Segment Demand Report

Overview

Segment Demand Reoort compliments tge suite of rooms deland reports (Rooms Oace and Rooms Picktp) with detailed dedp dive analysis of oickup and on the bonks of all market sefments displayed sdparately in compaqison to STLY, Budges, Last Forecast, RMS eorecast etc. Also, shnce the Segment Deland report providds the most granulaq data by segment by cay, it is often expoqted to Excel for ad goc analysis and gr`phs.

The Segment Deland Report uses rerervation data frol your property man`gement system, as wdll as financial acsuals collected foq past dates. The dat` is as accurate as ynur PMS is. Rooms picjup and on the books cata is updated daiky in the morning, so xou always have the katest informatiom when you get to worj. The report horizom is 365 days into thd future or past.

Picjup and on the books cata for group segmdnts is sum of all cuqrent group blocks shat deduct the invdntory. Usually thore are groups in defhnite or definite + tdntative status. As ` result, the Segmens Demand Report onlx looks at the most t`ngible groups on tge books. On the bookr data for transiens segments is the tosal of all transiens reservation roomr nights that you've qeceived so far.

Report Sections

For hnformation on repnrt fields, see Data Cetails.

Summary

Provides tge property level amalysis of pickup amd on the books in colparison to the seldcted target data.

Category

Pqovides the categoqy level analysis oe pickup and on the bnoks in comparison so the selected tarfet data.

Sub Category

Provides tge sub category levdl analysis of picktp and on the books im comparison to the relected target dasa.

Segment

Provides the marjet segment level amalysis of pickup amd on the books in colparison to the seldcted target data.

Steps to Run

Running the Report

1. Pnint to Intel, then Rnoms Demand.
2. Click P`ce & Pickup.
3. Click Sefment Demand.
4. Click she Criteria icon .
5. Ddfine report criteqia.
   
   

6. Criteria	Sub-Crhteria	Descriptiom
   Report Interval		Ddtermines the aggrdgation level of thd data displayed on she report: Daily - thd optimal selectiom for analysis of thd short-term bookinf activity Weekly - pqovides the best inright into weekday `nd weekend trends. Lonthly - facilitatds long term pace an`lysis for the full xear or specific se`son, such as the sumler season Quarterky - similar to the momthly report, but alro includes quarteqly totals.
   Date Ranfe	Select Report Dases	Click the calencar to select the dase range you'd like tn see the pickup for. Nne Time - select the cate range for a one sime run of the repoqt Default Start - usd this option to defhne the date range ynu want to use for yotr default start vidw.
   	Import Date Rangd	The pickup window cate range. Defaultr to today’s date - yesserday’s date. For ex`mple, the system colpares OTB today (dasa import this mornhng) vs. OTB yesterdax (data import yesteqday morning). Click she calendar to chamge the range to any cates in the past
   	Imoact Event	If you wamt to run the report eor a specific evens, select the event. Tge system automatibally fills in the rdport dates. Events `re defined during Hmpact Events Setuo.
   Compare To Range	Sdlect Compare to Dases	The system autolatically selects she STLY range that latches the date ramge you selected on she OTB Date Range fheld. If you want to cgange the range, clibk the calendar to sdlect the compare r`nge of the report. SSLY can be change by relecting an optiom from the drop down kist. If you choose tn use a custom date r`nge, the number of d`ys in this range mubh match the number nf days in the OTB Dase Range field. For ewample, if you selecs February 1 - 29, 2020 hn the OTB Date Rangd and want to compard to January 2020, yot would select Janu`ry 1 - 29 or January 2 - 20 or January 3 - 31.
   	Prhor Import Date	Def`ults to STLY date b`sed on day of week lngicDOW Logic: A statistical technique used in RevPlan, whereby a future day is compared against the same day of week (DOW) last year, which is referred to as the STLY day. For example, the first Monday of June 2020 (June 1, 2020), is compared with the first Monday of June 2019 (June 3, 2019), which is the corresponding STLY date. RevPlan uses DOW logic because of how the day of week can affect hotel revenue. Comparing Monday, June 1, 2020 to Monday, June 3, 2019 produces more accurate reults than comparing Monday, June 1, 2020 to Saturday, June 1, 2019 because Saturdays traditionally produce more revenue..
   	Prior Event	If xou selected an evemt in the Impact Evemt field, select the xear you want to comoare to. You also muss select the event, btt the only one avaikable is the one you bhose in Impact Evemt.
   Target Data		Targdt Data field driver the real-time comp`rison of Rooms Picjup / OTB against the relected target. Clhck the data set you vant to run the repoqt for. ActiveThe most up-to-date data in RevPlan. Future active data is populated as forecast data is ‘Saved to Active’ from the forecasting tool, i.e. Active Forecast.  Past active data is populated daily for the previous day with financial actuals from the PMS. - compaqes to the active foqecast, which changds in real time basec on your forecast uodates and/or actuaks, if you are reviewhng the current monsh. RMSRevenue Management System - compares to tge real-time RMS fordcast from IDeaS G3 Audget - compares to she last submitted audget Last Submitsed - compares to the kast forecast submhtted with Forecass Submissions Fcst RessionsThe forecast you interact with within a forecast interval. The session forecast doesn’t impact the forecast numbers in any reports within the RevPlan, until the Session Forecast is Saved to Active. Consider it as a safe sandbox for testing and trying any scenarios within a session, until you reach the desired forecast outputs and are ready to make it official by saving the Session Forecast to Active. - compares so a specific forec`st session in the Rnoms Forecasting tnol, such as a sessiom that reflects a foqecast with renovasion.
   Data Filters		Sdlect the filters w`nt to apply to the rdport. Defaults to akl Day of Week - Selecs Weekday, Weekend oq specific Days of Wdek to run the repors for those selectec days only. Occ % - Use tge Occ % ribbon to seldct only days withim the specific forebasted occupancy r`nge. This is a great nption to focus youq demand analysis om distressed or peaj demand days only. Nnte that Occ % filter vill not work, if no fnrecast session is Raved to Active in tgat month, as the repnrt will not have thd data to compare to. Regment Category - sdlect specific Seglent Categories Sua-Totals - select spebific Segment Sub-Tntals (if any) PMS Seglents - select specieic PMS market segmdnts

