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Eye For Travel, Amsterdam, November 24 2014Eye For Travel, Amsterdam, November 24 2014
Source: © INMAGINE.com
WE ARE EXERIENCING A PIVOTAL
MOMENT IN THE HISTORY OF DATA…
2
80%
Of all data were
created in the
last 18 months
10X
by 2020
UPSELL UPSELL
ROUND THE CLOCK RM ACTIVITY
… BUT A NORMAL HUMAN BRAIN
CANNOT AFFORD SO BIG DATA
3
BIG DATA IS ALREADY AT THE CORE
OF RM JOB AND DECISIONS
BIG DATA
Forecast
Algorithms
+1M 3.5K
reports/year users/month
Reporting
Pricing
…
« If you have just a little bit of the right information
a couple of seconds or minutes in advance, it’s
more valuable than all of the information in the
world six months after the fact.” Vivek Ranadive
THE NEW ERA OF FAST DATA,
‘‘the 2-second advantage’’
AN EXAMPLE OF BIG DATA
Dynamic pricing solution for ibis
HOW WE DO IT ?
We look for a fine understanding of clients and hotel sensitivity
Price sensitivity: client & calendar Competitive environment & place
capacity
Psychological and min / max prices
(depending on hotel cost structure)
Lead time & booking curve impacts
SMART
Pricing
per hotel
What is the right price every day (high & low season)
for each type of client (business & leisure)?
How do prices evolve depending on competition
intensity?
How does price sensitivity evolve along booking
curve and lead time?
What are the psychological prices (min and max) for
each hotel?
PRICE SENSITIVITY
7
0.5
1.2
2.0
We find a strong relationship between the occupancy rate and the price index.
The hotel strategy has to be based on the understanding of this relationship
Low elasticity
High elasticity
Synthesizewithavaluescale
SEASON
High Season
Low Season +
-
DAY
Monday
Friday & Sunday
Tuesday,
Wednesday,
Thursday & Saturday
+
-
LEAD TIME
Early
booking
Last minute
booking
+
-
COMPETITIVE INTENSITY &
ENVIRONMENT
High
Low
+
-
HIGH ELASTICITY:
“I RAISE MY PRICES BY 10%,
I DECREASE MY VOLUME BY 20%,
SMART PRICING IS GOING TO
RECOMMEND A « VOLUME
STRATEGY » WITH A PRICE DROP
LOW ELASTICITY:
“I RAISE MY PRICES BY 10%,
I DECREASE MY VOLUME BY 5%,
SMART PRICING IS GOING TO
RECOMMEND A « MARGIN
STRATEGY » WITH A PRICE
INCREASE.
AN EXAMPLE OF BIG DATA
Accor Dynamic pricing solution
SHIFTING TO FAST DATA NOW
All in one solution, decision driven data
BENEFITS
ALL INCLUSIVE TOOL
OUTPERFORMING OTHER HOTELS BY 5% IN REVPAR,
1 REVENUE ANALYST MANAGING UP TO 25 HOTELS
offers an “all inclusive” tool enabling hotels to monitor
all Pricing related matters in a powerful, efficient & user
friendly environment.
PICK UP Follow your hotel
pickup for the last 21 days
Calculate & finalize
price grid & strategy
RATE SHOPPER
Supervise the
competitors prices
TARSiPMS
Daily Pricing Monitoring
through a fully
automated & integrated
INTERFACE
Access reliable
and aggregated
REPORTS
SUPPORT Register and
follow any bug online
FAST DATA, WHAT’S NEXT ?
CUSTOMER CENTRIC REVENUE MANAGEMENT
2.5TIMES HIGHER
A customer value
LOYAL
CUSTOMERS
3TIMES HIGHER
vs traditional approach
Click & conversion rate
CUSTOMIZED
OFFERS BY PROFILE
8
Data scientist :
new profile in RM,
BI, CRM, web
FAST DATA: What is going to change for RM
and Analytics ?
