/ Our Expertise
Revolutionizing Business Landscapes with Intelligent Innovation
Utilizing Large Language Models to decode and understand employee sentiments and feedback. Dive deep into a trove of data to gauge, analyze, and enhance workplace satisfaction and engagement.
Harnessing the potential of Large Language Models to unearth nuanced insights into consumer needs and desires. Unlock the secrets of marketing success by understanding consumer behaviors, preferences, and aspirations at a granular level.
Elevate your customer service by leveraging AI's prowess in comprehending feedback, reviews, and interactions. With our advanced text understanding capabilities, optimize every touchpoint, ensuring a more personalized and fulfilling journey for every customer.
In the intersection of Artificial Intelligence and business tools, we offer expertise in Large Language Models and collaborate on technological development. Our APIs allow for straightforward integration into existing processes, enhancing understanding and application.
Navigating the vast world of employee feedback can be challenging, especially when it comes to open-ended responses. These comments often contain the most genuine insights, but they require capacity to extract actionable information. Our specialised service focuses on analysing these open-ended responses from employee satisfaction surveys.
1. Multilingual Analysis: Language diversity shouldn't obscure critical feedback. Our advanced analytical tools can interpret responses in multiple languages, ensuring you grasp the essence of every comment.
2. Cross-Departmental Insights: From tech and product teams to sales and R&D, our analysis ensures comprehensive coverage, making it relevant for diverse corporate sectors.
3. GDPR Compliant: We prioritize data privacy. Rest assured, our service operates in full compliance with the General Data Protection Regulation (DSGVO), ensuring that the data is handled with the utmost confidentiality.
4. Integration with Existing Code Plans: Should you have prior surveys and associated code plans, our system is adept at incorporating these, guaranteeing continuity in your analysis process.
5. Quick Turnaround: Time is essential. Our system is designed for a swift analysis, allowing you to derive insights promptly and implement necessary changes without delay.
Built upon the advanced open-source framework "presidio", we offer a customized anonymization model. This model meticulously scans texts for specific entities such as names, locations, mobile/telephone numbers, and email addresses. Once these data points are identified, they are reliably replaced with placeholders, ensuring the original data remains concealed. What sets our solution apart is its adaptability: it can easily be expanded to include additional, unique elements such as TANs or departmental designations.In today's data-driven environment, safeguarding personal information is of paramount importance. Our anonymization solution ensures that all sensitive data within your texts remain protected and confidential.
We offer a detailed examination of online surveys, specifically focusing on open-ended responses. By analyzing likes and dislikes mentioned by consumers, our service provides insights to understand product feedback and make necessary adjustments. This is a data-driven approach to enhancing product performance.
Check out our product test for our customer Tchibo here.
Our service concentrates on monitoring digital conversations around specific content themes. By observing these discussions, we gain a comprehensive understanding of the prevailing sentiments and trends related to those topics. This method provides a systematic view of consumer perspectives in the digital sphere.
Check out our ai-based social listening project for our customer Mercedes-AMG here.
We assess spontaneous brand associations posed as unaided questions. This approach allows us to analyze Distinctive Assets, understanding the immediate cognitive connections consumers have with brands. It provides a clear view of a brand's presence in consumers' minds.
The Surveybot facilitates nuanced online questioning by dynamically responding to participants' answers. Integrated via REST API into various survey solutions, it enhances both the quantity and quality of responses by providing an interactive, tailored questioning experience for respondents.
Our software specializes in categorizing unaided mentions of brands, products, or individuals. By capturing spontaneous associations, it provides insight into which entities are foremost in consumers' minds, allowing a clearer understanding of the market's mental landscape.
We provide an analytical service for online surveys focusing on open-ended questions, such as likes and dislikes related to a concept. Our specialized analysis of these responses aims to derive insights that can inform and refine the concept under evaluation.
Our service centers on the analysis of online surveys containing open-ended questions, such as likes and dislikes, related to a specific spot or advertisement. We exclusively analyze these open responses to derive insights, enabling refinements to the advertising concept.
We focus on the analysis of online surveys that incorporate open-ended questions pertaining to design elements, such as likes and dislikes. Our sole objective is to analyze these candid responses to extract insights, aiding in the refinement of the design concept.
Our service involves analyzing online surveys with open-ended questions related to advertising claims, capturing likes and dislikes. Through meticulous examination of these responses, we discern what respondents associate with specific claims or which brands they relate them to.
Our service specializes in the automated classification of customer feedback, enabling the monitoring of specific themes or the general sentiment. This feedback can originate from various channels, such as CRM systems, feedback platforms, or social media, ensuring a holistic understanding of the customer experience.
We delve into the analysis of customer feedback to understand the driving factors behind a high or low NPS. By identifying these key themes, our service aims to provide a clearer picture of elements influencing customer loyalty and overall satisfaction.
Our service focuses on analyzing feedback to comprehend the driving themes behind high or low CSAT ratings. Through this examination, we aim to pinpoint specific areas affecting customer satisfaction, offering a more detailed understanding of their experiences.
We analyze customer feedback from various sources, including Amazon, proprietary online shops, and return/complaint channels. Our analysis aims to identify areas for product improvement, streamline ordering and delivery processes, and highlight the strengths of competitive products, offering a comprehensive view of product-related experiences.
We assess customer feedback from platforms like Google Maps, Facebook, and TripAdvisor to understand perceptions about specific locations. Our focus lies in pinpointing areas for on-site improvements, evaluating potential renovation investments, and discerning characteristics of successful competitor locations, providing a holistic view of location-based experiences.
Check out our location analysis case for our customer ECE here.
We examine customer feedback from sources like the App Store, Play Store, and in-app comments to understand user experiences and sentiments. Our analysis aims to identify potential enhancements for the app, streamline in-app ordering and delivery, and discern what sets successful competitor apps apart, ensuring an optimized user experience.
The Cauliflower Text Analytics Engine offers Topic Identification, a feature that discerns significant themes without the need for training data. In a two-step process: 1) Texts are segmented into semantically meaningful parts. 2) These segments are then autonomously grouped and labeled, generating themes from contextually related statements rather than mere keywords.
The Cauliflower Text Analytics Engine provides a Topic Classification feature. This tool assigns texts to predefined topics, with or without the use of training data, offering a streamlined approach to categorizing and understanding textual content.
Beyond basic sentiment analysis, the Cauliflower Text Analytics Engine offers Sentiment Classification at the aspect level, determining the polarity of individual facets using a proprietary solution. It's underpinned by a multilingual model trained on approximately 2 million data points per language from reviews, customer feedback, and open-text responses.
Cauliflower's Summarization feature automates comment summaries at both topic and overall levels, enabling objective selection of verbatim responses and immediate insight into central themes and nuances. Two complementary summarization methods capture both core aspects (dominant voices) and important peripheral topics (topic coverage).