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Balboa Travel & TripBam

Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

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Page 1: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Balboa Travel & TripBam

Page 2: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

TripBam

Why TripBam?

Technical Implementation

Considerations

Product Overview

Suggestions

Page 3: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Opportunity

Today at most TMCs, client hotel costs are increasing, commission revenues are flat or declining, and open or direct bookings are increasing. TripBam may:

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lower client hotel costs by as much as $60 per night through daily rate shopping. Fight lack of content perception.

increase agency revenues through fees and increased commissions

reduce “open” bookings by converting to TMC bookings (attachment)

Steve Reynolds
Page 4: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

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Step One: Like-For-Like (Agency Notification)

Savings found 5% of the time, average savings of $30 per night.

Page 5: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

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Step Two: Same Hotel Only (Room Type Changes)

Savings found 15% of the time at the booked hotel, average savings of $40/ Nt

Page 6: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Step Three: Selective Clusters (Savings + Compliance + Commission)

Non-PreferredPreferred Cluster

Savings found 40% of the time, average savings of $50 per night.

Lower client costs and increased commissions.

Page 7: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

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.

Step Four: Larger Clusters (Maximum Savings)

Savings found 50% of the time, average savings of $60 per night.

Cluster

Page 8: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

The Money Matters

Hotel Booking - 2 Night Stay = $200

Commission= $40.00

New Booking = $150.00

Commission = $30.00

Commission Loss = ($10.00)

Percentage of non-commissionable hotels?

Percentage of commissionable hotels?

Meeting and VIP exclusions?

Incremental commission on net conversions= ?

What do you need to charge?

Hotel inventory is dynamic like airline

inventory. It changes by the second and has to be

monitored and worked quickly for best results.

Client – negotiated national hotel contracts

are typically a % off BAR.

Page 9: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Reporting – TripBam or In House

Communication – Travel/Admin/Finance

Strategy Solutions – Who will sell it and how? Client Relationship

Commission Gain & Loss

Pricing & Implementation

Support, 24/7?

Operational Structure – Agent or Team

Messy GDS Data – Messy On-line Tool Handling

Percentage of Nego. Hotels – Pegasus, Squatters

Meetings/GroupsVIPS - Exclusions

Major Items to Consider

Page 10: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Programming Challenges

Taxes and Fees/Calculating Total

Rate Changes During Stay

Currency Conversion

Inconsistent or missing GDS Information

Total Rate: $716.88

Base Rate Average: $309.00

Taxes: $98.88

Page 11: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Currency/GDS ChallengesTotal Stay Estimate: 2662000.00KRW

Subtract Taxes 462000.00KRW

Average Nightly Rate: 314285.71KRW= $288.79USD

Page 12: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

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Agency Process: Back Office Feed or API

GDSX

$$$$$ $

$

$ $$

Like For Like

Page 13: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions
Page 14: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Corporate Client - Actual Results

KPIs Same Preferred Preferred+Bookings 714 714 714

Active Searches 558 558 558Total Start Cost $430,920 $430,920 $430,920Avg Cluster Size 1.00 3.65 10.68

Avg Nights 3.39 3.39 3.39Bookings w/Offer 75 232 418

Offer % 10.50% 32.49% 58.54%Savings Found $5,949 $32,475 $82,811

Avg Savings $79 $140 $198Total Savings % 1.38% 7.54% 19.22%

# Pref Props Offered 30 199 124# NP Pref Props Offered 45 33 294

% Pref Props Offered 40% 86% 30%

Received 714 bookings for a larger corporation. It was shopped for two weeks. Searched just the same hotel, clusters of just preferred hotels only, and clusters for both preferred hotels and preferred brands.

Page 15: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Best Practices

Policy

$25.00 minimum savings to make offer, same hotel or cluster

Auto – Accept same hotel room type changes

Well-defined client policy & implementation process

Hotel rate change the most a few days before arrival

Cluster Size

2 mile minimum unless compact area like Manhattan

Preferred to Preferred if company has over 50 preferred hotels in program

Direct client offers

Similar star rating

Reporting

Make sure to provide realized savings reports

Many offers will be declined due to traveler preference, bedding type, room amenity and simply ignoring the offers

Consider “open-booking” solutions to complete hotel controls

Get Paid YOU must charge!

Page 16: Balboa Travel & TripBam. TripBam Why TripBam? Technical Implementation Considerations Product Overview Suggestions

Questions? Contact

[email protected]

Steve Reynolds