Growing Market Share for MedTech Products with AI-Enabled Market Intelligence

In the competitive landscape of medical technology (medtech), accurately assessing and growing market share is a significant challenge faced by senior executives and commercial managers. Often, they are presented with product-specific inquiries for very specific geographies, driven by an awareness that an opportunity may exist but lacking the quantitative data necessary to validate market potential and justify investment. Even if their organization is active with the product and in the region in question, there may be issues with relying on data from local sales teams and distributors. This post explores a strategy to address these challenges using market intelligence enabled by artificial intelligence (AI).

The Need for Reliable Market Intelligence

Accurate market intelligence is critical for making informed decisions about market entry, expansion, and investment. However, one of the most common issues is the reliance on narrow data sources or outdated information.

Challenges with Traditional Data Sources

Regional sales teams and distributors often serve as primary sources of market intelligence. While their anecdotal information can be valuable, relying solely on them can be problematic due to potential biases and a lack of broader market perspective.

• Sales Teams: Focused on closing deals, sales teams may provide biased or incomplete information, leading to overestimation of demand or underestimation of competition. Their portrayal of the company’s position in the market may be overly positive, lacking objectivity.
• Distributors: Distributors’ market intelligence might be limited to their specific product lines and customer base, resulting in a skewed view of the overall market. Additionally, distributors may be competitors and therefore unwilling to share detailed information.
• Syndicated Reports: Off-the-shelf reports, typically produced annually, rely heavily on limited supplier-provided data and desk research. These reports often lack the timeliness and depth needed for actionable insights at a local level.

Pairing big data with AI can help to overcome many of these challenges, namely:

• Providing data accuracy.
• Removing data silos.
• Speeding information delivery.
• Enabling a broader perspective.
• Increasing objectivity.
• Eliminating sales bias.
• Removing time constraints.

Without Quality Data, there is No AI

But to achieve this objective, you must first have a large repository of quality data followed by the ability to extract and structure data based on specific criteria. We use big data in the form of several years’ worth of tender awards and notices (40 million contracts) coupled with machine learning to locate, extract, and structure only the relevant data. Our NLP allows us to search at a ‘lot’ level for only those contracts that align with our inquiry. This enables quick, statistically relevant analysis that is not anecdotal, biased, or survey based. It is also different than running queries on a generic LLM-based GPT that may introduce erroneous responses, or hallucinations, as they are not restricting their search to a particular dataset.

To illustrate this point further, consider that for any inquiry into any market that utilizes tenders for procurement we can quickly identify (1) the size of the public market by product type, (2) exactly which hospital is buying, in what amount, and from which manufacturer and distributor, (3) the market share for each manufacturer and distributor (visualizing the direct and indirect market), (4) historical trends analysis and contract renewal dates to prepare for upcoming bids. This information can better prepare an organization to:

• Quickly understand the company’s actual market position, and that of the competition.
• Get an unbiased view of the competitive landscape, visualizing buying patterns between hospitals and suppliers.
• Understand which suppliers are selling directly versus through distributors.
• Target specific hospitals based on spend analysis.
• Identify key influencers at those target hospitals that can expedite the sales process.
• Prepare cost/benefit analysis against the competition.
• Coordinate with the local sales team to focus sales and marketing efforts.

Conclusion

Leveraging advanced analytics for market intelligence is a powerful tool for medtech companies seeking to grow their market share. By providing rapid, comprehensive, and unbiased insights, it enhances decision-making and enables businesses to strategically navigate complex markets. If interested in learning more, the Vamstar team is scheduling meetings for the MedTech Forum 2025 in Lisbon from May 13-15.