Customer centric RM
optimization
vs. transaction
Integration
All in one solutions
Real-time data
11
agnes.roquefort@accor.com
THANK YOU

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Agnes Roquefort, SVP Revenue Manager Accor

  • 1. Eye For Travel, Amsterdam, November 24 2014Eye For Travel, Amsterdam, November 24 2014 Source: © INMAGINE.com
  • 2. WE ARE EXERIENCING A PIVOTAL MOMENT IN THE HISTORY OF DATA… 2 80% Of all data were created in the last 18 months 10X by 2020
  • 3. UPSELL UPSELL ROUND THE CLOCK RM ACTIVITY … BUT A NORMAL HUMAN BRAIN CANNOT AFFORD SO BIG DATA 3
  • 4. BIG DATA IS ALREADY AT THE CORE OF RM JOB AND DECISIONS BIG DATA Forecast Algorithms +1M 3.5K reports/year users/month Reporting Pricing …
  • 5. « If you have just a little bit of the right information a couple of seconds or minutes in advance, it’s more valuable than all of the information in the world six months after the fact.” Vivek Ranadive THE NEW ERA OF FAST DATA, ‘‘the 2-second advantage’’
  • 6. AN EXAMPLE OF BIG DATA Dynamic pricing solution for ibis HOW WE DO IT ? We look for a fine understanding of clients and hotel sensitivity Price sensitivity: client & calendar Competitive environment & place capacity Psychological and min / max prices (depending on hotel cost structure) Lead time & booking curve impacts SMART Pricing per hotel What is the right price every day (high & low season) for each type of client (business & leisure)? How do prices evolve depending on competition intensity? How does price sensitivity evolve along booking curve and lead time? What are the psychological prices (min and max) for each hotel?
  • 7. PRICE SENSITIVITY 7 0.5 1.2 2.0 We find a strong relationship between the occupancy rate and the price index. The hotel strategy has to be based on the understanding of this relationship Low elasticity High elasticity Synthesizewithavaluescale SEASON High Season Low Season + - DAY Monday Friday & Sunday Tuesday, Wednesday, Thursday & Saturday + - LEAD TIME Early booking Last minute booking + - COMPETITIVE INTENSITY & ENVIRONMENT High Low + - HIGH ELASTICITY: “I RAISE MY PRICES BY 10%, I DECREASE MY VOLUME BY 20%, SMART PRICING IS GOING TO RECOMMEND A « VOLUME STRATEGY » WITH A PRICE DROP LOW ELASTICITY: “I RAISE MY PRICES BY 10%, I DECREASE MY VOLUME BY 5%, SMART PRICING IS GOING TO RECOMMEND A « MARGIN STRATEGY » WITH A PRICE INCREASE. AN EXAMPLE OF BIG DATA Accor Dynamic pricing solution
  • 8. SHIFTING TO FAST DATA NOW All in one solution, decision driven data BENEFITS ALL INCLUSIVE TOOL OUTPERFORMING OTHER HOTELS BY 5% IN REVPAR, 1 REVENUE ANALYST MANAGING UP TO 25 HOTELS offers an “all inclusive” tool enabling hotels to monitor all Pricing related matters in a powerful, efficient & user friendly environment. PICK UP Follow your hotel pickup for the last 21 days Calculate & finalize price grid & strategy RATE SHOPPER Supervise the competitors prices TARSiPMS Daily Pricing Monitoring through a fully automated & integrated INTERFACE Access reliable and aggregated REPORTS SUPPORT Register and follow any bug online
  • 9. FAST DATA, WHAT’S NEXT ? CUSTOMER CENTRIC REVENUE MANAGEMENT 2.5TIMES HIGHER A customer value LOYAL CUSTOMERS 3TIMES HIGHER vs traditional approach Click & conversion rate CUSTOMIZED OFFERS BY PROFILE 8
  • 10. Data scientist : new profile in RM, BI, CRM, web FAST DATA: What is going to change for RM and Analytics ? Customer centric RM optimization vs. transaction Integration All in one solutions Real-time data