Understand what users love, need, and dislike about your product by analyzing feedback from reviews, surveys, and online discussions.
3,000+ growth-obsessed teams from 90+ countries
create 5 reports in every 30 minutes at Kimola.
Scrape reviews from any mobile app on App Store and Play Store by pasting links of the app or searching the name of the application on home page. Analyze reviews automatically, generate pain points, feature requests and more.
Kimola tracks conversations across social media, news sites, blogs, and forums, helping you stay informed about discussions around your product. Users can also enter links from platforms like Trustpilot, Google Play, and the App Store to continuously monitor user feedback.
For those already collecting user feedback, Kimola allows direct dataset uploads in Excel, CSV, or TSV formats to create structured qualitative research reports. Additionally, users can integrate their Google Sheets, Zendesk, or Intercom accounts, seamlessly connecting existing user interactions to Kimola for in-depth analysis.
Kimola assigns sentiment for each theme in a single user feedback, ensuring you capture every detail—what users like, dislike, and why. Even when a user mentions different topics within the same review, Kimola successfully breaks down feedback into multiple aspects and accurately assigns sentiment to each, so no insight is lost!
Learn about Aspect-based Sentiment Analysis
Kimola's Dynamic Classification™ technology understands context and generates relevant theme clusters without relying on pre-defined categories. It adapts to any dataset, eliminating the need for manual labeling or data annotation. This ensures precise categorization of unstructured feedback from online reviews, surveys, and social media—without human error.
Kimola analyzes competitor reviews alongside your own, revealing differences in user sentiment, feature satisfaction, and common complaints. Identify market gaps, track strengths and weaknesses, and uncover new opportunities. Automated reports and keyword tracking provide real-time updates on shifts in user perception, helping you stay ahead of competitors.
Kimola analyzes large-scale feedback and generates structured executive summaries around key topics and themes. Unlike generic AI-generated text, Kimola offers summaries with sub-sections and with sentiment and content classifications, which provides clarity, focus, and actionable insights.
Learn more about Executive Summary
Kimola analyzes user feedback to reveal what drives purchases, what causes frustration, and how your product is positioned in the market. AI-driven analysis detects patterns across any number of reviews, highlighting key motivations, recurring pain points, and competitive advantages.
Kimola analyzes customer feedback through a four-stage journey framework—Discovery, Purchase Experience, Usage & Support, and Loyalty & Advocacy. By applying its proprietary scoring algorithm, Kimola classifies feedback into these stages to reveal how customers perceive each step, measure satisfaction levels, and pinpoint the critical moments that define brand relationships.
Kimola delivers automated reports in hourly and daily basis to track specific keywords, influence levels, or sudden data spikes. Get notified about 🔔 keyword mentions, 👑 influencer involvements, or 🔺 sudden spikes in the data volume. Each email type has a unique emoji in the subject line, so you can recognize the type of update at a glance—without even opening your inbox.
AI-generated executive summaries present key findings in a structured format, making them easy to interpret and act upon.
Collect and centralize feedback.
Make sense of large-scale feedback.
Turn data into meaningful insights.
Find out how Kimola can improve your feedback analysis process.
Uncover customer needs, likes, and dislikes from product reviews and feedback.
Analyze customer reviews and ratings to optimize online shopping experiences.
Extract insights from social media conversations and online discussions.
Make sense of free-text survey responses with AI-powered analysis.
Understand customer sentiment and concerns from chat and call transcripts.
Identify workplace trends and employee sentiment from internal feedback and reviews.
Product Feedback Analysis is the process of collecting, analyzing, and understanding customer opinions, reviews, and discussions about a product. It helps businesses identify what customers appreciate, what frustrates them, and what improvements they expect. With AI-powered tools like Kimola, businesses can automate this analysis and extract meaningful insights from large-scale feedback.
User feedback directly impacts product success. Analyzing feedback allows businesses to improve product features, enhance user experience, and address pain points before they affect customer retention. It also helps in competitive benchmarking by revealing how a product compares to alternatives in the market.
Kimola analyzes product reviews, survey responses, social media discussions, forum conversations, and customer support interactions. Feedback can be collected automatically from platforms like Amazon, Trustpilot, Google Play, and the App Store, or uploaded manually from custom datasets.
Yes. Kimola provides automated reports and real-time alerts based on keyword mentions, influencer involvements, and sudden spikes in feedback volume. Businesses can set up hourly, daily, or custom reports to stay updated on customer sentiment.
Kimola integrates with Google Sheets, Zendesk, and Intercom, allowing businesses to seamlessly connect their customer feedback data. Users can also upload datasets in Excel, CSV, or TSV formats to conduct qualitative research.
Analyze customer feedback in 30+ languages—no AI training needed.
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