Understanding the AI Model: Core Principals

At TakeUp, we believe smarter pricing starts with better learning.

That’s why we built an AI engine designed to go beyond assumptions—one that learns from real demand signals, adapts to your market, and helps you make pricing decisions grounded in truth, not guesswork.

Let’s break down the basics of how it works.

The Core Principle: Price Sensitivity

Price sensitivity is the missing link in most pricing strategies.

It’s the measure of how likely your potential guests are to book at one rate versus another—and it’s foundational to setting rates that optimize revenue. But here’s the catch: price sensitivity isn’t static. It changes every day, for every date, across the entire booking window.

Traditional revenue tools don’t give you visibility into this. They rely on rules, heuristics, or assumptions. TakeUp is different.

We observe real guest behavior on your booking engine—every search, every booking—and learn from it.

Understanding AI-Driven Pricing Decisions

Our AI is built to learn.

Every day, it runs thousands of micro-experiments to find out how changes in rate affect your conversion and pace. Over time, this builds a detailed map of price sensitivity for each future night.

And when demand shifts—because of events, competitor pricing, or unexpected macro factors—TakeUp adapts. It doesn’t need to know why things are changing. It just watches the “what,” and adjusts based on observed results.

That means more accurate pricing, faster reactions, and better outcomes.

What Data Are We Looking At?

TakeUp combines data sources to give you the clearest picture of demand and conversion:

• Searches on your booking engine 

• Booking behavior and pace trends

• Competitor rate movements

• Seasonality and macro shifts

And instead of relying on a fixed competitor list, TakeUp lets the data reveal which competitors are actually influencing your demand.

Why You’re Seeing What You’re Seeing

TakeUp isn’t a black box.

Inside the platform, you’ll see exactly what rates are being recommended and why. You can view your rate history, booking curve, and conversion patterns. You’ll also see how your AI is testing rates and learning from results.

And you’re always in control. You can set rate boundaries, review recommendations, and even push your own pricing hypotheses. If the market doesn’t respond well, the AI will pull things back to optimize performance.

Adapting to Demand Signals—Without Guessing

Demand changes. Constantly. That’s why TakeUp continuously learns and adjusts.

Maybe a hurricane just hit the region. Maybe a local festival was just announced. Even if you don’t know the reason for a shift, TakeUp is already measuring its impact—and testing rates to find the right response.

This feedback loop is something most revenue managers never had access to. Now you do.