Understanding Product & Market Trends Using Open-Source Data (OSINT)

Dec 1 Written By Mida Pezeshkian, PhD

Understanding trends are key to making good decisions in go-to-market (GTM) and product development. The standard frameworks to tackle market size, demand, customer types, buying journey, and positioning are essential to setting a winning product strategy. However, these frameworks do not often take advantage of the wealth of data available in form of open-source (free) or alternative data (fee-based). Use of open-source/alternative data and machine learning has revolutionized access to faster and more valuable insights. These methodologies leverage the power of processing massive amounts data via machine learning with advanced mathematical techniques such as network analysis.

Here, we applied this methodology to look at publication trends (9,964 publications in NCBI) to find articles related to Next Generation Sequencing (NGS) and COVID-19, published from 2017 to 2022. The bar graph below shows NGS (red), COVID-19 (blue) and overlap in both criteria (green). This data can serve as a proxy to better understand the market need and demand for SARS-CoV-2 sequencing products from materials to kits & reagents to data analysis pipelines.

Q1 2020 onward, scientists in academia, government, and industry began to leverage whole genome and targeted sequencing to map SARS-Cov-2 for identification, drug & vaccine development, and monitoring new variants as they emerged. This is apparent from the bar graph above; however, it also shows that sequencing was a small fraction of the total publication rate focused on COVID-19 - useful insight to validate projections. Additional drill down into the data would provide more context into other approaches and areas of focus.

A network analysis of the same data showing COVID-19 (purple) and Sequencing (white) enables a deeper look into topics and their relationship/similarity to each other. These insights can be combined with other data points to highlight areas of interest/opportunity in this space.

Incorporating other open-source data such as Google Trends can serve as another tool to assess interest. As an example, pivoting from sequencing to vaccine development and distribution, which significantly benefited from the work done via sequencing to identify the virus genome, worldwide interest in COVID-19 transitions from COVID-19 (blue) to COVID-19 Vaccine (red). Real-time understanding of this type of interest can aid pharma/biotech companies in the vaccine and/or related markets fine-tune their marketing and GTM strategies.

Open-source/alternative data into machine learning accelerate setting data-driven GTM and product development strategies for market growth and dominance. These methodologies, combined with other market-tested strategies, enable companies to make more informed decisions in all phases of the product life cycle.

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