Build Your AI Hotel Revenue Forecast Analyst

Go beyond pasting pace reports into an AI chat tool.

You already know AI can analyze a report you paste. That isn't what this is. This is how you build a hotel forecasting system wired to your PMS, your POS data, and your booking patterns, so the analysis runs whenever you ask, against live reservation data, in a workflow you built and control.

Self-paced with no time limit and permanent access to all materials.

20+ hoursShort, one-topic, on-demand videos

5-10 minutesLessons designed to fit into your lifestyle

Forever accessSelf-paced with no time limit

Real transaction dataWork from practical business examples

Unlimited course updatesEvery new module and improvement included for life

For revenue managers who have hit the ceiling with AI chat platforms

Your hotel forecast should not start over every Monday morning.

You use AI chat platforms to analyze your hotel data. You get useful answers. But every session starts from scratch: export the pace report, paste it in, explain your segments again, prompt again when it loses direction, get a number, close the tab. Your PMS, your STR data, your booking window — each one a separate one-time task. Nothing connects. Nothing persists. This course is for revenue managers who are done with that pattern and ready to build a connected hotel forecasting system that runs on their real reservation data without the manual reset every week.

What you build

Control your entire hotel forecasting ecosystem.

Not a one-time answer you paste into a chat window. A connected system that runs against your real data, on demand, whenever you need it.

connected_tools

Your PMS, POS data, and Excel files wired to the AI agent through MCP, so it reads your live reservation data instead of a pace export you pulled this morning.

data_ontology

Your segments, rate codes, comp set, and booking window rules encoded once, so the agent stops guessing what transient, compression, or OTB mean at your property.

forecast_workflow

Pickup tracking, pace analysis, and demand forecasting that run end to end against live reservation data, without you stitching the steps together by hand each Monday.

defensible_output

Pricing recommendations you can take into the revenue strategy meeting, because you know how the model reached them and where it would break.

A connected system gives you what chat alone cannot:

Grounded answers. AI works from your actual PMS and Excel data instead of generating answers from a paste you pulled this morning.

Consistent analysis. Your pickup methodology and pace logic are codified, so the same process runs every Monday without variation.

No repeated explanations. Your rate codes, segments, comp set, and booking window rules are preserved in your hotel ontology and never need to be re-explained.

A structured path from data to decision. The agent remains guided through each stage of the hotel forecasting workflow instead of losing direction when the analysis gets complex.

Less wasted token use. Your workflow retrieves only the relevant pace, pickup, and demand data instead of repeatedly sending full PMS exports and entire datasets.

A skill that advances your career. Revenue managers who can build and direct connected AI systems are rare. This moves you from report reader to the person who owns the hotel forecasting infrastructure.

The curriculum

Know every forecasting method.Know how to direct AI to apply them.

RM Data Extraction and Preparation

Hotel forecasting starts before any analysis runs. Your reservation data lives in a PMS, your market data in STR, your channel performance in your OTA extranet, and none of it arrives in a form the AI agent can immediately use. This module covers how to extract data from the real systems revenue managers actually run on, how to handle the transformation step that turns a raw PMS export or Excel file into a clean, structured reservation file, and how to build a preparation pipeline that runs the same way every Monday regardless of who runs it. Getting this step wrong produces pickup and pace figures that look precise while being systematically wrong, and most revenue managers never trace the error back to the extraction.

You will build a repeatable RM data preparation pipeline using real PMS and STR data, identify and correct the quality issues that produce misleading pace figures, and understand how to structure the staging step so your workflow never depends on a manually cleaned spreadsheet.

Hotel RM Ontology and MCP Setup

An AI agent does not know what your hotel's data means. It knows what the field names say, but not what transient means at your property versus a competitor's, whether your OTB figure includes tentative group blocks, how your rate codes map to your actual pricing strategy, or what your comp set looks like this year after a renovation changed it. A hotel RM ontology solves this by encoding your segments, rate codes, booking window rules, comp set definition, and RevPAR calculation logic once, permanently, so every analysis the agent produces is reasoned in your terms. MCP then wires your data systems directly to the agent, so instead of pasting a pace report into a chat window, the agent reads your live reservation data and runs your workflow on demand.

You will build a working hotel RM ontology and configure an MCP connection to at least one real data source, so the forecasting and pricing workflow you build in later modules runs against live reservation data from day one.

Pickup and Pace Analysis

Pickup and pace are the most operationally important numbers a revenue manager tracks, and they are also the easiest to misread. This module covers how booking curves work, how to build a same-time-last-year comparison that is actually comparable after calendar shifts and demand changes, how to identify a pace position that is genuinely strong versus one that looks strong because your comp year was weak, and how to detect the difference between a lead-time shift and a real demand change. You will direct an AI agent to calculate pickup across your segments, build your booking curve, and interpret the position in the context of your hotel's historical pattern rather than a generic benchmark.

You will build a pickup and pace analysis that runs automatically against your live reservation data, distinguishes meaningful position changes from noise, and produces a clear answer about where you stand relative to your own history.

