LodgIQ helps revenue teams to have optimal group revenue strategy by recommending Group price that will give the hotel/portfolio the right mix of Group and Transient business. This enables the hotel to evaluate the opportunity cost of potential Group business and help meet revenue goals for the hotel.
LodgIQ provides a robust control center to support group business called the “LodgIQ Group Displacement Evaluator” which makes it simple to manage group business on a daily basis. It enables a break even analysis for potential group business. The group displacement tool enable users to control:
Displacement calculations determine the Group Price Quotation & an estimate of Displaced Revenue for each stay date and the group total based on factors including current demand and Forecast (by market segment), historical data, current and competitor rates,
Ancillary Profit margins, Commission %. After the calculations, users are provided with a group price quotation to manage group sales strategies with ease.
To use LodgIQ Group Displacement Evaluator:
1. Visit LodgIQ RM:
2. Switch to your hotel or “LodgIQ RM Demo”
3. Open up the Group Tile. Select a Date range, Populate Run-of-the-House, Populate Ancillary revenue and hit Submit.
4. View the Optimal Rate
5. Include Ancillary revenue and press the Submit button again.
6. Export the quote to an Excel to view full details and also Alternate Dates.
7. To cross-verify, visit main dashboard,
* Displacement Calculator shows the minimum rate with which the Group can be quoted and revenue displaced.
LodgIQ’s core pricing engine (part of LodgIQ Vision offering) recommends sell-rates at BAR level for Room Types. These recommended prices are pushed to CRS/PMS where all the adjustments for different rate plans and rate codes are applied.
LodgIQ Pricing engine is easily extensible from bar pricing to segment based pricing. This is achieved by creating plans that float off of BAR with a discount percentage so that the hotel achieves optimal revenue during exceptionally busy periods or any special event as well as days with lower demand.
The plans are determined by the hotel and market demand, competitor rates etc. This is accomplished by a sophisticated rules engine. Currently, LodgIQ uses a complete UI-Less implementation of these rules-engine. This is to enable full automation i.e. auto-pilot and restrictions push (such as CTA, CTD, LOS) based on demand.
A full UI version will be available in LodgIQ Voyager release (Q4 2021).
LodgIQ Voyager (Rules, Restrictions and Promotions) will recommend sell-rates for various market segments and/or rate codes. LodgIQ determines these rates by segment based on various factors e.g. hotel forecast, market forecast and special events.
Moreover, users will also have the option to enter certain criteria that will affect how rates are derived for various market segments and/or rate codes.
Customers can come to RM UI and fill the plans as per their convenience. If the plans are not filled, they will be recommended by LodgIQ’s AI Platform.
LodgIQ’s pricing engine is a third- generation, patent-pending algorithm developed over several years based on feedback from hundreds of revenue managers using a production environment. The basic design tenets are:
LodgIQ’s pricing engine optimizes revenue based on demand (total number of people interested in booking regardless of price) and willingness-to-pay (the maximum a given potential customer is willing to pay for a night’s stay at the given property). It enables hotels to make the most of market dynamics through real-time price optimization for the upcoming 365 days by continuously exploring the market’s willingness to pay.
By dynamically adjusting to competitors’ rates, the pricing makes sure hotels benefit to uniquely tailor their pricing strategy to each night to maximize revenue. LodgIQ combines and analyzes more data than any other RMS. Data sources include forward looking market data, hotel reservation data and booking trends, competitor rates, events, hotel reviews and macroeconomic trends.
LodgIQ’s patent-pending events impact estimation and market insights algorithm detect unexpected events or market demand fluctuations thus developing a robust top-down pricing strategy.
The figure (What-If) illustrates the points and helps revenue managers understand maximized revenue and rooms pickup.
Extensibility
LodgIQ Pricing engine is easily extensible to other dimensions e.g. room-type or LOS or market segment.
By Room Type
LodgIQ introduces pricing optimization at the room-type level using state-of-the-art Machine Learning and AI technologies. Room Type Pricing gives hotels the ability to price different room types independent of each other, based on demand rather than a fixed-dollar amount. The algorithm analyzes the willingness-to-pay for each room type. Such pricing strategy empowers hotels to optimize every single booking (be it a family group, or a couple, or a business traveler) by room type demand.
