Back
Case Studies

On-Sale Price Optimization — Live Event Demand AI

Mission:

Supercharge ticket revenue by adjusting event prices in real-time, based on how fast seats are selling.

Tagline:

🔥 Pricing that adapts as fast as fans buy.
🎯 AI-powered ticket pricing for the entertainment world.

The Challenge:

Live events don’t sell at a steady pace — demand spikes, stalls, and swings based on artist, genre, timing, competition, and hype. Event managers needed a smarter way to:
  • Spot slow-selling shows early
  • Decide when to boost marketing vs lower price
  • Capitalize on fast-selling shows with dynamic price increases
  • Run everything automatically (no manual spreadsheet panic)

How the Khares Analytics team helped:

  • Fully automated machine-learning pipeline to predict sell-through momentum
  • Real-time pricing signals based on “run-rate” (speed tickets are selling)
  • Event-level feature engineering:
• Artist & event metadata
• Date & time dynamics (seasonality, lead-time trends)
• Genre & sub-genre behavior patterns
• Ticket sell-through pace (% of inventory sold over time)
  • Exploratory demand analysis to understand why some shows crush it while others flop

The Outcome:

The system gives event teams a data-driven pricing autopilot, enabling them to:

✅ Automatically suggest price changes
✅ Spot under-performing shows early and push promos
✅ Avoid unnecessary discounting
✅ Boost profits on shows with high demand

Bottom line:

More sellouts. Fewer empty seats. Maximum revenue — powered by predictive intelligence, not guesswork.
Next Project
Event Slot Forecasting