Market Segmentation Analysis

A single occupancy and ADR figure hides everything that matters. The revenue story of your hotel is a segmentation story: which channels are producing at what rate, whether your transient mix is shifting toward lower-rated OTA business, whether your negotiated corporate accounts are booking ahead or coming in last minute, and whether your group base is covering the periods where transient demand falls short. This module covers how to build a segmentation analysis that answers those questions automatically, how to direct the AI agent to detect mix shifts early, and how to interpret the patterns in your own data rather than fitting your hotel into a generic framework.

You will build a segmentation analysis that breaks down your reservation data by segment, channel, and lead time, automatically flags material mix shifts, and delivers a clear picture of where your revenue is actually coming from each week.

Competitive Set and Rate Analysis

Your pricing does not exist in a vacuum. Rate decisions are made relative to a comp set, and most of the errors revenue managers make in competitive positioning come from reading STR data incorrectly: comparing index figures without accounting for mix differences, reading rate parity as a pricing strategy rather than a floor, or missing the point in the booking window where your competitors moved and your rates did not. This module covers how to build a comp set analysis that detects meaningful rate moves rather than noise, how to identify your fair share position by day type and segment, how to work with the rate data you have in Excel or your RMS, and how to direct the AI agent to surface the competitive dynamics your manual analysis would take two hours to find.

You will build a comp set and rate analysis that runs against your rate data and booking history, identifies meaningful rate positioning gaps, and gives you a clear competitive picture before your weekly strategy call.

Demand Forecasting for Hotels

Hotel demand has structure that general forecasting methods do not capture unless you configure them correctly: strong day-of-week patterns, compression periods that create discontinuous demand spikes, lead-time decay curves that vary by segment, and calendar events that repeat annually but shift by date. This module covers the forecasting methods that work on hotel reservation data, how to select the right method for the right horizon and segment, how to build a forecast that separates base demand from event-driven demand, and how to direct the AI agent to run the forecast, evaluate its own accuracy against your recent history, and flag periods where the confidence interval is too wide to rely on.

You will build a hotel demand forecast that runs automatically against your live reservation data, separates structural demand from event-driven demand, and delivers occupancy and RevPAR projections by segment and day type at the horizon your strategy decisions actually require.

Pricing Strategy and Optimization

A forecast tells you where demand is heading. A pricing strategy determines what you charge while it gets there. This module covers how to connect your demand forecast to a rate decision: what BAR logic actually encodes and when it fails, how to build yield thresholds that reflect your property's real cost structure rather than a generic rule, how to think about price elasticity in your specific market and segment mix, how to handle the last-room-available decision correctly, and how to direct the AI agent to evaluate a rate scenario against your forecast and your comp set position simultaneously. The goal is a pricing workflow that produces a defensible recommendation, not just a number.

You will build a pricing workflow that takes your demand forecast and comp set position as inputs, evaluates rate scenarios against your yield thresholds, and produces a pricing recommendation you can walk into a strategy meeting and defend.

Group Evaluation and Displacement

Group business is the most analytically demanding decision a revenue manager makes. A group inquiry arrives with a rate request and a block size, and you have to decide whether to accept it, negotiate it, or displace it in favor of transient demand that has not materialized yet. This module covers how to build a group displacement analysis: how to project the transient demand your group block would displace using your own booking curve, how to calculate the true net revenue of the group after food and beverage and attrition risk, how to evaluate concession requests against your pace position, and how to direct the AI agent to run the full displacement model and produce a clear accept, negotiate, or decline recommendation with the numbers to back it up.

You will build a group displacement model that runs automatically against your current pace and transient booking curve, calculates net group value, and delivers a clear recommendation with the supporting analysis for every group inquiry your sales team brings to you.

Directing the AI Agent

Knowing what the right RM analysis is and knowing how to direct an AI agent to run it reliably are two different skills. This module covers how to structure the prompts and workflows that keep the agent on track through a multi-step RM analysis, how to recognize when the agent is producing a confident-sounding answer that is misaligned with your hotel's actual data structure, how to intervene and correct it without restarting the entire session, and how to build the checkpoints and validation steps that make your weekly RM workflow something you can hand off to the agent with confidence. The agent does not have your market knowledge or your experience reading your property's booking patterns. You do. This module is about how those two things work together reliably.

You will build a personal framework for directing the AI agent through your weekly hotel RM workflow, including the correction prompts, validation checkpoints, and output standards that keep every analysis grounded in your property's real data and your own judgment.

Reporting and Defensibility

A hotel RM recommendation that you cannot explain under pressure is not a recommendation, it is a guess you got attached to. This module covers how to build a RM report that communicates your pickup position, demand forecast, pricing rationale, and competitive context in a format your GM or ownership group can follow without a tutorial. It covers how to quantify the uncertainty in your forecast honestly, how to present the pricing decision with the analysis behind it rather than just the rate recommendation, how to handle a pushback from ownership on a decision you are confident in, and how to document the reasoning so next week's numbers tell the story of last week's decision. The goal is a reporting workflow that makes your analysis auditable, your reasoning transparent, and your credibility consistent over time.

