Results / $3M+ in new annual revenue·Case study

AI Revenue Recovery Engine for a ~$200M Luxury RV Dealer

$200M Luxury RV Dealer

AI Revenue Recovery Engine for a ~$200M Luxury RV Dealer (Revenue & Growth)
What we did:
AI Engineering Business Process Design Data Engineering Full Stack Development Systems Integration Training & Change Management
Industry: Automotive

Business Situation

A luxury recreational-vehicle dealership in the $200M annual revenue range, selling high-consideration units on long research cycles, holding an 18,000-contact database and over 1,000 new leads a month.

The Challenge

An 18,000-contact database carried no predictive scoring, and 1,000+ monthly leads were qualified by hand, so customers ready to buy were indistinguishable from cold ones. Purchase windows closed unworked every month.

Why It Matters

Compose built the AI Revenue Recovery Engine: an ML lifecycle-scoring model ranking contacts by probability of buying now, NLP classification extracting intent from inbound lead text, an AI agent running personalized multi-channel outreach against the ranked list, and automated routing matching each prospect to a best-fit specialist.

What Compose Delivered

  • ML lifecycle scoring model ranking all 18,000 contacts by buy intent
  • NLP classification extracting intent signals from inbound lead text
  • AI agent running personalized multi-channel outreach at scale
  • Automated routing matching prospects to sales specialists by fit
  • Contact-database consolidation and enrichment pipeline
  • HubSpot CRM integration wiring lead scores into the sales workflow
  • Sales-team training and change management on the scored queue

Outcome

$3M+ in new annual revenue measured over 12 months on a ~$200M base, from a contact database that had never been scored.

The scoring model surfaced high-probability buyers that manual review had never flagged, and automated routing matched each one to a best-fit specialist, turning a dormant contact list into a ranked working queue.

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