jason houle vice president, travel operations lixto travel price intelligence 2.0

34
Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

Upload: evan-small

Post on 12-Jan-2016

224 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

Jason HouleVice President, Travel Operations

LixtoTravel Price Intelligence 2.0

Page 2: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

2©2010 Lixto Software

My name is Jason Houle. For the last 5 years I have been building the price intelligence business for Lixto software in the travel vertical. Our price intelligence solution delivers real-time competitive price visibility on the web.

It is critical that OTA’s and hoteliers monitor pricing, product ranking and customer evaluations on the web to ensure their competitive positioning. It is a well established fact that there are considerable price differences for the same product across different distribution channels – rate parity is a myth. Price optimization needs to be based on market information that reflects what customers are basing purchase decisions on - AND THAT IS INFORMATION OFF THE WEB!!!

Today I will present an application built for the hospitality industry and I will show you how our clients use this information to benchmark the performance their products and to control the efficiency of their online distribution channels.

In the development of this solution Lixto has pioneered three innovations that enable us to deliver the highest quality, most efficient price intelligence solution available.

Page 3: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

3©2010 Lixto Software

Innovation 1: Lixto Visual Developer

The Visual developer is a visual development environment that we use to develop our data aggregation programs otherwise known as screen scrapers to get data off the web.

We were awarded a patent in early 2010 for our unique approach to data aggregation. The video playing in the background is a recording of one of our engineers developing a data extraction program on the BOOKING.com website.

The engineer is recording a navigation sequence to teach the tool where to find the data we are interested in. You can think of this as something like a macro recorder and the process is set up once for each website that our clients want to collect data fromOnce this navigation sequence is configured we can feed any combination of query parameters through the navigation sequence.The entire program is developed without programming a single line of codeThe main benefits of having patented technology like the Lixto Visual Developer to build onFirst: we can set up these processes very quicklySecond: Maintenance is required when the structure of the website changes. The entirely visual nature of the development process means that the maintenance can be easily delegated to any free resource in our team as there is no code that needs to be picked apart.

Normally our clients don’t even realize we have performed maintenanceThe data extraction programs are then deployed on cloud resources –

Using many thousands of IP ranges that are constantly changing makes it nearly impossible for us to be detectedWe look like a customer visiting a website

Our clients can scale up as required without the expenses or headaches associated with hosting the entire service ouselves

Page 4: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

4©2010 Lixto Software

Innovation 2: Data consolidation using crowd sourcing

Everyone has heard of the cloud –let’s talk about the crowd

A lot of the data we get like cancellation conditions, meal plans room type descriptions is unstructured located in free text fields on the websitesThis information needs to be mapped, or normalize the data so that it becomes comparable and we can perform analysis on it.

It is nearly impossible to develop algorithms that perform this mapping correctly 100% of the so we don’t even try

We use a low tech but extremely scalable solution utilizing hundreds of outsourced workers to perform our data matching jobs on the fly as mini tasks.

Whenever we have a new website to collect data from, or data changes on a website we have a data mapping challenge that is handled through crowd sourcing to enable our customers to scale horizontally quickly and cost efficiently

Page 5: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

5©2010 Lixto Software

Innovation 3: Our SaaS analytics platform

Although our clients benefit from two important innovations on our back-end the only thing they see is their own customized analytics platform which I am going to demonstrate for you now.The platform was developed using Oracle Business Intelligence to enable us to handle the requirements of even the largest of organizations

Page 6: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

6©2010 Lixto Software

Price Analytics and Operations

Page 7: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

7©2010 Lixto Software

Price Analytics & Price OperationsHOME PAGE

Page 8: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

8©2010 Lixto Software

Price Analytics & Price OperationsHOME PAGE

Page 9: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

9©2010 Lixto Software

Price Analytics & Price OperationsHOME PAGE

Page 10: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

10©2010 Lixto Software

Price Analytics & Price OperationsHOME PAGE

Page 11: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

11©2010 Lixto Software

Price Analytics & Price OperationsHOME PAGE

Page 12: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

12©2010 Lixto Software

Price Analytics & Price OperationsHOME PAGE

Page 13: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

13©2010 Lixto Software

Price Analytics: Hotel

Page 14: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

14©2010 Lixto Software

Price Analytics: Hotel

Page 15: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

15©2010 Lixto Software

Price Analytics: Hotel

Page 16: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

16©2010 Lixto Software

Price Analytics: Hotel

Page 17: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

17©2010 Lixto Software

Price Analytics: Price Development by Check-In Date

Page 18: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

18©2010 Lixto Software

Price Analytics:

