REVENUE MANAGEMENT STRATEGIES AND ONLINE DISTRIBUTION

Welcome

Hoşgeldiniz

AÇIKLAMA Hotel Linkage Summit 19 Şubat 2016 Tarihinde Raffles Hotel

Istanbulda “Revenue Management Stratejileri ve Online Satış Teknolojileri” başlığı altında Hotel Linkage tarafından düzenlenmiştir. Bir sonraki sayfada göreceğiniz 12 konuşmacının hazırladığı sunumlardan oluşan bu döküman yaklaşık 153 sayfadır.

Bu Sunum Revenue Management Konusunda Şimdiye Kadar

Hazırlanmış En Kapsamlı Sunumdur. Bu Sunumu Şirket İçi Eğitimlerinizde, Liselerde ve Üniversitelerde kullanabilirsiniz. Bu Sunumu Kullanırken Sunum Sahiplerine Atıf Yapmayı Unutmayınız.

Hotel Linkage Summit 2016 ® | Istanbul

KONUSMACILAR


Mehmet Alpatlı– Istanbul Şehir Üniversitesi

Hotel Linkage & Numbers



Hotel Linkage Istanbul Şehir Üniversitesi Bünyesinde yer alan Incuba.city ve EIF’nin 35 milyon euroluk fonuna katılan ŞEHİR Teknoloji Transfer Ofisinin girişimlerinden biridir. Hotel Linkage Otellere 360° online kanal yönetimi ve online kanal teknolojileri konusunda çözümler üreterek otellerin internet üzerinden yaptıkları satışları arttıranbir teknoloji danışmanlık firmasıdır.


HOTEL LINKAGE’NIN ÜRUNLERI






Erhan Kaya – Hotel Linkage Data & Education

DATA VE EĞİTİM



17. Y.Y ANTONIE VAN LEEUWENHOEK


DATA KARAR


KOKU ÖLÇER


DATA YOL GÖSTERİR


RM = SAHTEKARLIK

RM = KAYNAK YOK


Hotel Linkage Summit 2016 ® | Istanbul Hotel Linkage Summit 2016 ® | Istanbul

Teşekkürler...


Nihan Demir – Raffles Istanbul

Basics of Revenue Management

WHAT IS REVENUE MANAGEMENT?


Revenue Management is the application of disciplined analytics that predict consumer behavior at the micro-market level and optimize product availability and price to maximize revenue growth.

TRADER Joe’s Butcher Shop



•  High fixed costs and low variable costs.

•  A fixed amount of resources are available for sale at any given time

•  Resources are perishable.

•  Different customers are willing to pay a different price for the same resources.

•  There is some ability to predict future demand for resources.

WHY Joe NEEDS REVENUE MANAGEMENT?


•  Tracking the data & KPI's ü  Units sold per each day,

ü  Products sold by the day of the week,

ü  Competitive intelligence,

ü  Prices in the market.

How he Will set The Price?


•  Forecasting ü  Past data,

ü  Market conditions,

ü  Segmentation,

ü  Weekday & Weekend statistics,

ü  Seasonality,

ü  Special events,

HOW HE WILL SET THE PRICE?


•  Pricing: ü  Optimum Price= Equilibrium,

ü  Classify your inventory,

ü  Prices of the competition,

ü  Weekday - weekend rates,

ü  Seasonality,

ü  Discounts,



•  Inventory Management ü  Allocation of resources, ü  Optimize revenue when the demand is high,

ü  Facilitate sales when the demand is low,



HOW HE WILL EVALUATE THE RESULTS?

ü  Total Revenue Total units sold

ü  Total Revenue Total units available

The real performance of every unit


REVPAR AS A KEY PERFORMANCE INDICATOR •  RevPAR is a total guest room revenue per available room per day; ü  Average Daily Rate (ADR)= Hotel’s total room revenue divided by the number

of sold rooms, ü  Occupancy = Number of sold rooms divided by the available hotel rooms

OCCUPANCY = REVPAR xADR


REVPAR IS A KEY PERFORMANCE INDICATOR

Occ. Rooms:100 ADR : $56 BAR :$69 REV :$5800 OCC :100% RevPAR:$58

Occ Rooms: 88 ADR: $139 BAR: $150 REV: $12200 OCC: 88% REVPAR: $122

Occ. Rooms: 39 ADR: $225 BAR: $250 REV:$8757 OCC:39% REVPAR : $88


REVPAR IS A KEY PERFORMANCE INDICATOR

ü  It is the combination of the ADR and Occupancy,

ü  It allows comparisons with other hotels,

ü  Hoteliers are able to understand the exact performance of each room,


THANK YOU…

Yonca Erdoğ – Çırağan Palace Kempinski

Forecasting Demand


Forecast demand

Forecast demand


Doluluk oranı ?