You will build a weekly RM report that runs automatically from your live data, communicates your forecast and pricing strategy in a format built for your specific stakeholders, and creates a documented record of the reasoning behind every rate decision you make.

The distinction

Pasting a pace report into an AI chat tool is not a hotel forecasting system.

It is a one-time export. You get an answer. You close the tab. Next Monday you paste the new pace report and start over. Nothing is connected, nothing persists, nothing runs without you.

This course builds the other thing: a hotel forecasting system wired to your PMS and Excel data, so the pickup and pace analysis is always there, always current, and always yours to direct.

Chat-based — every session

YOU Export data from your system

YOU Paste it into the chat window

YOU Re-explain your business context

YOU Re-prompt when the model loses direction

→ Answer. Discarded. Start over next week.

Connected — set up once

YOU ONCE Wire your tools via MCP

YOU ONCE Build your data ontology

YOU ONCE Define your forecasting workflow

AUTO Reads live data. Runs the workflow. Delivers output.

↻ Runs again on live data, any time you ask.

Every piece of the right diagram is something you assemble yourself, on your own data, with no code required.

What Makes This Course Different

4 Sessions Included

This is not a course where you watch videos and hope the pieces fall into place. Every student gets 4 private 60-minute sessions with Robert to work through the material on their own data, apply every technique to their own forecasting system, and get real answers to real business questions. Additional sessions are available at $200/hour.

Stuck on a concept?

Book a session and Robert walks you through it on your own data until it clicks. No time limits, no ticketing system.

Not sure which model fits your problem?

Bring your actual business situation. Robert helps you select the right algorithm, run it, and interpret the output.

Want to apply this to your own data?

That is the entire point. Every technique in this course gets applied to your specific business data in your personal sessions.

Sessions cover course concepts and applying the workflow to your own data. Not done-for-you consulting.

Student results

6,000+ analysts. Here is what they say.

★★★★★

"This course was a great learning experience — well-structured, short videos, easy to study at your own pace. The SQL and Excel content are extremely useful and I will definitely be applying much of this in my work in business intelligence."

JBJulia BaunemannBusiness Intelligence

★★★★★

"Robert took me step-by-step into understanding the how and the why of every process. Now I can understand my demand patterns and optimize prices based on real information. I discovered the beauty of Data Science through these courses."

YEYassir EL BASSIMAnalytics Professional

★★★★★

"I wish I had done this many years ago — it would have helped so much during my career as an analytics leader. This course provides a great tool to learn analytics from how to retrieve data all the way to making pricing decisions and creating forecasts."

RDRozsa DimandoAnalytics Leader

★★★★★

"I cannot begin to tell you the value of this course. It provided the tools to be mathematically specific in what I ask our reporting departments to do. Understanding the SQL reporting capabilities was golden."

LCLisa CullyAnalytics Director

★★★★★

"Robert was able to break complex material into small, easy-to-consume explanations. I know the value of myself and my company have vastly improved with the completion of this course."

BGBryan GatzemeyerBusiness Professional

★★★★★

"These courses have shed new light on how I can improve my Excel workbooks. It is quite obvious you are what analytics needs to be and I look forward to modeling myself in these practices."

MGMark GrossmanIndependent Hotel Manager

★★★★★

"Having been through a number of analytics courses including one from Cornell, yours really explains and shows the calculations behind the systems. Your concept of looking at individual transactions opened a whole new world for me."

RHRonald HopmanAnalytics Professional

★★★★★

"Though I have finished the Cornell Advanced Analytics certification, I felt your course is something I should have learned earlier."

APAbhijeet P.kCertified Analytics Professional

★★★★★

"The presentations are expertly done, presenting difficult mathematical concepts in simple language. Your concept of looking at individual transactions opened a whole new world for me."

IDIvan R. DrechslerAnalytics Professional

★★★★★

"The body of knowledge is the true science of analytics. These skills will equip you with the confidence and wisdom you need to apply analytics concepts."

RARonald AlliAnalytics Professional

★★★★★

"I've taken many other analytics courses but... if you are serious about analytics, you have to take this course."

CPConstantino PapadopulosAnalytics Professional

★★★★★

"This is the best analytics course I have ever taken."

NTNikolaos TsitsoulisAnalytics Professional

Enrollment

Build the hotel forecasting system your property actually needs.

100% Money-back Guarantee.
Real hotel data: PMS exports, POS data, and Excel files throughout.
Lifetime access and all future course updates.

Meet Your Instructor

Robert Hernandez

I am Robert Hernandez, and I am committed to helping you learn everything I know, without wasting your time on purely academic skills that do not translate into real-world value. I bring a rare combination of cross-disciplinary experience, advanced mathematical and analytics skills, technical competency, multi-industry knowledge, and business process improvement expertise. I started my career in FP&A and am an energetic and dedicated analytics professional with strong business acumen and more than 20 years of experience creating and managing data-driven models and processes for diverse organizations, both on-site and remotely. I have worked at Walt Disney and HP/Compaq, and have consulted for dozens of companies across industries, from e-commerce to entertainment to energy.

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Have a Question about this course? Email me.

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