Customer Experience

7 Common Challenges in In-App Feedback Analysis

Nov 27, 2023

8 mins read

Manisha Khandelwal

Imagine you spend most of your time on social media apps because you love sharing pictures. But today you’re unable to upload multiple photos in one post – a technical glitch. 

Now after a few days, while using the app (as you’re a frequent user), an in-app survey popped up. 

You leveraged this moment and explained the issue step by step. You gave detailed feedback and suggested making it easier to add multiple pictures and organize them in a single post.

This is the power of conducting in-app feedback. 

Powered by a robust in-app feedback tool, this detailed feedback helps the developers fix the glitch and improve the app.

But wait. This was just one instance. 

What would you do if you got more than THOUSANDS of qualitative in-app feedback? 

And how would you know which ONE is important from all the comments and ratings?

Well, this is a hectic task. 

That’s where we come in with this blog exploring how to simplify the complex task of in-app feedback analysis by resolving these common 7 challenges. 

7 Challenges in In-App Feedback Analysis

Here are the challenges that most encounter while analyzing the gathered in-app feedback. With this, you’ll not only transform a myriad of comments, ratings, and suggestions into actionable insights but also know how to prioritize improvements based on diverse user perspectives.

Challenge 1: Low User Participation

The first challenge is less participation of users because not all users are open to expressing their thoughts. Also, they: 

  • Can’t find the feedback button, like having something to say but not knowing where to speak up.
  • Do not feel motivated to share thoughts if they don’t see the value or get any rewards for it.
  • Privacy worries them from speaking up if they’re concerned about their feedback not being secure.

So, what to do to increase user participation?

To overcome this challenge and encourage more users to participate, consider implementing the following strategies. 

A screenshot of the Jira in-app survey asking how your editing experience on the 5 emoticon scale from very angry to very happy and then asking the second open-ended question to gather targeted in-moment feedback

  • First, ask the feedback right there in the app and not on the other channels because they tend to ignore it.  Make the feedback prompt highly visible and user-friendly like Jira. Ensure users can easily find and use it, eliminating any hurdles in sharing their thoughts. 
  • Secondly, offers incentives for providing feedback, such as small rewards or discounts, creating a tangible benefit for users to engage just like Google. 
  • Lastly, emphasize the value of users’ feedback by actively incorporating their suggestions into app improvements. Additionally, consider integrating OAuth (Open Authorization) for a seamless and secure login experience. This not only enhances user trust but also simplifies the feedback process, contributing to increased user participation.

When users see the direct impact of their input, they are more likely to feel valued and motivated to contribute regularly, fostering increased user participation.

Challenge 2: Feedback Bias

Feedback Bias is when the feedback you get is mostly from users who love or strongly dislike something, creating an unbalanced view. This happens because these extreme feelings prompt users to share their thoughts more often.

For example, if you mainly listen to those who love the app (the promoters), you miss what others think. This can mess up the overall understanding of what all users feel. Fixing this bias is tough because it’s hard to know where it’s coming from.

So, what to do to resolve this challenge?

To handle this, you should use the following strategies: 

  • First, make sure you’re hearing the voice of the customersthose who like the app a lot and those who don’t love it as much. This gives a more honest picture. 
  • Second, use tools like Text Analytics to spot feedback that’s too positive or negative. This helps keep things balanced. 
  • Lastly, check feedback against other information, like what users do in the app or any issues they report. 

Doing this helps confirm if the feedback is on track and gives a more reliable picture of what users really think.

Challenge 3: Noise and Ambiguity

This challenge refers to the difficulty in dealing with irrelevant or unclear feedback. It makes it difficult to extract meaningful insights from user comments. There are chances that users provide feedback in various formats or use technical details or industry words, adding complexity to the analysis process.

So, what to do to resolve this challenge?

To make things simpler, try the following strategies:  

  • Regularly clean up and check your feedback for anything that’s not useful or up-to-date. This ensures you’re working with feedback that matters. 
  • Ask users clear and short questions to get straightforward feedback and avoid confusion. 
  • Use tools that understand the language users use, even if it’s a bit complicated, so you can figure out what they’re saying. 

