Introducing Caplena 3.0

Text analysis tools like ours and quantitative analysis tools have coexisted for some time, yet no solution has truly succeeded in combining these perspectives. The challenge no longer lies in the basic methods themselves– statistics and LLMs are well established – but in distilling the vast array of potential metrics into insights that move the needle for business. With Caplena 3.0, that’s exactly what we’re aiming to achieve, and we couldn’t be more excited.

After securing our latest funding round last July, we are launching our new product version on January 30, 2025. This major update – Caplena 2.0 was launched in 2022 – marks our evolution from a text analysis tool to a feedback analysis platform.   

Caplena has established itself as a go-to solution for analyzing the voice of customers or employees at scale, handling feedback from all sources, surveys and reviews, while serving leading brands and market research companies like DHL, Lufthansa and Euromonitor. 

This new product version is the result of 18 months of hard work. It is a complete revamp of the application for peak performance, security, scalability and a sweet new design ✨👩‍🎨 .   

So, what makes Caplena 3.0 stand out? 

We have designed our new platform with the vision of combining feedback with quantitative variables, while placing generative AI at its core. With this approach, we aim to pioneer new ways to discover insights and help engage with data more effectively. 

It builds on our award-winning topic-level sentiment analysis feature and our transparent approach to AI: not a black box, but coding you can fine-tune and control for full confidence in your results 🔎.
 

Key Features 

• One-click reports: an enhanced library of pre-built “Insights elements” (from NPS & star-rating reports to driver analysis and trends) to accelerate time to insights. Of course including the hottest LLMs for AI-generated summaries and actionable improvement recommendations, but also old-and-proven techniques like highlighting statistical significance.

• InsightChat: an LLM-powered chatbot interface to answer your insights questions, from a quick dip into a qualitative topic summary to a deep dive on quantitative differences between segments.

• Multi-source analysis: as customers often analyse different data sources (like in-store and online surveys, or App store and Play store reviews), they can consolidate sources and analyze them across quantitative and qualitative data to see how they differ.  

• Continuous topic detection: as your customers and the world around them aren't static, the topic model should evolve with them. Caplena is now able to highlight new topics that emerge in the data - or might have been missing all the way, if you are just bringing your data into Caplena. Users can also be notified when new topics are detected. 

• Alerts: to stay on top of changes, alerts can be set to stay on top of (significant) changes in topic mentions or sentiment over time.

Finding insights in surveys, trackers and online reviews is still a challenging task. With our new platform, we are enabling researchers to uncover deeper insights faster while staying up-to-date with changes in text feedback effortlessly.

Our detailed high-quality text-analysis will elevate CX teams to base their insights on human-level coding across multiple data sources like online reviews and customer satisfaction surveys in a seamless process.

Curious to see more? Join one of our upcoming webinars for an action-packed guided tour, or book a 1:1 call with our friendly team.

And we're far from done building 👷‍♂️🏗️. Stay tuned for more to come soon.