Oda fiyatı ?

Gelir/total gelir ?

Forecast demand


GÜNLÜK/ANLIK

HAFTALIK

AYLIK

Forecast demand – Günlük veriler

Forecast demand – haftalık veriler

Forecast demand – Aylık veriler

Forecast demand- gelir artırıcı olanaklar


Forecast Demand- yeni etkenler

Forecast Demand- PACE


Booking Pace: Start tracking and monitoring your booking pace for each segment. Booking pace is a key element of Revenue Management. It measures how many bookings you have on the books at any given time for a future date. A matrix of stay dates by booking dates provides the booking pace or booking curve as it is sometimes called. The idea is to begin measuring it as soon as possible so you can build up some history on how fast your rooms filled up for each day last year. Then, as this year unfurls you can easily determine if demand is stronger or weaker based on whether the booking pace is a head of or behind the same day last year. This enables you to determine if you should be in a promotional mode or an allocation mode in your sales strategy.

FORECAST DEMAND-PACE PATTERN

5 years ago :

Pace pattern : last year same time BOB the books and last year actual

Today :

3 days before arrival date 3 days after arrival date

1 week before arrival date 1 week after arrival date

1 month before arrival date 1 month after arrival date

Same time last year and actual

Forecast demand- pace /rate level

Forecast demand/pace by segment

On

tAN

e B

ook

Estim

. Pic

k-up

FORECAST 2016 February ON THE

BOOK ESTIMATED pick up

Rm Nts ADR Revenue Rm Nts

ADR Room Revenue Rm Nts ADR Revenue

CONTRACTED INDIVIDUAL CCR - Contracted Corporate - Local 150 134,63 20.194 630 426,90 268.950 780 370,70 289.144 CTA - Consortia 40 162,88 6.515 45 515,00 23.175 85 349,29 29.690 CRG - Contracted Corporate - Global 75 6,45 484 150 200,00 30.000 225 135,48 30.484 GVT - Government 0,00 0 0 0,00 0 LOG - Long Stay/ Residences 0,00 0 0 0,00 0 STL - Special Discounted Rates 0,00 5 110,00 550 5 110,00 550 WHD - Whole Sale - Dynamic 0,00 0 0 0,00 0 WHP - Wholesale - Static 350 140,04 49.013 735 450,00 330.750 1.085 350,01 379.763 RST - Residence 0 0,00 0 0 0,00 0 TOTAL CONTRACTED IND. 615 123,91 76.206 1.565 417,52 653.425 2.180 334,69 729.631

GROUP CEX - Convention 0,00 0 0 0,00 0 MTG - Meetings 1.150 318,26 366.000 250 450,00 112.500 1.400 341,79 478.500 INC - Incentive Groups 0,00 0 0 0,00 0 SMERF - Social, Military, Education, Rel 200 378,75 75.750 50 405,00 20.250 250 384,00 96.000 GRP - Corp. Group w/o meeting 252 527,63 132.963 120 475,00 57.000 372 510,65 189.963 ADH - Ad hoc Groups 0,00 0 0 0,00 0 TOP - Tours 0,00 0 0 0,00 0

FORECAST DEMAND – PACE PATTERN

FORECAST DEMAND- TEAM SPIRIT

FORECAST DEMAND- start


Zak Ali (F-HOSPA,CRME) – Director Global Revenue Development

Market Segmentation and Hotel Competitive Analysis

RETHINKING SEGMENTATION


What factors are influencing our

Market conditions?

What is the level of customer

price sensitivity per segment?

What type of Business mix do

you currently have in the Hotel and at

what level?

Do you have sales strategies per segment in

place?

Can you tell the behavior of the different

customers? (Lead time, contribution, LOS and booking conditions)

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WHAT IS MARKET SEGMENTATION


•  Targeted Sales and Marketing Activities

•  Increase Guest Retention Levels

•  Targeted Pricing

•  Increased Market Share of the Desired Segments

Drivers for Segmentation Incorrect Segmentation

Segmentation involves subdividing markets, channels or customers into groups with different needs to understand the growth potential.

