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PRIX 

[preeh]
The single biggest lever in your
business is PRICE
Every potential customer has a
unique willingness to pay
Have you experimented to find
out the willingness to pay?
SOLUTION
PRIX has developed a
Real-time, Machine Learning

Platform
You have full control over limits,
levels, timings and coverage
You have a super-computer working
24/7 to find the right price
CASE-STUDY - SIMULATION 1
CASE-STUDY - SIMULATION 1
# Viewed # Sold € Revenue € Avg. Price
Fixed Price 468 317 63,400 200
Tit-for-tat 468 354 69,363 196
Q(λ) -learning 468 ? ? ?
10% improvement in revenue 

1% drop in average price
TEAM
BOARD OF ADVISORS
• Jens Munch

3 years Chief Strategy Officer, iZettle

5 years of Strategic Partnerships, Google

• Galina Shubina

10 years Engineering, Google

MSc Computer Science, Brown University
BOARD OF ADVISORS
• Jason Pinto

LP at Amadeus Capital

10 years in Venture Capital

PhD Physics, Cambridge/MIT/Stanford

• Eric D. Collins

Chief Revenue Officer, Swiftkey

JD Harvard Law School
BOARD OF ADVISORS
• Rupal Rana

Lecturer in Management Science 

PhD, Warwick University

MSc, Nottingham University

• Mitra John Groff

Head of Pricing and Product, National Express

15 years in yield management
NEXT STEPS
THE PROOF IS IN THE PUDDING
Let’s create an experiment to demonstrate increased revenues:
• We set aside 10% of your potential customers
• Fix a price-floor close to your current price
• And let PRIX optimise for revenue!
Worst case scenario revenue improvements are small.
Thanks
contact@prix.ai

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Prix.ai sales deck-f2f

  • 2. The single biggest lever in your business is PRICE
  • 3. Every potential customer has a unique willingness to pay
  • 4. Have you experimented to find out the willingness to pay?
  • 6. PRIX has developed a Real-time, Machine Learning
 Platform
  • 7. You have full control over limits, levels, timings and coverage
  • 8. You have a super-computer working 24/7 to find the right price
  • 10. CASE-STUDY - SIMULATION 1 # Viewed # Sold € Revenue € Avg. Price Fixed Price 468 317 63,400 200 Tit-for-tat 468 354 69,363 196 Q(λ) -learning 468 ? ? ?
  • 11. 10% improvement in revenue 
 1% drop in average price
  • 12. TEAM
  • 13. BOARD OF ADVISORS • Jens Munch
 3 years Chief Strategy Officer, iZettle
 5 years of Strategic Partnerships, Google
 • Galina Shubina
 10 years Engineering, Google
 MSc Computer Science, Brown University
  • 14. BOARD OF ADVISORS • Jason Pinto
 LP at Amadeus Capital
 10 years in Venture Capital
 PhD Physics, Cambridge/MIT/Stanford
 • Eric D. Collins
 Chief Revenue Officer, Swiftkey
 JD Harvard Law School
  • 15. BOARD OF ADVISORS • Rupal Rana
 Lecturer in Management Science 
 PhD, Warwick University
 MSc, Nottingham University
 • Mitra John Groff
 Head of Pricing and Product, National Express
 15 years in yield management
  • 17. THE PROOF IS IN THE PUDDING Let’s create an experiment to demonstrate increased revenues: • We set aside 10% of your potential customers • Fix a price-floor close to your current price • And let PRIX optimise for revenue! Worst case scenario revenue improvements are small.