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Forecasting for the hospitality industry

Cloudbeds

Hotel forecasting is a critical component of successful hotel management, serving as the foundation for strategic decision-making and operational efficiency. For hotel managers and the industry as a whole, accurate forecasting is not just beneficial—it’s essential for maintaining competitiveness and profitability in a dynamic market.

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Understanding ARI: A key metric in hotel management

Cloudbeds

The average rate index (ARI) is a metric that allows hoteliers to evaluate the performance of their room rates relative to a group of competitors during a specific period. Another metric to look at is the fair market share, obtained by dividing the hotel’s available rooms by the competitors’ available rooms.

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Navigating Online Bookings and Digital Marketing: A Guide for Accommodation Providers

STAAH

Data-Driven Pricing Strategies Dynamic Pricing: Implement dynamic pricing strategies to adjust room rates based on demand, competitor rates, and market conditions. Use data analytics to forecast demand and set competitive prices that attract budget-conscious travelers without compromising revenue.

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Hotel rate shopping: How to use rate shopper software

SiteMinder

Rate shopping your hotel competitor rates gives you the opportunity to: Optimise pricing: Understanding competitor pricing helps you set competitive rates, maximising revenue without sacrificing occupancy. Identify pricing gaps: You’ll be able to spot chances to increase rates without losing market share.

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Hotel Star Reports: What are they and how to read them

SiteMinder

The company is the recognised leader in hotel industry benchmarking and provides market data including supply and demand and market share information on a global scale. For example, STR data reveals that the average occupancy rate across US hotels in August 2022 was 66.5%, and the average daily rate was US$151.49.

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The role of data analytics in optimizing hotel operations

Cloudbeds

Revenue managers, leveraging artificial intelligence (AI) and machine learning (ML) combine external data like market demand and competitor activity with internal data like historical performance and future demand to guide dynamic pricing decisions, inventory controls, promotions, and demand forecasting. Revenue management KPIs.

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What is a SWOT analysis of a Hotel?

Catala Consulting

A few metrics to include in your SWOT analysis include: Average daily rate Sales circle length Event Activity Web traffic percentage of direct bookings Percentage of occupancy Revenue per available room Customer feedback, comments on social media, online reviews, and feedback.

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