•  Inaccurate Forecasting

•  Ineffective Pricing Strategies

•  Incorrect Sales and Marketing Activities

•  Strategy Impact

55

MARKET SEGMENTATION - DEFINITION


Measurability

•  Can you measure the visits of a certain segment to your city/area? e.g. Corporate, Is your market segment measurable?

Actionability

•  Are your product offering and price interesting enough for that segment to buy from you?

•  Can they actually book a room at your hotel?

Accessibility

•  Can you reach that segment? Distribution Platform

Substantiation

•  Is this segment large enough to be viable? Cost’s, Price willingness, Profitability, level of demand.

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KEY CONSIDERATION OF AN OPTIMAL SEGMENTATION


Customer Behavior / Lifestyle

57

Price & Buying Behavior

Product Ancillary Spend Loyalty

Sensitivity Lead Time Conditions

KEY CONSIDERATION OF AN OPTIMAL SEGMENTATION


Contribution

58

Channel & Cost

Product Ancillary Spend Loyalty

Cost Profit/Chnl Positioning

SEGMENTATION OPTIMIZATION CYCLE

Segmentation Optimization

Cycle


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Analyze – Mix, Performance, Profitability Goals – Where and What, Distribution, People Execute – Strategy and Evaluate

Segmentation – Constantly evolving

MARKET SEGMENTATION CONCLUSION


Segment Transient Direct, Transient OTA, Corporate, Group, Wholesale, MICE

Cost of Acquisition & Cost of Distribution

Net Contribution Net RevPAR, GOP

Optimization Pricing, Inventory, Channel Mgt, Conversion

Planning - Strategy Contribution, Profit Mix

Generation Advertising, OTA optimization, Sales Opportunities

60

DETERMINING THE COMPETITIVE SET

”A competitive set is defined as a group of hotels by which a property can compare itself to the group’s

aggregate performance. Before a hotel can construct a strategic plan it is

important that they understand the market in which they operate in.

If this critical first step is not completed, then the foundation upon which the future strategy is built may be

fundamentally unsound.”

61


BENCHMARKING & COMPETITOR ANALYSIS

Benchmarking should give us information on:

•  Prices

•  Room Types

•  Products

•  Packages

•  Channel of Distribution

•  Occupation

•  Serviced offered

YoY

Cha

nge

Manager A

0%

10%

20%

-20%

-10%

7%

15%

A’s Competitor

YoY

Cha

nge

Manager A

0%

10%

20%

-20%

-10% -3%

-10%

A’s Competitor

62


COMPLETING A SWOT ANALYSIS

SWOT is a strategic planning method used to evaluate the:

SWOT of a business.

Stage 1 – SWOT

Stage 2 - Evaluation

63


COMPLETING A VALUE ASSESSMENT – STEP 1 A Value Assessment is a very useful tool, allowing the ranking of the comparative value of the hotel.

64

Location Quality of Service Food and Beverage Quality Breakfast offering Internet Price & Speed Leisure Facilities Average Transient Rate Guest Room Types Age and Design

Loyalty Program Complimentary Services Brand Cleanliness Reviews Ranking on Review Sites and Average ranking on OTA sites.

1st Step - determine the relative quality of each of the selected competitors

Factors to Compare


COMPLETING A VALUE ASSESSMENT

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2nd Step - Once rating criteria have been selected, each of the competitors will be rated against the hotel.

COMPLETING A VALUE ASSESSMENT - MATRIX

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3rd Step - Once the product offer is rated, each of the comparative values must be plotted on a matrix against the price offered


TO ASSESS COMPETITON - ANALYZE

•  How do my occupancy rate compare to competitors? •  How do my average rates compare to my competitors? •  How is my week vs. weekend business? •  Do they use yield? •  Predict future moves •  Spot opportunities and be alerted to changes in

market conditions

67


BENEFITS OF BENCHMARKING

•  Identify and maximize revenue opportunities •  Make informed business decisions – based on facts •  Assist with Budgeting process •  Plan marketing and sales activities •  Fine-tune your pricing strategies •  Analyze competitive markets specific to your hotel •  Spot trends and be alerted to changes in market conditions •  Set realistic, challenging goals •  Establish realistic action plans

68


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Theodoros Katsimbras BookOnlineNow

Pricing Strategy

& Increase Direct Bookings



WHY HOTELIERS DREAM BECOMES A REALITY?