Length-of-Stay-Discounts and Full-Pattern-Length-of-Stay
LodgIQ Pricing engine is easily extensible from daily pricing to Full-Pattern Length of Stay (FPLOS) pricing based on demand. This is achieved by creating plans that float off of BAR with a discount percentage so that the hotel achieves optimal revenue during exceptionally busy periods or any special event as well as days with lower demand. The plans are determined by the hotel and market demand, competitor rates etc.
LodgIQ uses a complete UI-Less implementation of these rules-engine for FPLOS plans. This is to enable full automation i.e. auto-pilot and auto-rates and restrictions push (such as CTA, CTD, LOS) based on demand. A full UI version will be available in LodgIQ Voyager release (Q2 and Q3 2021).
Example:
As an example, when the system optimization runs and for a target stay date, the projected occupancy is >95% meanwhile the day after the target stay date has low occupancy of 60%, then this rule will fire and apply a 2-night MLOS on the target stay date.
Email Notification
Once system identities which stay dates require LOS, CTA, or CTD, it generates an email notification and delivers it to the DORM to suggest them to apply yield control. Email content example as shown below:
LodgIQ recognizes four tiers of pricing capability in hotels:
Level 1: Hotel Sell-Rates + Competitor rates + Ratings + Reviews
At this level, the pricing model is trained on Hotel Sell-Rates, Competitor rates, Ratings and Reviews. This level can be run without integrating Hotel PMS.
What It Means: No demand data is necessary to generate price recommendations. Hotels can be onboarded within a week with little or no data needed.
Level 2: Level 1 + Hotel reservations
At this level, the pricing model is trained on Hotel Reservations as well as other data sources mentioned above in Level 2. Historical Hotel Reservations are required to train the model.
What It Means: Price recommendations are generated by taking demand into account.
Level 3: Level 2 + Market data
At this level, the pricing model is trained on Market Reservations as well as other data sources mentioned above in Level 2. Historical Market Reservations are required to develop the willingness to pay model.
What It Means: Price recommendations are generated by taking market data into account. The model learns the market’s willingness to pay at this level.
Level 4: Level 3 + Events data
At this level, the pricing model is trained on Events Data as well as other data sources mentioned above upto Level 3. Ingestion of Events Data makes the model responsive to events days and holidays.
What It Means: Price recommendations are generated by considering holidays and special events. Shoulder Dates are automatically generated by the algorithm. The algorithm is able to generate restrictions during high demand dates.
New users are provided access to LodgIQ RM based on the hotel’s data within 2 weeks or less.
The existing spectrum of integrations facilitate a very rapid onboarding process for new users. The onboarding follows a structured process which has been captured as below:
1. Week 1:
2. Week 2-3:
LodgIQ’s AI platform provides users to quickly receive recommendations and forecasts as soon as the onboarding process is achieved. It follows an adaptive strategy that can progressively enhance and incorporate more available data and also gracefully degrade when some data sources are not available.
The four levels of LodgIQ’s AI platform (and data sources) are given below:
Level 1 – Hotel Sell-Rates + Competitor rates + Ratings + Reviews
Level 2 – Level 1 + Hotel reservations
Level 3 – Level 2 + Market data
Level 4 – Level 3 + Events data
LodgIQ RM implements UI screens to manage rates for different market segments or rate-plans such as Advance Purchase, Consortia, AAA, AARP. Voyager UI is meant for several advanced functionalities, e.g. algorithmic Promotions, promotions management UI and collaboration features to name a few. This topic is also covered in question number 2.
Currently, DORMS use an Extranet provided by OTAs (Bookings and Expedia) to manage the promotions. Both are very similar and simple to use. They are usually not alerted when Promotions are expiring so that you can extend, sunset or alter them.
LodgIQ Voyager will programmatically generate these promotions. Along with rate recommendations, identify low-demand periods and recommend a promotion:
A sample promotion would be generated for a specific Audience.
For example, generate offers for 3-night stay for certain room types for Chinese New Year for Chinese guests. Or generate for certain date-range run a promo for Australian visitors Recommend promotions targeting specific DBA booking windows (i.e. customers booking a month in advance vs. 2 weeks in advance) and Fine tune for specific room types
Voyager Promotions UI will provide screens:
– Manage Promotions (edit, delete, pause, resume, archive)
– Track Promotions
– Monitoring pickup patterns for the targeted dates/room-types
– Measuring correlation between promotions and bookings
– Measuring effectiveness by room-type
– Generate Alerts (if occupancy exceeds a threshold
– trigger an alert to pause or adjust an existing promotion)