These steps help you analyze your feedback smoothly and gather reliable insights.

Challenge 4: Limited Data and Context

You get limited data and context when you conduct the in-app survey. But that’s not sufficient. Because users share their thoughts, but we often miss important details about them, like how they use the app. This missing context makes it harder to fully understand what users need. 

So, what to do to resolve this challenge?

To resolve this, implement the following strategies: 

  • Use analytics tools like Mixpanel, Google Analytics, etc. to track how users behave in the app. This gives you more information about what users do. 
  • Talk directly to users through interviews and surveys to gather detailed data about their experiences. This personal touch provides nuanced insights that go hand in hand with in-app feedback. 
  • Keep an eye on social media too; it gives you a different angle on what users think beyond the app. 

By combining these strategies, you get a fuller understanding, making it easier to make informed decisions based on both in-app feedback and valuable contextual data.

Challenge 5: Prioritization and Actionability

Managing in-app feedback can be tough because there’s a lot of it, making it hard to find the most important insights. Even when you find valuable feedback, making changes based on it can be tricky. 

So, what to do to prioritize and action feedback?

To address the challenges of prioritization and actionability, consider incorporating these strategies into your approach:

  • Begin with customer segmentation and tagging feedback to create a structured system. This makes it easier to sift through and identify patterns. 
  • Look for recurring themes and patterns within the feedback, highlighting the issues that appear most frequently. This helps in identifying the areas that require immediate attention.
  • Use feedback as a guiding force for your product roadmap. 
  • Align feedback with your development roadmap to ensure that user suggestions are not only acknowledged but actively influence the direction of your app’s evolution. 

These strategies empower a more efficient and effective process for prioritizing and acting on user feedback.

Challenge 6: Sentiment Analysis

A gif showing how SurveySensum’s Text Analytics Software works to analyze the gathered qualitative feedback by creating tags, and themes. 

How do you know WHAT your users actually mean in their feedback, especially in open-ended feedback?

This can be confusing, right? 

Because sometimes, they express their feelings in a way that’s not straightforward, making it hard to get the exact meaning. Also, dealing with sarcasm and irony in feedback adds another layer of complexity, as it requires a sharp understanding to know if users are genuinely criticizing or just playing around.

So, what to do to resolve this challenge?

To resolve this issue, you should use a sentiment analysis tool. This tool looks at the words users use and figures out if their feedback is positive, negative, or neutral. By adding this tool to your feedback analysis, you can get a clear sense of what users are saying and better identify areas to improve. 

Analyze Your In-App Feedback with Text & Sentiment Analytics

Challenge 7: Volume and Variety of Feedback

How are you dealing with tons of user comments?

This is indeed a big challenge. It is hard to go through all of them and understand what users are saying. Plus, users express themselves in different ways, using text, images, and videos. This mix of feedback formats makes things more complex.

So, what to do to resolve this challenge?

To resolve this challenge, you should: 

  • Use tools that group similar feedback, making it less overwhelming. This helps manage the large number of comments. 
  • Use a feedback system like SurveySensum. Its Text Analytics software categorizes customer’s qualitative responses as positive, negative, and neutral. After categorizing the gathered responses, you get the trends and pain points on which you can make decisions. This way, you get the full picture of what users are saying in various ways. 

By implementing the actionable strategies, you can resolve all the given challenges. 

Wrapping Up, 

The importance of in-app customer feedback cannot be overstated. It stands out as a valuable resource, providing a direct line to user experiences and preferences. While the challenges of analyzing this feedback can be complex, addressing them unlocks valuable insights that pave the way for enhanced product experiences. 

You can resolve all the given challenges that are most commonly faced by employing feedback aggregation tools, sentiment analysis, and versatile feedback management systems like SurveySensum. With this, you can streamline the analysis process. When effectively implemented, feedback analysis not only transforms challenges into opportunities but becomes a catalyst for continuous improvement. 

Manisha Khandelwal

Senior Content Marketer at SurveySensum

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