HOW TO DEFINE YOUR ROOM PRICE


Yield & Revenue Management

ü  Forecast Demand With the right DATA ,you can get reasonably close REMEMBER: Organizing & interpreting historical data is 90% of the job ü  Optimize Demand In order to have more available rooms thus yielding to a better turnover ü  Control Demand Demand can be volatile and can vary depending seasonality or country ü Monitor Demand Increase annual turnover by acquiring a better engagement with the appropriate target

PARALLEL WORLDS


SALES STRATEGY vs MARKETING STRATEGY

ü  PRODUCT DEFINITION

ü  COMPETITIVE BENCHMARKING

ü  DESTINATION/ INDIVIDUAL DEMAND ANALYSIS & FORECASTING

ü  DISTRIBUTION MANAGMENT

Modern Sales &

Marketing process

CLEVER PRICING STRATEGIES


Ø Price match your competition Ø Penetrate the market Ø Surround your middle market Ø Psychological Pricing Ø Differential Threshold Ø Avoid Pricing Similarity

KING OR JUST A MAN


When a hotel actually competes its own brand

WAYS YOUR IBE IS PUSHING PEOPLE OUT


ü  Rates are cheaper on third party sites and OTAs ü  You stopped selling before they’re sold ü  No Special discount - offer special discounts, put them on your specials

page with automatic embedded links carried to your booking environment

ü  No inspiration - your website experience must go above and beyond to inspire and excite visitors (satisfy both two types of thought: rational and emotional)

ü  It’s too frustrating to make a reservation - your booking engine must be a simple process

RATING STRATEGY COMPARED TO OTAS


ü Have similar prices with OTAs on standard rates and give discounts with special rate plans

ü Give lower price for specific room types for different channels

ü Have different rate plan policies (Deposit, Cancellation days)

ü Create different products for a specific period ü Make offers with Promo Codes

HOTEL WEBPAGE + BOOKING ENGINE


ü Share Posts About Great Deals Link your special offers of your booking engine to your website. ü  Use Design Strategies to Persuade Visitors First off, make it as easy as possible to book ü Give Deals to a Select Group of Customers ü Offer Money-Saving Packages ü Do not ignore beginners

GUEST LOYALTY


ü  Personalized communication Automated personalized emails are sent to guests confirming reservations, pre-arrival reminders, and post-stay thank you email ü  Memberships – Loyalty system with credits Categorize customers to special customer groups (VIP, Gold etc) and create special rates and promotional coupons per group ü  Discount codes: Membership discounts for people who

have stayed at the hotel before, or if you sign up through the website.


CHECK EFFECTIVENESS OF EACH SOURCE


Track Guest Requests and Booking Sources ü  Bookonlinenow tracks and monitors guest

searches (start date, end date, number of adults) ü  Track and monitor the source of each request or

booking ü  Bookonlinenow monitors the effectiveness of each

booking source and understand how each source contributes to your traffic and bookings.

EMAIL RETARGETING


Bring back visitors who have abandoned the reservation process

ü  If guests exit the booking engine without completing the reservation process, a pop up is served and ask them for their email address.

ü  Reservation Email Retargeting sends automated emails to any user who starts but does not complete the Reservation

ü  Email retargeting dramatically increases the likelihood that a website visitor will complete their abandoned reservation. The email will be delivered at a pre-selected time frame

GEO-PRICING


CASE STUDY I


( Hotel of 223 Rooms near to airport – Year 2015) Bookonlinenow represents 33% of the hotel total revenue (Direct sales 33% of total sales) Bookonlinenow represents 56% of the hotel revenue from online bookings Bookonlinenow maximum conversion rate: 9.32%, average conversion rate: 7.04%

CASE STUDY II


(Hotel Chain Of 9 Hotels – Year 2015) Bookonlinenow represents 29% of the hotel chain total revenue Bookonlinenow represents 68% of the hotel revenue from online bookings


“The Distance Between

Your Dreams And Reality Is Called ACTION “



14:35 – 15:00

Uygar Koçaş-The Marmara Taksim

Gelir Yönetimi Yönetimi







Beklentiler

Rezervasyon bölümünün standartları



Bir günüm ve gelir yönetimi








Nadir Kadakal – Dedeman Bostancı İstanbul

Misafir Memnuniyeti ve Gelirler



ACENTELER

ŞİRKETLER

ONLINE KANALLAR F&B OUTLETLER


‘‘ Otellerime gelenlerin müşteri değil misafir olduklarını her zaman herkese

telkin etmişimdir’’

Mehmet Kemal DEDEMAN


Misafir Memnuniyeti =

Beklentiler + Algılanan Değer


Misafir memnuniyeti evrensel bir değer değildir.

