Today marks the successful delivery of a data-driven customer prioritization model developed for an emerging manufacturing technology provider and machine distributor. Specializing in 3D printing and hybrid additive manufacturing, the client needed a scalable solution to prioritize over 9,000 global prospects based on alignment with their advanced machinery and services.

Challenge

Faced with a vast and diverse list of global prospects, the key challenge was to determine which leads were most relevant and worth pursuing—without relying on weeks of manual research. Traditional CRM data alone offered limited insight into each organization's technical focus, funding status, or engagement with advanced manufacturing.

Approach

We built a custom NLP-powered targeting engine tailored to this challenge, combining the following components:

• Web Scraping & Content Ingestion: Public-facing websites of global prospects were crawled, collecting up to 30 internal pages per organization to extract relevant insights using Named Entity Recognition (NER)—including ORG (Organizations), PRODUCT (Technologies & Machines), GPE (Cities & Regions), NORP (Government/Military Groups), FAC (Labs & Facilities), and EVENT (Conferences & Expos).
• Natural Language Processing (NLP): Insight content was parsed and analyzed to identify indicators of:
• Technology Adoption
• Relevant Tools & Equipment
• Funding & Grants
• Industry Collaboration
• Keyword Scoring Logic: Carefully curated keyword sets across four categories were scored using fuzzy matching, phrase detection, and content density to reflect alignment and intent.
• Smart Filtering & Ranking: A custom algorithm filtered out low-signal targets, normalized scores, and ranked prospects based on weighted relevance.

Outcome

The final output was a prioritized and enriched lead list—ready for sales and marketing action. This enabled the client to:

• Save time: Reduce weeks of research and qualification work into a matter of hours.
• Focus outreach: Prioritize the top 10–20% of global prospects with the highest alignment to their offerings.
• Increase relevance: Personalize communications using keyword-derived context from each target’s web content.
• Improve alignment: Enable cross-functional collaboration between business development and marketing teams based on shared prospect intelligence.
• Adapt and reuse: Easily update the model for other product lines, regions, or emerging trends in advanced manufacturing.

Curious how NLP and AI-powered targeting can refine your go-to-market strategy?

Reach out to explore how DataInfer can help you unlock scalable, smart, and efficient lead prioritization.