Using AI to rapidly analyse conversations in the US Heartburn Category

Performing analysis and strategic insights on over 100,000 public conversations and images for a global healthcare company.

The research before the research

A global healthcare company wanted to conduct research on consumers in the Heartburn category through our sister agency, STRAT7 Incite, with whom they’ve partnered many times. 

However, prior to the primary research stage beginning, the healthcare company wanted to uncover what unmet needs existed in the category and identify any emerging ones. 

Performing the pre-fieldwork task would enable the client to test hypotheses and develop an informed, evidence-based view of the category, which would sharpen the subsequent research. It would also capture the themes and exact language used to describe heartburn needs, rather than limiting the analysis to pre-defined keywords and themes. 

By using to rapidly collect, analyse and visualise unstructured data, coupled with our team’s ability to turn that data into actionable insights that guide strategic decisions, we were the perfect partner for this project.


Using, we collected and analysed >100,000 unique public conversations to quickly uncover unmet and emerging needs, as well as capture the voice of the customer.

Analysing 100,000 unique conversations

We used proprietary webscrapers and social media APIs to perform exhaustive data collection on Heartburn from publicly available online conversations. 

Over 100,000 unique conversations, including both text and images, were collected from multiple sources in the United States over from Jan 2021-Jan 2023. Using search queries around heartburn, this vast amount of data was scraped from online forums and various social media channels.

Collecting such an enormous quantity of data ensured we had a sample size that would yield more accurate results from the analysis that followed. 

The next step was to use the data to size the needs and symptoms. While generative AI tools like ChatGPT can also generate a list of needs, they can’t size them using the latest online conversations – but can. 

We used a ‘rules based’ approach to size a long list of needs and symptoms directly from previous research and insight reports which we’d received from the client. 

Each need had particular keywords associated with them, making them easy to cluster together. From there, analysing the data was easy because we could overlay the brands to see where each brand “plays”. 

Overlaying brands like this quickly established what need each heartburn medication was the ‘go to’ for. 

Reliable results informing future research

Our work helped our global healthcare client understand the main needs where they already played, as well as areas where they were behind the competition. It gave them access to a large structured dataset containing verbatim text and images of consumers language and thoughts – all tagged by need, symptom and brand. 

Not only did this insight provide the brand with a lot of context in the customer’s own voice, it also gave our quantitative researchers  at STRAT7 Incite a lot of information with which to write more targeted primary research questionnaires. In particular, the consumer language used to describe heartburn needs helped to generate consumer facing benefit statements, used as direct stimulus for the quant stage.

Uncover insight hiding in plain sight

Publicly available data is an opportunity hiding in plain sight. And AI can help you turn that unstructured data into a competitive advantage. 

Rapidly collect, analyse and visualise data from public or proprietary data. Then let our team of data scientists and market researchers turn it into actionable insights that guide strategic decisions. 

With, each use case is completely different. Speak to one of our specialists to find out how we can help you answer your business questions.


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