How to Use AI Chatbots to Collect SaaS Customer Feedback

Illustrator: Adan Augusto
ai chatbots for customer feedback

Gone are the days when SaaS companies had to rely solely on traditional methods like surveys, email threads, and focus groups to gather customer feedback. While these approaches provided valuable insights, they were often plagued by low response rates, siloed data, and a lack of scalability.

Today, SaaS businesses need a more proactive, conversational, and user-friendly approach to collecting feedback. 

Enter AI chatbots. 

These intelligent conversational agents can seamlessly integrate into SaaS applications, websites, and messaging platforms, offering a user-friendly and proactive approach to gathering feedback. These can operate around the clock, allowing customers to give feedback at any time that suits them. Plus, chatbots reduce the need for humans to manually collect feedback, leading to significant cost savings. 

This blog article will discuss multiple ways AI chatbots can revolutionize customer feedback collection for SaaS companies — enabling you to serve exceptional experiences that keep your customers coming back for more. 

6 Ways AI Chatbots Can Collect SaaS Customer Feedback

1. In-App Surveys 

Chatbots can be integrated directly into the SaaS application, proactively prompting users to provide feedback through surveys or forms. These can be triggered at strategic points, ensuring feedback is collected in a timely and contextual manner, for example, after a user completes a task, achieves a milestone, or spends a certain amount of time on a feature.

Let's take an example of using AI in the insurance sector. Chatbots integrated into insurance management tools can proactively gather feedback by triggering a survey after a user completes a policy update or files a claim.

By understanding the user’s journey within the app, chatbots can ask relevant and timely questions that are more likely to elicit thoughtful and accurate responses. Plus, they can personalize survey questions based on user behavior, preferences, and history. 

For example, after a user tries a new feature, the chatbot can ask:  

  • How was your experience with the feature? Please rate it on a scale from 1 to 5 and provide any additional comments.
  • Did you find the new feature useful? What improvements would you suggest?

To implement in-app chatbot surveys effectively, you can: 

  • Utilize survey tools like SurveyMonkey, Typeform, or Google Forms that can be integrated with chatbot platforms.
  • Use the chatbot platform’s native features to create a conversational survey experience.
  • Ensure that surveys are short, relevant, and easy to complete. Use a mix of question types to keep users engaged.
  • Regularly review the feedback collected to identify actionable insights and make data-driven decisions to improve the app and user experience.

This way, you can create a continuous feedback loop that drives product excellence and customer satisfaction. And ensure that feedback is timely, relevant, and actionable, leading to a better user experience.

2. Conversational Feedback

Chatbots can engage in natural language conversations with users to understand their experiences, challenges, and suggestions for improvement. This approach encourages users to share more detailed and nuanced feedback. Plus, they feel more comfortable and willing to share their thoughts.

Open-ended questions play a crucial role in this process. 

Unlike closed-ended questions that limit responses to predefined options, open-ended questions allow users to express their thoughts freely and uncover insights that might otherwise be missed — providing a richer and more comprehensive understanding of user experiences. 

A good example of conversational feedback could be: 

Chatbot: “We recently added a new feature to our app. Have you had a chance to try it out?”

User: “Yes, I tried the new scheduling feature.”

Chatbot: “Great! How was your experience with it? Were there any issues or improvements you’d suggest?”

This follow-up capability ensures that the feedback collected is thorough and well-understood, making it more actionable for the business.

To implement this strategy in your feedback collection process: 

  • Ensure your chatbot uses NLP capabilities to effectively understand and respond to open-ended user inputs.
  • Craft thoughtful and engaging open-ended questions that encourage detailed responses.
  • Use analytics tools to process and interpret the feedback collected, extracting valuable insights and actionable data.
  • Demonstrate to users that their feedback is valued by making visible improvements and communicating these changes back to the user base.

3. Sentiment Analysis

Sentiment analysis, also known as opinion mining, uses natural language processing (NLP) to assess the emotional tone of a user’s message. It categorizes feedback into positive, negative, or neutral sentiments and can also identify specific emotions such as happiness, frustration, or confusion. This helps SaaS companies gain insights into customer satisfaction and identify areas of concern or delight, enabling them to take appropriate actions. 

