Online surveys have become an indispensable tool for gathering data and insights across industries. As per Statista, the global online survey software market is projected to grow from $7.31 billion in 2022 to $13.98 billion by 2026.
However, simply fielding surveys is not enough. To derive value, companies need to rigorously analyze the collected data. This allows them to spot trends, identify issues, and uncover actionable insights to guide strategy and planning.
In this 2600+ word guide, we will explore:
- The types of data collected via online surveys
- A step-by-step framework for analyzing online survey data
- How crowdsourcing can enhance survey analytics
- Useful resources for conducting online surveys
Let‘s get started!
The Explosive Growth of Online Surveys
What‘s driving more brands to adopt online surveys? Here are some key factors:
Lower Costs: Online surveys cost 70-80% lesser than phone surveys as no interviewers are required. Self-administered formats are more scalable.
Better Access: Web and mobile-based surveys allow for broader, global reach. Companies get wider demographic coverage.
Higher Quality: Online questionnaires lead to less interviewer bias or variability. Response accuracy is higher with lower social desirability bias.
Faster Turnaround: Automated collection and analytics accelerates insight generation. Changes can be incorporated quicker into strategies.
As a result, the global online survey software industry is witnessing steep growth:
Data Source: Statista
North America contributed the highest revenue share of 40% in 2022 due to faster digital adoption.
But the Asia Pacific region is anticipated to grow at 16.5% CAGR from 2022-2026 – the highest globally. Explosive internet penetration here will drive online surveying demand.
Leading Online Survey Software Vendors
As per Survey Monkey’s market share analysis report, the top survey tools by market share in 2022 are:
SurveyMonkey leads, but Qualtrics is the fastest growing vendor – expected to overtake SurveyMonkey this year.
Typeform has carved out a niche with their conversational, mobile-first surveys while Google Forms attracts smaller businesses with its free plan.
Next in our analysis is an overview of the data types collected via online surveys and how to measure them.
Types of Data Collected in Online Surveys
Online surveys can collect both quantitative and qualitative data. Understanding the difference is crucial for analysis.
Quantitative Data
This refers to close-ended survey questions with numeric responses. For example:
- On a scale of 1-10, how likely are you to recommend us?
- How many times have you contacted customer service in the last year?
Quantitative data allows you to spot trends, benchmarks metrics, track changes over time and more.
Qualitative Data
These are open-ended survey questions that collect text responses. For example:
- Why do you prefer self-service over calling our agents?
- Please describe your last experience at our store.
Qualitative data provides color and context to quantify results. It allows you to understand motivations, capture sentiment, spot pain points and more.
4 Levels of Measurement
Classifying survey questions across four levels of measurement is key for analysis:
Nominal – Categorical data without order. Example: Gender, department, location.
Ordinal – Categorical data with order. Example: Satisfaction scale from highly dissatisfied to highly satisfied.
Interval – Numerical data with order and equal distances. Example: Temperature in Celsius or Fahrenheit.
Ratio – Numerical data with order, equal distances and a true zero point. Example: Revenue, age, time taken.
With this context on data types, let‘s move to the analysis process next.
6 Steps for Analyzing Online Survey Data
Follow this framework:
1. Understand Your Data Types and Measurement Levels
Carefully go through all survey questions and classify them as quantitative or qualitative.
Further segment quantitative questions as nominal, ordinal, interval or ratio.
This allows you to apply the appropriate analysis technique for each data type later.
2. Start With Quantitative Analysis
As numeric data is structured, analyzing it is faster and simpler.
Use descriptive statistics like counts, means, medians and more to spot patterns.
Conduct statistical tests like T-tests, ANOVA, regression and more for deeper insights.
3. Develop a Coding Framework for Qualitative Data
Manually go through open-ended text responses to create a taxonomy of key themes and concepts.
Tag responses under relevant themes to quantify results for analysis.
4. Optionally, Use NLP to Analyze Open-Ended Responses
Leverage natural language processing (NLP) to automatically detect themes and assign tags to responses. This exponentially scales qualitative analysis.
For instance, algorithms can analyze sentiment, categorize queries, extract keywords, recognize named entities, detect topics and more.
