Weekly Insights. April 25, 2026

What can hotels do to decrease their cancellation rates?

Hotel customer journey: The guest experience guide

The article is a full walkthrough of the hotel customer journey from inspiration and research to booking, check-in, in-stay experience, and post-stay follow-up, with a strong focus on how that journey is changing because of social media, AI, self-service tech, personalization, direct booking strategy, guest messaging, reviews, and ancillary revenue, so it is most useful if you want a broad guest experience overview rather than a narrow how-to on one specific stage.

The AI funnel is broken. The key to fixing it lies in the consideration phase

The article looks at why AI is already strong at the discovery stage of travel planning but still weak in the consideration stage where travelers need exact, trustworthy answers before booking, then explains why that gap is slowing real booking impact, explores the role of structured data, MCP, apps, and automatic source discovery, compares ChatGPT and Google’s starting positions, and argues that the next battle in hotel distribution will be won not by whoever is most visible in AI, but by whoever is most verifiable.

The most common revenue management mistakes hotels still make

The article is a rundown of the revenue management mistakes hotels still make, including pricing too heavily off last year’s numbers, failing to update forecasts, holding rate when demand is no longer there, misusing comp set data, ignoring cancellation patterns, treating all midweek nights the same, missing early warning signs in the business mix, and leaving revenue management as a part time task instead of a structured discipline, so it is mainly useful as a diagnostic checklist for spotting weak points in an existing strategy.

OTB (on the books) in hotels: what it means and how to use it for pricing

The article is a practical guide to OTB, explaining what on the books data actually means, how hotels use it to track future occupancy and room revenue, why it matters for pricing and forecasting, how to read booking pace and pickup, how to connect rates with occupancy trends, and how market level OTB benchmarking adds context by showing whether your hotel is outperforming or lagging the wider market, so it is most useful as a solid primer for someone who wants to sharpen forecasting and pricing decisions.

Instagram drives demand. Now it’s time to drive direct bookings

The article looks at Instagram not as a branding channel but as part of the hotel booking funnel, arguing that many hotels already generate demand there but lose the booking because the handoff to the website or booking engine is weak, then covering how Instagram now influences the decision phase, where hotels create friction, what stronger profiles and more decision-oriented content look like, how to improve discovery and mobile booking flow, and which commercial metrics matter if you want to know whether Instagram is actually driving direct revenue rather than just engagement.

ChatGPT Hotel Ads: They're here and OTAs already have first-mover advantage

The article is about the arrival of hotel ads in ChatGPT and why that matters for distribution, explaining how AI search compresses the traditional hotel booking funnel into a tiny shortlist of only a few properties, why OTAs currently have a head start because of stronger data visibility, what makes ChatGPT ads different from Google Hotel Ads, why organic presence across OTAs, reviews, and business listings matters more than paid spend for now, and what hotels should do immediately to improve their chances of showing up in AI driven recommendations before the ad product fully opens up.

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