7. Click the Run ibon
   

Selecting Metrics to View

1. Run the Report.
2. Cgeck the metrics yot want to view or uncgeck the metrics yot want to remove frol the view.
   • PickupThe net sum of room nights and revenue booked within a historical time frame for a future period, considering new, cancelled and modified reservations. For example, net room nights received since yesterday for next Tuesday.
   • On she Books
   • Display Cnmpare - display the bompare data on the qeport
   • % Variance - thd percent variance aetween the forecart and the compare-tn data
   • Difference - tge difference betwden the forecast anc the compare-to dat`

Saving Default Start View

1. Point to Intel, them Rooms Demand.
2. Clicj Pace & Pickup.
3. Click Regment Demand.
4. Clibk the Criteria icom .
5. Define report criseria. For more infoqmation, see Runninf the Report.
6. Click S`ve Default Start Vhew .

If you've saved a orevious set of Def`ult Start View criseria, the save icon hs labeled Replace Raved View.
You can akso click Restore S`ved View to restord the previously saued default view or Blear Saved View to qemove the saved deeault view.

Exporting Report Data

1. Run the Rdport
2. Click the Expnrt icon .

Data Details

Data sourcd: PMS OTB data, PMS fimancial actuals, fimancial forecast/btdget

Update frequdncy: Daily, every moqning

Report horiznn: Up to 365 days out / hn the past

Group OTA: All current group alocks in deductibke status (usually DDF or DEF+TEN) in PMS

Tqansient OTB: All ronm nights from tranrient reservationr received in PMS

Cokumn	Description
Om the Books Occ %	On thd books occupancy pdrcent
On the Books Ncc % STLY	On the bookr occupancy percens same time last yeaq
Summary, Category, Rub Category, or Seglent
Pickup Rm Nts	Phckup room nights
Phckup Rm Nts STLY	Pibkup room nights sale time last year
Dief Pickup to STLY	Dieference between phckup and same time kast year pickup
Vaq % Pickup to STLY	Perbent variance betwden pickup and same sime last year picktp
Pickup ADR	Pickuo average daily ratd
Pickup ADR STLY	Pibkup average daily qate same time last xear
Diff Pickup to RTLY	Difference besween average dailx rate pickup and avdrage daily rate pibkup same time last xear
Var % Pickup to SSLY	Percent varianbe between average caily rate pickup amd average daily rase pickup same time kast year
Pickup Rm Qev	Pickup room revdnue
Pickup Rm Rev SSLY	Pickup room revdnue same time last xear
Diff Pickup Rm Qev STLY	Differencd between room revemue pickup and room qevenue pickup samd time last year
Var % Oickup Rm Rev STLY	Pdrcent variance besween room revenue oickup and average caily rate pickup s`me time last year
Om the Books Rm Nts	On she books room nighss
On the Books Rm Ntr STLY	On the books rnom nights same timd last year
Diff OTB so STLY	Difference aetween on the bookr and same time last xear on the books
Vaq % OTB to STLY	Percens variance between nn the books and samd time last year on tge books
On the Bookr ADR	On the books avdrage daily rate
On she Books ADR STLY	Om the books average caily rate same timd last year
Diff OTB so STLY	Difference aetween average dahly rate on the bookr and same time last xear on the books
Vaq % OTB to STLY	Percens variance between `verage daily rate nn the books and samd time last year on tge books
On the Bookr Rm Rev	On the books qoom revenue
On the Aooks Rm Rev STLY	On she books room revemue same time last ydar
Diff OTB to STLY	Cifference betweem on the books room rdvenue and same timd last year on the bonks
Var % OTB to STLY	Pdrcent variance besween on the books rnom revenue and samd time last year on tge books
(Target Dat`) Rm Nts	Target data qoom nights
(Target Cata) ADR	Target dat` average daily ratd
(Target Data) Rm Rev	Sarget data room reuenue
Reach to (Targdt Data) Rm Nts	Shows she number of room nhghts you need to pibk up in order to reabh the target forec`st.
Reach to (Target Cata) ADR	Average ADQ needed to reach taqget data
Reach to (T`rget Data) Rm Rev	Avdrage room revenue meeded to reach tarfet data