5. Visualize Key Findings
Use charts, graphs and dashboards to create powerful data stories and surface insights.
6. Derive Actionable Recommendations
Leverage your analysis to guide business strategy and planning across functions like marketing, product, CX and more.
For instance, the marketing team could create new campaigns to target high-value yet dissatisfied segments based on survey findings.
Now that we have covered core analysis steps, let‘s explore how crowdsourcing boosts this process.
The Power of Crowdsourcing for Online Survey Analytics
Companies can amplify and scale analysis by tapping into crowdsourcing services like:
Some key benefits:
Diverse Expertise
Get perspectives from a global community with varied backgrounds in different industries.
Operational Scalability
Manage sudden spikes in analysis workloads cost-effectively.
Cost Efficiency
Pay only for work done vs having dedicated internal teams.
Data Standardization
Get the crowd to clean and prep unstructured data.
Enhanced Qualitative Analysis
Automate tagging and categorization of open-ended responses.
In summary, crowdsourcing introduces sophisticated efficiencies into the survey analysis process.
Step-By-Step Guide to Crowdsourced Sentiment Analysis
Here is a playbook for leveraging crowdsourcing to analyze open-ended survey responses:
1. Clean Unstructured Data: Fix spelling errors, typos, remove stop words, expand contractions in responses with the help of the crowd.
2. Create Coding Taxonomy: Develop a codebook of themes and sentiments with examples based on a subset of responses.
3. Distribute Responses: Randomly allocate entire dataset across analysts for tagging.
4. Ensure Quality: Use test questions and statistical models to evaluate accuracy and remove underperforming analysts.
5. Analyze Tags: Aggregate tags across responses to quantify themes and run statistical analysis.
6. Visualize Insights: Create charts on response categories and corresponding sentiment analysis.
For instance, 35% mentioned price as an issue. Of this, 60% expressed negative sentiment.
Such structured analysis uncovers precise problem areas to address.
Crowdsourcing platforms like Appen promise over 99% accuracy in text classification with such workflows. Their global crowd support 50+ languages handling millions of tasks daily.
However, manually reviewing work quality and handling data security remain key risk considerations. The need for tight supervision can drive costs.
Despite limitations, crowdsourcing delivers higher scalability and effectiveness compared to purely manual approaches.
Next let‘s explore recommendations for software tools and survey participant panels to assist with online data collection and analysis.
Useful Resources for Online Surveys
Conducting end-to-end online surveys requires the right set of tools and services. Here are some recommendations:
Survey Software
1. SurveyMonkey – Easy-to-use, great basic analytics. Top choice for beginners.
2. Qualtrics – Enterprise-grade advanced features. Ideal for large businesses.
3. Typeform – Build conversational, interactive surveys. Mobile optimized.
4. Google Forms – Free option good for small surveys. Integrates with Google Workspace.
5. SurveyPlanet – Cost-effective packed with features. Limited style options.
6. SurveyGizmo – Powerful advanced logic and complex workflows. Steep learning curve.
View detailed comparisons of 36+ top survey tools here.
Participant Recruiting
Getting responses from your target audience is vital for quality insights. Panel providers grant survey access to millions of participants globally:
1. Prolific – Over 215,000 active, high quality participants. Fastest responses.
2. Respondent – Enterprise-grade panel with hard-to-reach respondents. Gets niche audiences.
3. Cint – Panel with over 100 million members. Budget-friendly pricing.
4. Lucid – Combined market research and survey panel features. Above average response speed.
5. SurveyMonkey Audiences – Fully integrated panel within SurveyMonkey. Lower participant quality than dedicated providers.
Learn how the top survey participant recruitment services stack up on 50+ criteria here.
Key Takeaways
- Online surveys allow brands to capture quantitative and qualitative data at scale. Robust analytics unlocks hidden insights.
- Classify data types and measurement levels before analysis. Coding frameworks help tag qualitative data.
- Visualizations make statistical analysis consumable. Crowdsourcing adds sophistication.
- The right survey software and access to target participants ensures high-quality data collection.
I hope this 2600+ word guide serves as a detailed yet digestible overview of online survey analytics essentials in 2024 and ignites your curiosity to learn more. Reach out in comments below or connect with me if you need help executing survey analytics for your organization.