Weekly Insights. August 29, 2026
Best hospitality industry articles focused on 💵revenue, 📊markets, and 🎯strategy (Aug 23 - Aug 29, 2026)
The Illusion of control in commercial leadership
Hotels often make commercial decisions according to whichever KPI is most visible to sales, revenue management, or operations rather than the total value created for the property. The article proposes evaluating decisions through an explicit hierarchy that considers revenue impact, displacement cost, and operational value when metrics conflict. It is a strong framework for moving commercial discussions away from departmental optimization toward hotel-level profitability.

Not all events created equal in terms of hotel demand, guest spend
The article argues that event attendance alone is a poor indicator of hotel opportunity. It divides event travelers into different behavioral groups and looks at how far they travel, how early they book, length of stay, willingness to pay, and who funds the trip. The framework can help revenue teams distinguish between events with genuine pricing power and those that generate substantial attendance but relatively limited hotel demand or spend.

Building a hotel Food & Beverage budget that performs
A practical eight-step framework for building 2027 hotel F&B budgets around performance rather than simply applying percentage increases to prior-year results. It covers outlet and banquet revenue opportunities, labor deployment, food and beverage costs, pricing, capital investment, guest experience, and contingency planning. The central point is that an F&B budget should connect operating decisions with revenue growth and margin protection rather than function only as an expense-control exercise.

Group Business vs Transient: What drives more profit?
The article compares group and transient business from a profitability perspective rather than just ADR or total revenue, explaining how displacement analysis should be used to decide whether a group is worth accepting, what hidden costs sit behind both group and transient demand, why group business works best as a base on softer nights but can destroy value on compressed dates, and why there is no universal “ideal mix” — the right answer depends on the specific date, demand strength, acquisition costs, wash risk, and what business would be displaced.

Hotel star rating system: How ratings are determined and what they mean
The article is a straightforward guide to hotel star ratings, explaining who assigns them, why standards differ by country, what travelers can generally expect from one through five-star properties, and how official classifications differ from guest review scores, before covering why star level affects pricing, staffing, positioning, and guest expectations and offering basic advice for hotels that want to improve both formal ratings and online reviews.

Hotel email marketing: The complete guide for hoteliers
The article is a practical guide to hotel email marketing, covering how to use automated messages across the full guest journey from booking confirmation and pre-arrival upsells to in-stay communication, post-stay reviews, and win-back campaigns, then explaining how segmentation, personalization, list building, and OTA guest recovery can turn email into a stronger direct-booking and repeat-business channel, with the bigger argument that owning the guest relationship becomes even more valuable as AI and OTAs increasingly sit between hotels and travelers.

OTAs already speak the language of AI discovery, and most hotel marketers don't
The article is essentially a glossary and strategy primer for AI-driven hotel discovery, explaining terms like GEO, AEO, Share of Model, drift, MCP, structured data, and agent directives, then tying each one back to a commercial question: whether your hotel shows up in ChatGPT, Gemini, Claude, or Perplexity, whether the information is accurate, and whether the hotel or an OTA gets cited, with the broader warning that OTAs are already building fluency and infrastructure around these concepts while many hotel marketing teams are still treating AI search as something too abstract to measure.

Follow on LinkedIn