Chatbots leverage sentiment analysis to tailor their responses based on the user's emotions. This enhances interactions with empathetic and relevant replies, improving user satisfaction and resolving issues more effectively.

For example, when a chatbot detects a negative sentiment, it can immediately alert customer support teams or trigger automated follow-up actions to address the user’s concerns. Similarly, positive feedback can help identify satisfied users who might be potential advocates for the product. 

Additionally, insights from sentiment analysis guide product development by highlighting features that users love or find problematic. Positive feedback on a particular feature can enhance its performance, while consistent negative feedback might prompt a redesign or improvement.

Here are two examples: 

Negative Feedback 

User: “The new update is terrible. It keeps crashing.”

Chatbot: “I’m really sorry to hear that you’re having trouble with the update. Can you tell me more about when the crashes occur? I’ll make sure our support team looks into this right away.”

Positive Feedback

User: “I love the new feature! It’s exactly what I needed.”

Chatbot: “That’s fantastic to hear! We’re glad you’re enjoying the new feature. Is there anything else you’d like to see in future updates?”

4. User Ratings 

Chatbots can strategically prompt users to rate their experience after specific interactions or milestones within the application. For example, after completing a transaction or achieving a goal, the chatbot can ask, "How would you rate your experience?"

Additionally, chatbots can prompt users to rate specific features or functionalities within the application. 

By capturing user ratings in real time, chatbots ensure that feedback is collected when it's most relevant to the user's experience, increasing the likelihood of accurate responses. Plus, businesses can gather granular insights into which aspects of the product are performing well and which ones may require improvement. For example, sudden drops in ratings may indicate emerging issues that require immediate attention.

To collect feedback via user ratings: 

  • Use customizable rating scales, such as a star rating system or a Likert scale, tailored to the specific context of the feedback being collected.
  • Integrate chatbots with analytics platforms to automatically aggregate and analyze user ratings, providing actionable insights for decision-making and product development. 
  • Ensure that the rating prompts presented by chatbots are user-friendly and intuitive, maximizing participation and response rates.

Overall, chatbots provide an interactive and engaging platform for users to provide feedback. Users are more likely to participate in feedback collection when it's integrated seamlessly into their interactions with the application.

5. Gamification and Incentives

Gamifying the feedback process through chatbots involves integrating game-like elements into the feedback collection process to incentivize user participation and engagement. 

SaaS companies can offer rewards, such as discounts, coupons, or loyalty points, to users who provide valuable insights through feedback. This creates a win-win situation where users are motivated to participate, and businesses gain valuable feedback.

Here’s how it works: 

Chatbots can present users with feedback challenges or missions, such as providing feedback on a specific feature or completing a series of feedback tasks within a given timeframe. Users who successfully complete these challenges can earn rewards or badges. This can encourage users to provide more detailed and insightful responses over time.

Also, create interactive quizzes or trivia games related to the product or service, where users can earn rewards for answering questions correctly or providing insightful explanations.

In short, by utilizing gamification in the feedback process through chatbots, businesses can transform feedback collection into an interactive and rewarding experience for users, driving higher levels of engagement, participation, and valuable insights.

6. Multimodal Feedback Collection 

Chatbots can accept feedback in various forms beyond just text, such as voice recordings, screenshots, videos, or annotated images. This caters to different user preferences and provides richer context. Plus, users can express themselves naturally, just as they would in a conversation, without the constraints of typing.

While voice feedback accommodates users with disabilities or those who prefer verbal communication, screenshots or images are useful for reporting visual issues, UI/UX feedback, or demonstrating specific features or bugs.

Chatbots also encourage users to record short videos to demonstrate issues they encountered, provide walkthroughs of specific features, or offer testimonials and suggestions. 

For example: "Would you like to record a quick video explaining the issue you faced during the onboarding process?"

This way, customers can convey emotions, tone, and non-verbal cues that may not be captured effectively through text or images — providing richer context to their feedback.

Overall, this multimodal approach fosters more meaningful interactions between users and businesses, leading to improved products, services, and customer experiences.

Final Thoughts 

By leveraging these actionable methods, SaaS companies can collect rich, contextual, and highly targeted feedback from their users, enabling continuous product improvement and exceptional customer experiences.

So, incorporate AI chatbots into your feedback strategy today and empower your SaaS business to thrive in the ever-evolving digital landscape.