo's interactive charts further empower you to drill down and explore specific data points.

For example, a bar chart can show which product features customers liked the most based on their satisfaction ratings. A pie chart shows the different age groups of people you surveyed, helping you understand your target audience better.

These charts are fully customizable. You can change the colors to match your brand and choose what options to show.

Visualizing insights in custom charts and tables

Step 4: Deeper exploration using Kanban Boards

While quantitative data provides a foundation for understanding trends, open-ended questions offer a deeper layer of insight into the "why" behind the numbers.

Formaloo's Kanban boards are a valuable tool for analyzing these qualitative responses. Kanban boards allow you to create a visual workspace where you can organize and analyze open-ended responses.

Imagine a virtual wall with different sections. You can group similar responses, categorize them by themes, and track their progress through various stages of analysis.

This visual organization helps you identify recurring themes, patterns, and key points arising from the open-ended responses.

Step 5: Leveraging built-in AI analysis

Formaloo takes data analysis a step further with its built-in AI analysis block. This innovative feature allows you to analyze your survey responses directly within the platform.  

To simplify the language, split the sentence into shorter coherent sentences: Add the AzI analysis block to your app. Select your AI model. Input your prompts. Watch Formaloo's AI engine in action.

The AI analyzes your responses and generates a report highlighting key insights, trends, and correlations within your data. This automated analysis saves you time and effort, and helps you understand the reasons behind your results.

Additional tips:

Throughout your data analysis journey, consider leveraging additional tools to enhance your insights. For example, using a website data scraping tool can help you collect relevant data from various online sources, such as competitor insights, industry benchmarks, and customer sentiment. This enriched data allows for deeper comparisons and provides valuable context to your survey results.

By integrating these external insights with your survey findings, you can better align your analysis methods with your goals, ensuring that you extract the most actionable insights. Additionally, Formaloo facilitates exporting your data in multiple formats, making it easy to analyze with other statistical software if needed.

Follow these steps and utilize Formaloo's robust data analysis features to transform your survey responses into meaningful information. With Formaloo, you can uncover key insights that empower you to make informed decisions based on your audience's feedback, ultimately driving positive change.

Turning insights into action

The power of online surveys lies not just in collecting data, but in transforming it into actionable knowledge. By following the steps and using Formaloo's features, you can unlock hidden potential in your survey responses.

Remember, data analysis is an iterative process. As you explore your findings, new questions may arise, prompting you to delve deeper into specific areas. Embrace this curiosity – it's a sign that your analysis is yielding valuable insights.

The ultimate goal is to translate your findings into concrete actions. Use the insights gleaned from your survey to improve products or services, enhance customer experience, or inform future strategies. Let your data be the guiding light, leading you towards positive change.

So, the next time you conduct a survey, don't let the data sit idle. Partner with Formaloo to analyze data and make informed decisions based on audience feedback. Unlock the power of data analysis with us.

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How to analyze survey data