Long before generative artificial intelligence became a boardroom topic, businesses were already sitting on vast amounts of customer data. Reviews accumulated on e-commerce platforms. Support teams handled thousands of calls and emails. Surveys generated spreadsheets full of comments. Social media added another stream of opinions, complaints, and recommendations. The problem was rarely a lack of information. It was understanding what all of it meant.
Most of that information existed in an unstructured form. Unlike financial records or sales figures, customer feedback does not arrive neatly organized. It comes as sentences, fragments, conversations, and observations. For years, companies relied on manual research, surveys, and traditional customer satisfaction metrics to interpret those signals. Yet the growing volume of digital feedback created pressure for technologies capable of analyzing customer conversations at a much larger scale.
That challenge gave rise to a category of software commonly known as voice of the customer analytics. Among the companies that emerged in this space was Clootrack, founded in 2017 by Shameel Abdulla and Subbakrishna Rao. While the company initially positioned itself within customer experience analytics, much of its public narrative over the past several years has centered on a specific technical objective: extracting useful patterns from large collections of customer feedback without requiring extensive manual categorization.
The idea may sound simple. In practice, it is not. Traditional analytics systems often depend on predefined labels and categories. Someone must decide in advance what themes should be tracked, whether complaints relate to pricing, delivery, product quality, customer service, or something else. As customer conversations grow larger and more diverse, maintaining those structures becomes increasingly difficult. New concerns emerge. Language changes. Consumer expectations shift.
Clootrackâs response to that problem has been a thematic analysis approach that, according to company disclosures, relies on unsupervised machine learning techniques. The companyâs technology is associated with Indian patent number 497491, which relates to its thematic analysis system. Public descriptions of the platform state that it can identify recurring themes, trends, and customer concerns from large volumes of unstructured feedback without requiring predefined categories. The emphasis is less on counting keywords and more on identifying patterns that appear repeatedly across customer conversations.
The extent of the problem is one reason why solutions like these have been sought after. According to industry experts, up to 90% of business data is unstructured, and much of it comes in the form of customer dialogues. Reviews, chat, support transcripts, social media comments, emails, surveys, and other types of data may include valuable knowledge that is not easy to uncover using only quantitative metrics. In line with the growing digitization trend of organizations from the 2010s into the 2020s, there was a demand for technology that would analyze those signals more effectively.
As stated by the company, Clootrackâs toolset enables its users to work with more than 95 languages and more than 1,000 data sources. This solution addresses the problem many multinational companies face. Feedback from customers does not come through one channel. For example, complaints about a particular product may appear on a review site, be addressed in the context of customer support, and finally find their way to social networks. Consolidating those conversations has become an essential task for any customer intelligence strategy.
The companyâs technology received wider visibility through a series of product developments that coincided with the rapid growth of generative AI. In May 2023, destinationCRM reported that Clootrack had launched AskClootrack with GPT, a feature designed to allow users to query customer experience data using natural language. The timing was significant. Following the emergence of ChatGPT and similar tools, software vendors across multiple sectors began experimenting with conversational interfaces that could make complex datasets easier to explore.
For customer analytics providers, the appeal was obvious. Business users often need answers rather than dashboards. A product manager may want to know why returns increased during a particular quarter. A customer experience team may want to identify the most frequently discussed service issue. Natural language interfaces promised a different way of interacting with large datasets, reducing the need for complex reporting workflows.
Clootrack continued to expand that strategy over the following years. Company announcements describe a broader transition toward what it calls agentic artificial intelligence. This included the introduction of Clootrack Neo, positioned as an AI Super Agent capable of reasoning across customer feedback and generating insights from multiple sources. In February 2025, the company announced the release of its Agentic Workflow Builder for voice of the customer applications, reflecting a wider industry movement toward systems designed not only to analyze information but also to automate parts of the decision-making process.
The rise of these technologies occurred alongside a larger transformation in enterprise software. Organizations increasingly sought ways to combine traditional analytics with large language models. Partnerships, integrations, and marketplace listings were part of the strategy. Clootrack increased its footprint by being listed on Snowflake Marketplace, Microsoft Azure Marketplace, Genesys AppFoundry, and the marketplace ecosystem of Medallia. Also, Clootrack has been mentioned in Snowflake material regarding prompt engineering and customer feedback analytics.
One of the clearest signs of this change occurred towards the end of 2025. Clootrack revealed that its customers had analyzed over 100 billion OpenAI tokens within its platform. It said that all its thematic analysis workloads were moved to OpenAI models in the year 2024. While the figure originated from company communications, it illustrated the scale at which modern customer intelligence platforms are increasingly operating. What once involved manual analysis of survey responses has evolved into systems capable of processing vast volumes of conversational data.
Clootrack is one company within a highly competitive customer experience technology market. Viewed within a broader historical context, however, its development mirrors a larger change taking place across enterprise software. The industry has moved steadily away from simple measurement tools and toward systems designed to interpret, organize, and explain unstructured information. From its patented thematic analysis technology to the introduction of generative AI features and agentic workflows, Clootrackâs trajectory reflects many of the same forces that have shaped customer intelligence during the past decade.
As businesses continue to generate increasing amounts of customer feedback across digital channels, the central question remains largely unchanged. The challenge is not collecting customer opinions. It is understanding them. For technology providers operating in this space, that question continues to drive product development, investment, and experimentation with artificial intelligence. Clootrackâs evolution offers one example of how that process has unfolded since the company was founded by Shameel Abdulla and Subbakrishna Rao in 2017.
