The “hidden champion” dilemma Manufacturers of technical components (B and C parts such as sensors, seals, or connection technology) often face a paradox: their products are so technologically versatile that they could theoretically be used in hundreds of industries. In practice, however, sales teams usually only know the top customers in their core market. The “long tail” – thousands of niche markets with specific problems – remains a blue ocean because manual research is simply uneconomical here.

Generative AI as a “qualification engine” The “automated market discovery” approach puts intelligent analysis ahead of marketing. Instead of distributing the ABM budget indiscriminately, AI abstracts the technical DNA of your product and searches worldwide for matching problems.

The key question is not: “Who is buying from us today?” But rather: “Which industry has a technical problem that our product solves – without knowing it?”

A generic example: A manufacturer of sensor technology is strong in automotive engineering.

1. Abstraction: The AI analyzes the product data and extracts the functional pattern: “Precise pressure measurement in highly corrosive liquids at extreme temperatures.”

2. Transfer: The system scans databases from other industries for this requirement profile.

3. Match: The AI identifies the “geothermal energy industry” or “hydrogen production” as high-potential targets, as these are precisely the areas where such resistance is required.

The result: Data-driven ABM lists The system does not simply provide addresses, but a strategically validated “hit list.” Each target account is pre-qualified by:

This enables marketing and sales teams to focus their ABM resources (“sniper approach”) only on those targets where the probability of winning is highest. It is a shift from cold calling to solution-oriented consulting.