Analyze customer feedback to automatically get NPS, sentiment analysis, content classifications and summaries.
Kimola is loved by small-mid-sized businesses
and trusted by powerful enterprises across 80+ countries.
3,000+ individuals including product managers, UX researchers,
start-up founders create 5 reports in every 3 minutes at Kimola.
Analyze datasets without hustling with the training process. There is no need for data annotation or manual labeling, so there is no human error. Drag and drop spreadsheets and get your dataset analyzed and classified automatically in minutes.
Kimola offers Dynamic Classification™ technology, which understands the context and generates clusters with a relevant label name. This way, any dataset in any context can be turned into a research report automatically. This is best for qualitative analysis where data is unstructured, such as online reviews, open-ended surveys, or social media posts.
Learn about dynamic classificationAnalyze multiple languages simultaneously, view the analysis for the whole data, or filter by languages. Leverage our AI that scales for global teams.
Kimola can analyze datasets with rows in different languages. This way, customer experience teams handling multiple regions can seamlessly analyze feedback data from review sites or mobile application stores.
Using Kimola's browser extension, scrape online reviews on various mediums, from Amazon to Trustpilot, Tripadvisor to G2, effortlessly with one click.
Kimola brings the concept of Airsets, which is like datasets but on the cloud rather than a file on your computer. All the online reviews scraped from the internet are stored in the Kimola Cognitive account so they can turn into research anytime.
Meet Airset GeneratorClassify long and complex customer feedback data with more than one label and get the sentiment analysis for each label separately, whether the customer feedback comes from short WhatsApp messages or extended conversations on call centres.
Kimola offers Multi-label Classification Technology™, which splits text based on the context and analyses each part by considering how each part contributes to the overall text. This way, single customer feedback data with more than one topic can be a viable source for research accurately.
Meet multi-label classificationUsing GPT technology, transform customer feedback into powerful marketing materials. Leverage Kimola's Open AI integration and save time by summarizing, creating social media content, generating SWO analysis, and even creating new ideas to create an event.
This integration will help you to leverage customer reviews in a different way than ever. Explore the interpretation gallery to get started.
Explore GPT add-onView the gallery of ready-to-use AI models to automatically classify customer feedback for the most common use cases, like sentiment and hate speech analysis, along with consumer conversations around SaaS products, telco companies, banking industry, mobile apps, games and more. Track KPI’s across CX and product teams to understand what customers think about a specific topic.
Use pre-built sentiment classifiers that are fine-tuned for specific use cases. Categorize sentiment into positive, negative or neutral and understand how customers feel with up to 97% accuracy rate.
Choose one or more pre-built content classifier to quickly sort customer feedback into categories, such as product issues or customer service problems. Get a deeper and more precise analysis using specialized industry models with pre-defined or dynamic labels. Identify what needs improvement, what makes customers happy, and what trends are emerging. Turn messy feedback into actionable insights.
Train custom models with a dataset by only dragging and dropping a spreadsheet. Save 90% time while training comparing to other text analysis tools and leverage the no-code training process.
Kickstart your machine learning model journey by dragging and dropping your well-prepared training set in .xlsx, .xls, .csv, or .tsv formats. Wait while the suitability of your dataset for building a machine learning model is being analyzed. Create models with high accuracy rates. Store your models on the dashboard, edit training set if needed after the initial deployment process with bulk upload feature.
Leverage the AutoML technology to craft machine learning models with unparalleled accuracy rates.Leverage automatically rebuilding process of the model using the same AutoML pipeline, ensuring models stay up-to-date and are constructed with the most suitable statistical methods. Benefit from a streamlined process that prioritizes precision and simplicity in model development.
Learn more about custom machine learning modelsKimola Cognitive is famous for it's no training needed technology.
It’s easy to onboard, affordable to subscribe.
Customer feedback is like the inside scoop straight from the customers themselves. It's the lowdown on what people think about a product, service, or brand, and it's super important for companies trying to stay on the ball. You've probably seen it all around, from online reviews and surveys to chit-chats on social media. This kind of feedback is a game-changer for companies, helping them make smart moves and keep up with what folks want.
The power of Artificial Intelligence (AI) has unlocked new possibilities in customer feedback analysis. By utilizing Large Language Models (LLMs) and machine learning algorithms, businesses can now extract invaluable insights from the vast amount of customer comments and reviews available. These advanced technologies are particularly effective in sentiment analysis, allowing companies to instantly identify whether a customer's sentiment is positive, negative, or neutral, and even go beyond to identify specific emotions. With their superior ability to understand the nuances and context of language, LLMs are highly skilled at deciphering complex customer comments and extracting actionable information. This automation and precision have revolutionized the customer feedback analysis process, helping companies to stay on top of customer sentiment and respond to their needs in real-time, ultimately leading to greater customer satisfaction and success.