Price Development by Check-In Date

Page 19: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

19©2010 Lixto Software

Price Analytics:

Price Development by Check-In Date

Page 20: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

20©2010 Lixto Software

Price Analytics:

Price Development by Check-In Date

Page 21: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

21©2010 Lixto Software

Price Analytics: Price Development by Check-In Date (Price Evolution)

Page 22: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

22©2010 Lixto Software

Price Analytics: (Price Evolution)

Price Development by Check-In Date

Page 23: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

23©2010 Lixto Software

Price Analytics: (Price Evolution)

Price Development by Check-In Date

Page 24: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

24©2010 Lixto Software

Price Analytics: (Price Evolution)

Price Development by Check-In Date

Page 25: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

25©2010 Lixto Software

Price Analytics: Price Exception

Page 26: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

26©2010 Lixto Software

Price Analytics:

Price Exception

Page 27: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

27©2010 Lixto Software

Price Analytics: Price Exception Mails

Page 28: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

28©2010 Lixto Software

Price Analytics:

Per Exception

Page 29: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

29©2010 Lixto Software

Price Analytics:

Per Exception

Page 30: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

30©2010 Lixto Software

Price Analytics:

Per Exception

Page 31: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

31©2010 Lixto Software

Summary

Our solution is designed to deliver key insights to help optimize pricing and workflow tools to speed up corrective measures to price discrepanciesLeveraging our Visual developer, our crowd sourcing solution and our SaaS analytics Lixto delivers a significant and measurable increase to top line revenues for our clients by enhancing their ability to optimize prices in near time.

Page 32: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

32©2010 Lixto Software

Price Operations: Hotel Peer Group Report

These were not in screenshots so I just put them on the background

Page 33: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

33©2010 Lixto Software

Price Operations:

Hotel Peer Group Report

Iberostar Albufera Park

Peer Group min€ Rating Page rank min€ Rating Page rank min€ Rating Page rank min€ Rating Page rank

Grand Total 209 285 8,9 1 420,42 8,9 1 911,61 8,9 1 209 8,9 1Iberostar Albufera Park 209 285 8,9 1 420,42 8,9 1 209 8,9 1

Grupotel Parc Natural & Spa 764,93 299 7,6 5 1050 7,6 5 911,61 7,6 5

Eden Playa 374,49 299 7,9 9 532 7,9 9

Iberostar Albufera Playa

Peer Group min€ Rating Page rank min€ Rating Page rank min€ Rating Page rank min€ Rating Page rank

Grand Total 234 754,89 8,9 1 574 8,9 1 672,15 8,9 1 234 8,9 1Iberostar Albufera Playa 354 728 8,9 1 728,18 8,9 1 354 8,9 1

Grupotel Parc Natural & Spa 764,93 1050 7,6 5 911,61 7,6 5

Grupotel Gran Vista & Spa 234 754,89 7,9 9 574 7,9 9 672,15 7,9 9 234 7,9 9

Palace de Muro 862,12 875 7,9 9 1093,87 7,9 9

Iberostar Alcudia Park

Peer Group min€ Rating Page rank min€ Rating Page rank min€ Rating Page rank min€ Rating Page rank

Grand Total 90 135 8,9 1 378 8,9 1 481,35 8,9 1 90 8,9 1Iberostar Alcudia Park 129 139 8,9 1 532,35 8,9 1 481,35 8,9 1 129 8,9 1

Grupotel Los Principes & Spa 553,6 574 7,6 5

Viva Blue 90 378 7,9 9 90 7,9 9

Playa Garden 161 135 7,9 9 161 7,9 9

Thomas Cook

Property web channel

Property web channel

Booking

Booking

Ebookers

Ebookers

Thomas Cook

Thomas Cook

min€

min€

min€

Property web channel Booking Ebookers Switch between currencies;Switch between min./max./avg in combination withSwitch between values only, values+%, values+percent+rating/ranking