Her misafir aynı otelden aynı memnuniyeti elde edemez.


Misafirlerin beklentileri ürün yada hizmet performansını aşarsa memnuniyetsizlik,

beklentileri karşılandığında ise memnuniyet ortaya çıkar.


Misafirler memnun oldukları bir ürün yada hizmeti rekabetçi bir fiyatla değiştirmezler.




Teşekkürler...


Sascha Hausmann – HOWZAT PARTNERS

Latest Trends in Online Distribution Technologies

TECHNOLOGY PIT – ARE YOU PREPARED?


q  Define your needs q  Technology serves consumer innovation q  Technology is subordinated q  Look for product consolidators

CONSUMER TODAY -> ME FIRST! (CAMPBELL MITHUN STUDY)


KNOW THIS GUY?


PEER TO PEER

RAGING AGAINST THE „MACHINES“


BRAND

WHAT‘S THERE TO DO? A LOT UNFORTUNATELY


q  IMPROVE OUR WEBSITES q  IMPROVE THE CUSTOMER EXPERIENCE AND JOURNEY q  PRODUCT, PRODUCT, PRODUCT q  WORK WITH THIRD PARTY DISTRIBUTORS SMARTLY q  FIX MOBILE q  DEAL WITH THE GDS – THE BOYS AIN‘T DEAD q  LISTEN AND LEARN

COVER THE STUFF… A LOT AGAIN…


BACK-END HOTEL WEBSITE THIRD PARTIES

SHOW ME YOUR GOOD! SHOW ME THEIR BAD!

q  „I AM HERE, DON‘T MAKE ME LEAVE“ q  PRICE PARITY – A MUST FOR THE WEBSITE q  „YOUR ARE LEAVING – WHY?“ q  ARE YOU MOBILE FOR ME?

TRIP TEASE / LIVE RATE


CUSTOMER JOURNEYS – THE DIRECT INDIRECTS


q  Recommended from a friend or peer q  Fun to be engaged q  Rewards & Benefits

EXAMPLE: FLIP.TO

DIRECT BUILDS BRAND – BUT COSTS MONEY

q  SEO q  GOOGLE & CO q  METASEARCH (*) q  QUESTIONS – POTENTIAL OR MONEYSUCKERS?

(*) e.g. tripadvisor, trivago, hotelscombined, Google Hotelfinder


MAKE ME SAFE! A NEW OTA…

q  CONSUMER PROTECTION q  SERVES AS REVENUE SOURCE q  HAVE A GUEST AND CASH


ADDITIONAL BUSINESS


q  You are 100% occupied? Think twice... q  You think loyalty is out? Hmmm….

ADDITIONAL BUSINESS


q  Meetings not interesting… well …

BE AWARE – THE BAD BOYS!


q  Some never learn… CONSUMERS LOVE IT!

JUST RAISED €1,000,000 VIA CROWD FUNDING FROM OVER 1,000 CONSUMERS!

CRAZY IS STILL IN!

q  Consumers love it! Share, explore and be inspired


THANK YOU !


Cenk Demiroglu – Istanbul Bilgi University

Revenue Management Education

RM Educatıon: The Content


Ivanov, Stanislav (2014). Hotel Revenue Management: From Theory to Practice. Varna: Zangador, p. 12

Rm Usage at Hotels ın Turkey

105 Hotels Investigated

•  Mostly common at high category, high bed capacity, chain affiliated, urban and seaside hotels

•  No Revenue Manager – usually carried out by GM, FOM, MM

•  Top Tools and Techniques: Price Discrimination and Room Availability Guarantee

•  Most Neglected Tools and Techniques: Overcontracting and Overbooking

•  Availability of and WTP for RM software: very low

•  Top Distribution Channels: OTAs, hotel’s website, tour operators and travel agents