Using Artificial Intelligence (AI) and Language Model Models (LLMs) for customer feedback analysis offers numerous benefits. Firstly, it enables businesses to process vast amounts of data quickly and efficiently, which is crucial in the age of big data. Rapid analysis empowers companies to identify emerging trends, address issues promptly, and make data-driven decisions that enhance customer satisfaction and loyalty. Additionally, AI can categorize feedback, enabling businesses to identify recurring problems or customer pain points, which can be prioritized for resolution. Furthermore, by tracking sentiment changes over time, companies can gauge the effectiveness of their customer service improvements or product enhancements. AI-driven customer feedback analysis is a game-changer, offering businesses a competitive edge and helping them fine-tune their offerings to meet the evolving needs and expectations of their customers in real-time.
Kimola Cognitive has been a great find for me. I've purchased and used a few similar products before but Kimola stand-outs with many features.
Kimola Cognitive provides an astonishingly good value by helping in understanding customer sentiments better. This tool is godsent and saves a tremendous amount of time!
I love Kimola for team that listens to ideas of their users, focused on user experience and making things easy and chrome extension.
I've never had such great, complete and patient customer support.... ever! Nothing was too much bother.
Longtime AppSumo buying beast here... Kimola is an interesting tool -- certainly a few holes in their documentation and onboarding, but their customer service makes up for it. Much appreciated!
I am using this to scrape Amazon reviews from competitors and then use their product's weaknesses to develop ours and use it for our copywriting on our landing pages.
Love the tool it really helps analyze reviews with ease. I like the browser extension and the in-house analysis tools it makes it extremely easy.
I was looking for a tool to do some statistical and analytical research for my business and I purchased Kimola Cognitive. Hats off to everyone on the Kimola team! Thank you so much!!!
See how Kimola analyzes and classifies a raw dataset and turns into a PDF report.
Pricing is based on query limit, custom model count and support options.
Generate summaries, SWOT analysis, FAQ list
and even product descriptions inspired by your customer reviews dataset in any size.
Kimola Cognitive offers text analysis technology that identifies the dataset's most frequent words and phrases. These are displayed as a word cloud, and they can group words from the same root together. The technology also supports Entity Recognition, which automatically classifies words and phrases into labels like Organization, Person, Work of Art, Location, Nutrition, Interest, Race and Ethnicity, and Disease.
Kimola Cognitive includes pre-built AI models for common use cases like sentiment analysis, hate speech detection, and analyzing customer conversations around SaaS products, mobile apps, and games. These models can automatically classify customer feedback based on these everyday use cases. They are fine-tuned to recognize nuances and jargon, making classification faster and more accurate.
Yes, you can deploy custom AI models in Kimola Cognitive. Since each research project may have unique requirements, the platform allows you to train your own custom AI models using your dataset. Kimola Cognitive automatically selects the best-performing statistical model for your training data to ensure high accuracy. These custom models are hosted on the platform and can be accessed via the web user interface and API.
Kimola offers a web browser extension that research professionals can use to scrape customer feedback from various platforms. This extension simplifies collecting data from over 20 mediums, including platforms like Amazon, Yelp, YouTube, Capterra, and Trustpilot. It helps researchers save time and effort and allows them to focus on analyzing feedback rather than sourcing customer feedback manually.
Kimola offers pricing based on query limits, custom model count, and support options. The pricing ranges from $199 to $999 monthly, depending on the selected plan. Check the specific plan details on the Kimola website for a breakdown of features and usage limits for each pricing tier.
Yes, Kimola is committed to enabling all sizes of businesses, from coffee shops to global corporations, to conduct research by analyzing customer feedback.
To get started with Kimola Cognitive, you can visit the Kimola website and sign up for a free account. Once you've created an account and started your free trial, you can explore the features, choose the plan that suits your needs, and use the platform for customer feedback analysis.
Kimola Cognitive can be used in various industries for customer feedback analysis. It's particularly useful for businesses with a growth mindset obsessed with understanding what customers really need.
Kimola offers support options as part of its pricing plans. These support options may include customer support, training, and onboarding. The specific support options available will depend on your chosen pricing plan. You can typically access support through the Kimola website or by contacting their support team.
Yes, Kimola Cognitive has the capability to handle multiple languages in text analysis and data collection, making it suitable for businesses with a global customer base. Please note that for the most up-to-date information on Kimola and its features, you should visit their official website or contact their support team.
Try the most essential features, from creating to customizing reports, for free.
Start Your Free Trial! No credit card · No commitment · Cancel any time
Let's sign you up.
Join 3,000+ marketing and research
professionals from 80+ countries.