By default, min. price, reviews and rankings are displayed in the tableDrill-downs to

offer

Displays prices per hotel and its competitive set on the property‘s own channel and monitored web channels

shows at how many offers the user is looking per attribute (as on home dashboard)

Page 34: Jason Houle Vice President, Travel Operations Lixto Travel Price Intelligence 2.0

34©2010 Lixto Software

Price Operations:

Mockup – Hotel Peer Group Exceptions

Price Exception by Check-in Date

Peer Group

Check-in Date Hotel Web Channel Extraction Date Nights Board Category Room Category PAX Own Price € min€ avg€ Diff Diff%Iberostar Albufera Park Booking.com 11.03.2010 1 Room and Breakfast Standard 2 130,00 110,52 132,05 19,48 -17,6%

Iberostar Albufera Park Booking.com 11.03.2010 1 Room and Breakfast Junior Suite 2 130,00 128,00 144,17 2,00 -1,6%

Iberostar Albufera Park Expedia.co.uk 11.03.2010 1 Room and Breakfast Superior 2 160,00 159,00 176,28 1,00 -0,6%

Iberostar Albufera Park hotel.de 11.03.2010 1 Room and Breakfast Superior 2 160,00 150,14 164,94 9,86 -6,6%

Iberostar Albufera Park hotel.de 11.03.2010 1 Room and Breakfast Superior 2 160,00 157,90 171,64 2,10 -1,3%

Iberostar Albufera Park HRS 12.03.2010 1 Room and Breakfast Superior 2 160,00 154,00 163,24 6,00 -3,9%

Iberostar Albufera Park HRS 12.03.2010 1 Room and Breakfast Standard 2 130,00 127,30 135,61 2,70 -2,1%

Iberostar Albufera Park Venere 12.03.2010 1 Room and Breakfast Superior 2 160,00 151,30 164,46 8,70 -5,8%

Iberostar Albufera Park Venere 12.03.2010 1 Room and Breakfast Standard 2 130,00 129,00 143,84 1,00 -0,8%

Iberostar Albufera Park Booking.com 12.03.2010 1 Room and Breakfast Standard 2 130,00 129,00 141,72 1,00 -0,8%

Iberostar Albufera Park Expedia.co.uk 15.03.2010 1 Room and Breakfast Standard 2 130,00 117,50 132,19 12,50 -10,6%

Iberostar Albufera Park hotel.de 15.03.2010 1 Room and Breakfast Standard 2 130,00 120,00 135,16 10,00 -8,3%

Iberostar Albufera Park Venere 15.03.2010 1 Room and Breakfast Superior 2 160,00 149,14 165,34 10,86 -7,3%

Iberostar Albufera Park Booking.com 11.03.2010 1 Room and Breakfast Standard 2 130,00 119,13 132,08 10,87 -9,1%

Iberostar Albufera Park Booking.com 11.03.2010 1 Room Only Suite 2 419,00 407,14 455,43 11,86 -2,9%

Iberostar Albufera Park hotel.de 11.03.2010 1 Room Only Suite 2 419,00 404,00 464,60 15,00 -3,7%

Iberostar Albufera Park HRS 16.03.2010 1 Room and Breakfast Standard 2 130,00 117,50 132,19 12,50 -10,6%

Iberostar Albufera Park HRS 16.03.2010 1 Room Only Standard 2 130,00 128,00 144,17 2,00 -1,6%

Iberostar Albufera Park Venere 16.03.2010 1 Room and Breakfast Superior 2 160,00 158,00 181,70 2,00 -1,3%

Iberostar Albufera Park Venere 17.03.2010 1 Room and Breakfast Standard 2 130,00 128,00 147,81 2,00 -1,6%

12.04.2010

13.04.2010

15.04.2010

Like-to-like comparison

Sort table by check-in date / price deviation / Country, City, Hotel

Per default sorted by check-in date

Drill-down to offer level

Compare own room prices with prices of comparable rooms from the competitive set