Surveys give you direct insight into what your users think about your product, but manually combing through responses and pulling out the most relevant information can take more time than you have.
AI (artificial intelligence) tools can take thousands of responses and turn them into actionable product insights. Use this guide to understand how to use AI to analyze your data and how to select the right AI tool for your product team’s needs.
Challenges with Manual Survey Analysis
Some problems can come with doing traditional survey analysis the old-fashioned way:
- It takes a lot of time. Manually processing data can be incredibly time-consuming, especially when there’s tons of data to go through. First, you have to input and organize the data in excel sheets. After that, you have to analyze it closely enough to pull useful insights from it.
- It can be inaccurate. When you manually analyze surveys, you might only focus on the obvious takeaways and overlook meaningful hidden connections between data points. Without seeing the complete picture, you could form incomplete or even incorrect conclusions about user preferences, trends, and patterns.
- It’s prone to bias. When analyzing surveys yourself, you might subconsciously allow some of your opinions to sway how you interpret user feedback. This can make your conclusions less reliable since they incorporate personal ideas and biases.
- It often leads to human error. Going through numbers and open-ended responses by yourself, without any tools to assist, is a recipe for human error. You might miscalculate an important figure or miss the full context of why users are saying they aren’t happy with your product experience.
Introduction to AI in Survey Analysis
AI refers to technology that's designed to think and learn like humans. Machine learning (ML), a subset of AI, is any algorithm-based product that reviews data, learns from patterns, and makes predictions or decisions based on that process.
When used for analyzing surveys, AI puts ML to work to process, analyze, and pull insights from survey data. It quickly sifts through vast amounts of responses to identify trends and correlations that you might not notice otherwise. Plus, with AI, human error is no longer in the equation, and there’s less bias too. You’ll get near-perfectly objective insights that reflect the true nature of your data.
AI-powered analysis is almost entirely automated, so you’ll cut down on the time and effort traditionally required for analyzing surveys. It also captures the most important parts of your data in real time. On top of that, it gives you a thorough and accurate understanding of both your quantitative and qualitative data.
You'll see this power in action when you use Sprig’s AI Analysis. Our tool analyzes survey responses in real time and instantly generates digestible summaries from large volumes of data. It highlights current and emerging user trends while also pinpointing opportunities to optimize your product. This all requires little effort from you while delivering highly impactful insights.
Tools and Technologies in AI for Survey Analysis
When considering an AI tool, make sure it has the following features:
- Natural language processing (NLP). This feature gives you a better understanding of user responses to open-ended survey questions. Sprig’s language processing models pull from millions of data points to understand exactly what open-ended survey responses mean. It looks beyond keywords and phrases to the full context to meaningfully show you what users are really saying.
- Predictive analytics. AI algorithms use predictive modeling to forecast trends so you can anticipate future preferences based on your latest survey responses. These advanced models identify patterns in user responses and generate predictions so you can make product decisions that keep you ahead of the curve.
- Real-time insights. Waiting days or weeks for survey results to come in slows down your decision-making and makes it tougher to adapt to changing circumstances. Advanced AI tools solve this problem since they generate and analyze survey results in real-time. Sprig’s In-Product Surveys prompt users to provide feedback about your product as they’re using it. This way, you reduce recall bias and get actionable insights to use for immediate improvements.
- Automation. Cleaning and organizing data manually is usually pretty time-consuming and error-prone. AI tools’ robust automation capabilities make your job way easier since they take your most tedious tasks off your plate. Robust automation features accurately process your data and efficiently organize it with minimal work on your end.
- Integration with survey platforms. Your AI tool and survey platform should go hand in hand — and when you use Sprig, you get both in one. Gather feedback from users and analyze their responses on the same platform, eliminating the need to transfer data.
Real-World Applications
Noon Academy is an e-learning platform offering tutoring services for students across eight countries. To improve social engagement, the company introduced online study groups where students could discuss lessons together. Following the launch, Garrett Groszko, Noon’s design director, wanted to ask certain groups of students about their experience using the new feature. However, sending surveys to students across several regions and languages posed a significant challenge.
That’s where Sprig came in. The Noon team used Sprig’s simple, efficient in-product surveys to target 10th through 12th graders without disrupting their experience in the app. The survey prompted students to rate their level of satisfaction with the group session. It also asked an open-ended question to students who gave a low rating. Sprig’s AI analysis then processed all the student responses, grouped them into themes, and reported common issues students were experiencing.
Two themes were most common: bugs within the platform and students needing help during sessions. The team took the insights they received from Sprig and added helpers throughout the platform along with information items to simplify navigating the app.
“It’s absolutely amazing for us to find themes that we might not have seen ourselves,” Groszko said. “It’s super helpful.”
After rolling out the changes, the Noon team saw a 192% increase in the frequency of students using the platform’s social interface. The updates also resulted in a 74% increase in student participation during the sessions. Since then, Noon has continued using Sprig to monitor its student experiences across regions, better understand users, and expand its reach across the globe.
Best Practices in AI-Powered Survey Analysis
Ensure Data Quality and Integrity
Great survey analysis starts with great data. To gather the best responses from your surveys, review your questions to make sure they’re engaging and inclusive to all groups. You should also carefully review your surveys to confirm that they’re relevant and that they’re effectively reaching your intended audience. The goal is to prompt thoughtful responses that provide valuable insights into your user base. Review our templates for survey ideas and expert recommendations.
Prioritize Ethical Considerations and Privacy Concerns
Make sure your users know they’re participating in a survey. To promote transparency and trust among users, avoid disguising survey questions as anything besides opportunities for users to provide their feedback about your product.
Continuously Update and Train Your AI Models
Retraining your AI models is like giving your computer an update. When additional information becomes available or your dataset grows, update your AI tool with any preferences, criteria, or requirements needed to analyze your data. You can do this yourself or hand over the process to automation tools that specialize in improving your AI program’s data tracking and monitoring.
Let Sprig AI Do the Work
Sprig AI automates data processing and uncovers valuable patterns in survey responses. No more recall bias — Sprig’s In-Product Surveys prompt users to give feedback while their product experience is still fresh in their minds. As responses flow in, Sprig AI, powered by GPT, reviews and analyzes them. It turns raw feedback into comprehensive insights you can use to optimize your product. Improving your customer satisfaction is straightforward with Sprig.