•  Top Indicators: Occupancy, ADR, RevPAR

•  Forecasting: «Historical» rather than Statistical

Ivanov, Stanislav Hristov and Ayas, Çağakan, Investigation of the Revenue Management Practices of Accommodation Establishments in Turkey: An Exploratory Study (December 17, 2015). Paper presented at the First REMAPS Revenue Management and Pricing in Services conference, 17-18 December 2015, Paris


Rm Educatıon at Schools ın Turkey

Offerings at Top 10 Bachelor Programs*

•  Atılım University

•  Bilkent University

•  Boğaziçi University

•  Düzce University

•  Erciyes University

•  Istanbul University

•  Istanbul Bilgi University

•  Istanbul Commerce University

•  Okan University

•  Yeditepe University

RM covered under

o  Few Specific Core Courses

o  Few Specific Electives

o  Rooms Division Management

o  Automation

o  Airline Management

o  Forthcoming RM courses

*Engin Bayraktaroğlu, Akademik Turizm Bülteni, Yıl: 16, Sayı: 9, Eylül 2015


ApplıED Educatıon: Table Mıx Optımızatıon

Cornell CHR’s state-of-the-art Hospitality Tools: RTMO & RTS •  Group Size and Share •  Average Duration •  Average Check •  Table Size versus Space Ø  Max. groups/hour Ø  VPASH (max. revenue per available space-hour) Ø  Best table mix

Thompson, G. (2012). Restaurant Table Simulator, version 2012. Cornell Hospitality Tools, 3(3), 6-11.

Thompson, G. M. (2005). Tablemix Optimizer. Cornell Hospitality Reports.


Thank You!


Burkay Bozkurt – HOTECH

PMS - RMS İlişkisi & Veri Kalitesi

HOTECH BİLİŞİM


Hotech Bilişim; efektif Big Data analitiği ve yönetiminden yola çıkarak, konaklama

sektörüne yazılım, danışmanlık ve inovatif teknolojik çözümler sunan bir ekosistemdir.

HOTECH BİLİŞİM

YAZILIM DANIŞMANLIK

TEKNOLOJİK ÇÖZÜMLER

PMS

•  Esneklik•  Cloudveyaon-Premise•  Kullanımkolaylığı•  OnlineGuest•  Entegrasyon

RMS Döngüsü

BIG DATA

Events Weather

Competitor Pricing etc...

Dynamic Pricing 365 daily horizon

Revenue Management

Price Optimization

GDS OTA

IBE

Channel Manager

PMS

Optimizasyon

Optimizasyon

Veri Kalitesi

Veri Kalitesi için Anahtar Faktörler

Kaliteli veri bileşenleri •  Completeness (Bütünlük)

•  Kayıp ya da kullanılamayan veri var mı? •  Conformity (Uygunluk)

•  Formata uymayan veri var mı? •  Consistency (Tutarlılık)

•  Çelişki yaratacak veri var mı? •  Accuracy (Doğruluk)

•  Hangi veriler yanlış ya da eski? •  Duplicates (Tekillik)

•  Hangi veri değerleri veya özellikleri mükerrer? •  Integrity (Tamlık)

•  Hangi veriler kayıp ya da herhangi bir dayanağı yok.

Veri Optimizasyonu Veri Temizleme (Veri Standartlaştırma, Veri Ayrıştırma)

Veri temizleme terimi, genel olarak veritabanındaki yanlış ve kusurlu verileri tarayıp, ayırt edip düzeltmeyi ifade eder.

Veri Optimizasyonu Veri Birleştirme!

Veri birleştirme, farklı birden çok kaynaktan verilerin tek veritabanında birleştirilmesidir.

Birleştirme esnasında gereksiz ve tekrar eden veriler elenir.

Veri Optimizasyonu Veri Zenginleştirme

İç veya dış veri kaynağından elde edilen veriler doğrultusunda, mevcut veriye analitik değerlendirme sonucu elde edilebilecek yeni veriler eklemektir.

Veri Optimizasyonu Veri Madenciliği ve Raporlama

Veri madenciliği büyük veri yığınları içerisinden gelecek ile ilgili tahminde bulunabilmemizi sağlayabilecek bağıntıların bilgisayar programı kullanarak aranmasıdır.


16:30 – 17:00

REVENUE MANAGEMENT STRATEGIES AND ONLINE DISTRIBUTION

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