Using Customer Data for Revenue Maximization

Size: px

Start display at page:

Download "Using Customer Data for Revenue Maximization"

Felicia Robertson
6 years ago
Views:

1 Using Customer Data for Revenue Maximization Travel Distribution Summit May 27-28, 2014 Andrew Lau Group Director of Revenue Management and Distribution

2 Budget

3 Revenue Management Revenue Management is the application of disciplined analytics that predict consumer behaviour at the micromarket level and optimize product availability and price to maximize revenue growth. The primary aim of Revenue Management is selling the right product to the right customer at the right time for the right price and with the right pack. The essence of this discipline is in understanding customers' perception of product value and accurately aligning product prices, placement and availability with each customer segment. Cross, R. (1997) Revenue Management: Hard-Core Tactics for Market Domination. New York, NY: Broadway Books.

4 How to ensure we are right? Data Information to support Data

5 Where we can find the data? In most cases, your Property Management System (PMS) stored the customer data could provide the required data Unfortunately standard reports might not be sufficient

6 Resources Requirement If resource is available, o Business Intelligence Solution o Outsource If not..

7 Case Study Opera PMS Vision MS Excel MS Access Keeps the daily detail activities of each inhouse guest Excel limitation: Excel XP : 65,536 rows, 256 columns Excel 10 : 1,048,576 rows, 16,384 columns 100 rooms hotel, 80% occupancy, 50% double occupancy, ALOS 2 nights : 100 x 80% x 365 x 1.5 x 3 = 131,400 records

8 Extract data from PMS Vision works as an add-on in MS Excel Extract data from PMS directly Create macros in MS Excel to simplify repeated tasks

9 PMS Data Stay history & future reservations for o Checked out o In-house / due out o Reserved o Cancelled / no shows Group blocks o Definite o Tentative / inquiry o Allotment

10 PMS Data Room status o Out of order o Out of service

11 PMS Data Based on PMS configuration, fields include: o Reservation ID o Status o Arrival Date o Departure Date o Creation Date o Company ID o Travel Agent ID o Market Code o Source Code o VIP Code o Nationality o Country o Origin Code o No of Rooms o Room Number o Room Type o Rate Type Code o Room Revenue o F&B Revenue o Total Revenue o Rate Code o Rate Amount o Discount o Block Code o Payment o Membership o Adults / Children o Discount o Specials Requests o

12 MS Access Create databases in MS Access to store the data extracted from PMS via Vision Create other databases for code definitions

13 MS Access Create queries in MS Access to filter and consolidate the data Link to other tables to obtain other information

14 MS Access Create Macros to simplify work flow o Import / export MS Excel files o Calculate o Print

15 Daily Work Flow Upload the MS Excel file to MS Access for storage Run Vision to extract data and save in a designated location or export consolidated data back to MS Excel for further processing Run MS Access queries to generate reports

16 Reports Create Reports in MS Access o Consolidated reports o Comparison reports Export report data from MS Access and pick up by MS Excel o Graphical reports o Interactive reports

17 Report Contents Level o o Total Hotel Company / Profile Dimensions o o o o By Market Segment By Room Type Paid vs Stayed Upgrade reason By Channel By Geographic Values o o o o o o o Detail o o Room Nights Guest Nights Rooms Revenue F&B Revenue Other Revenue Arrivals Cancellation / no show Monthly Day of week

18 Use of Customer Data Revenue Management practices o Business on-the-book and pick up

19 Business OTB & Pick up On book and daily pickup o By Market Segment o By Distribution Channel o By Room Type o By Rate Code o By Company / Travel Agent / Block Reservations Pace

20 Use of Customer Data Revenue Management practices o Business on-the-book and pick up o Forecasting

21 Forecast Extract and keep the data on a daily basis to obtain the trend and pace

22 Forecast Current Historical Pick Up Trend On Book

23 Forecasting Estimate a forecast base on current on book plus historical pick up pace / current trend

24 Segmentation Forecast Wholesales Corporate BAR Pick Up On Book Pick Up On Book Pick Up On Book

25 Daily Segmentation Forecast Wholesales Corporate BAR Pick Up On Book Pick Up On Book Pick Up On Book Pick Up On Book Pick Up On Book Pick Up On Book 15 Dec 16 Dec

26 Daily Room Type Forecast Suite Club Rooms Pick Up On Book Pick Up On Book Pick Up On Book Pick Up On Book Pick Up On Book Pick Up On Book 15 Dec 16 Dec

27 Use of Customer Data Revenue Management practices o Business on-the-book and pick up o Forecasting o Hotel performance

28 Hotel performance Hotel performance in various dimensions o Market segment o Channel o Room type (paid / stayed) o Membership

29 Use of Customer Data Revenue Management practices o Business on-the-book and pick up o Forecasting o Hotel performance Marketing Strategies formation o Product and service redesign

30 Product / Service Redesign Customers preferences o Bed type requirement o Smoking vs non-smoking Rate code materialization o Benefits included package Country of resident / Nationality

31 Use of Customer Data Revenue Management practices o Business on-the-book and pick up o Forecasting o Hotel performance Marketing Strategies formation o Product and service redesign o Distribution strategy forming

32 Distribution Strategy Booking channel performance breakdown o By market segment o By country of guest origin o By room type

33 Use of Customer Data Revenue Management practices o Business on-the-book and pick up o Forecasting o Hotel performance Marketing Strategies formation o Product and service redesign o Distribution strategy forming o Sales administration

34 Sales Administration Company / Travel Agent Performance in various dimensions o Room nights o Rooms Revenue (Average Daily Rate) o Food & Beverage Spent (Average F&B Spent) o Other Expenses o How it s business level compares to previous year

35 Corporate Account Contract Other Areas to review : o Demand by room type o Number of upgrades o Loyalty programme / FFP membership o Booking channels Tailor-make the contract offer

36 Account Production Group multiple profiles with an unique ID Jan Feb Mar Apr May Jun Room Night Room Rev 4,843 9, ,620 1,220 0 F&B Rev Other Rev 1,709 1, Add second level filter such as o Buying room type o Booking channel o Loyalty programme membership

37 Sales Administration Sales Manager Portfolio o Total Room Nights o Rooms Revenue, F&B Revenue & Total Revenue o Top Accounts (Increase / Decrease)

38 Information Checking Reservations Errors o Complimentary Rooms with Rooms Revenue o Corporate / Wholesale Rate without Profile linked o Missing or invalid codes used

39 Benefits of Using Guest Data Free of charge Primary data Relevant to your business Up-to-date

40 Reminder

41 Thank You

Basic revenue management guidelines

Basic revenue management guidelines Hotel, hostel, apartments & meeting rooms. By John Kennedy john.kennedy@kennedyandersson.com INTRODUCTION Revenue Management (RM) This guide will explain what RM is