Caplena transforms from text analysis tool to feedback analysis platform with the launch of Caplena 3.0.

Caplena 3.0 sets a new standard for feedback analysis platforms with a completely revamped UI, enhanced performance, and next-level features.
  1. Home
  2. Newsroom
  3. Caplena transforms from text analysis tool to feedback analysis platform with the launch of Caplena 3.0.
Date 29 January
Author Marina Roman Herrera

After securing its latest funding round last July, Caplena is launching its new product version on January 30, 2025. This major update – Caplena 2.0 was launched in 2022 – marks the evolution of Caplena 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 has been developed over the last 18 months. It includes a complete revamp of the application for peak security, performance and scalability.

Most importantly, Caplena 3.0 comes with next-level features to help businesses to make data-backed decisions thanks to faster, deeper, actionable insights.

What makes Caplena 3.0 stand out? Caplena 3.0 builds on its award-winning topic-level sentiment analysis feature and its transparent approach to AI, allowing for fine-tuning and control.

It was designed with the vision of combining feedback with quantitative variables, while placing generative AI at its core. This approach aims to pioneer new ways to discover insights and engage with data more effectively.

Key Features

  1. One-click reports: an enhanced library of pre-built “Insights elements” (from NPS & star-rating reports to driver analysis) to fasten time to insights, now including AI summaries with recommendations for improvement.

  2. InsightChat: an LLM-powered chatbot interface to chat with your insights, from a quick answer to a deep dive into qualitative and quantitative data

  3. 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 them across quantitative and qualitative data to see how they differ.

  4. Continuous topic detection: as any analysis should be adaptable to new topics that emerge in the data (or research questions that change), users are now notified when new topics are detected.

  5. Alerts: to stay on top of changes, alerts can be set when existing topic sentiment or mentions change significantly over time.

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.

Maurice Gonzenbach, co-founder of Caplena

Finding insights in surveys and online reviews is still a challenging task. With our versatile AI research assistant InsightChat, our new reporting and our tools for CX monitoring, we are enabling researchers to find deeper insights quicker and to allow them to keep informed on changes in text feedback. 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.

Pascal de Buren, co-founder of Caplena

Marina Roman Herrera
ESOMAR Staff, Digital Marketing Specialist at ESOMAR