Using AI to Increase Aftermarket Sales

Aftermarket sales should be one of the most predictable sources of revenue. The installed base already exists. Demand is already there. But in practice, most of that opportunity goes uncaptured.

Sales and field teams often don’t know which parts they can offer as replacements—especially when dealing with competitor equipment. The data exists across catalogs, systems, and documents, but it is fragmented, inconsistent, and difficult to use in real time. As a result, teams rely on manual lookup, tribal knowledge, or simply move on when they cannot confidently identify a match.

The outcome is consistent: missed revenue, slower response times, and underutilized product lines.

This webinar breaks down why aftermarket sales remain reactive instead of systematic—and how manufacturers and distributors are changing that.

Instead of relying on manual search, AI evaluates parts across multiple sources—internal catalogs, competitor data, and field inputs—to identify compatible replacements in real time. Known matches are surfaced instantly. Uncertain matches are refined continuously, improving accuracy over time.

The result is a system where every interaction becomes an opportunity to sell. Field teams can recommend parts with confidence. Sales teams can respond faster. And organizations can unlock revenue that was always there but never captured.

This session walks through how these systems operate in real-world environments, showing how companies are increasing aftermarket revenue without increasing complexity or headcount.