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Rentlio BI – A Guide to Reading Data and Driving Business Decisions

Ana Begušić avatar
Written by Ana Begušić
Updated over 3 weeks ago

In today’s highly competitive hospitality market, understanding and leveraging data is no longer optional—it’s essential.

This guide provides a clear framework for using Rentlio Business Intelligence tools to monitor key metrics, gain actionable insights, and optimize your hotel’s performance.

Key Metrics to Know

RNS (Room Nights Sold) - Number of rooms sold in a given period.

  • Indicates hotel occupancy volume and sales performance.

ADR (Average Daily Rate) - Total accommodation revenue ÷ number of rooms sold.

  • Reflects the average price achieved per room.

Occupancy - Number of rooms sold ÷ total number of rooms.

  • A core indicator of capacity utilization.

RevPAR (Revenue per Available Room) - Total accommodation revenue ÷ total number of rooms.

  • The most comprehensive metric for overall hotel performance, combining both occupancy and ADR.

Revenue

Net Revenue: Total accommodation revenue excluding taxes and additional services.

Gross Revenue: Total accommodation revenue including all taxes and services.


Data Display Methods

OTB (On the Books): All reservations (confirmed, provisional, in-house, and checked-out).

Actuals: Only completed (checked-out) reservations.

SPIT (Same Point in Time): Comparison with the same date in the previous year.


Daily Pick-Up: Your Daily Compass

What is Daily Pick-Up?

Daily Pick-Up tracks day-to-day changes in bookings and revenue. It shows how many new reservations were "picked up".


Key Insights

  • Positive pick-up isn’t always positive news.

    • Example: +12 rooms may look good, but an SPIT comparison (–37% YoY) could indicate a serious decline.

  • Historical context matters.

    • Without year-over-year comparison, conclusions may be misleading.


How to Use Daily Pick-Up Data

  • Monitor trends over weeks and months, not just single days.

  • Act immediately on significant negative deviations (e.g., >20%).

  • Apply corrective measures when SPIT signals a slowdown.

  • Analyze performance by unit type to support portfolio optimization.


Why This Matters

Not all room types perform equally. Daily Pick-Up analysis helps you:

  • Identify the most profitable categories.

  • Plan renovations and conversions effectively.

  • Adjust pricing strategies with precision.


Practical Example

  • Situation: ADR for Standard rooms declined two years in a row, while Superior rooms were consistently sold out.

  • Action: Converted 15 Standard rooms into Superior category.

  • Result: +€280,000 in additional annual revenue.


For different departments:

Revenue Management

  • Monitor RevPAR by room type.

  • Identify opportunities for rate increases.

  • Design and implement yield strategies.

Sales & Marketing

  • Determine which room types to prioritize in promotions.

  • Analyze which markets show preference for premium categories.

  • Develop upselling and cross-selling strategies.

Operations

  • Plan maintenance based on actual room utilization.

  • Optimize housekeeping schedules and resource allocation.


Market Segments: Understanding Your Guests

Key Segments to Track

  • Leisure: Individual travelers on holiday.

  • Corporate: Business travelers.

  • Groups & Events: Organized group stays, conferences, and events.

  • OTA (Online Travel Agencies): Reservations via online platforms.

  • Direct: Bookings made directly with the hotel.


Segment Strategies

Group Segment

  • Provides stable revenue with lower cancellation rates.

  • Supports long-term capacity planning for the following year.

  • Focus on driving advance bookings to secure base business.

OTA vs. Direct

  • OTA: Delivers higher booking volumes but typically at lower ADR.

  • Direct: Generates fewer bookings, but with higher ADR and better profitability.

  • Balance the mix through seasonal optimization and tailored offers.


Sales Channels: Optimizing Distribution

Channel Performance Analysis

Evaluate performance not just by ADR, but by total revenue per available room:

  • Booking.com: €80 × 90% occupancy = €72 per room

  • Direct bookings: €120 × 40% occupancy = €48 per room

Optimization Strategies

  • High Season: Limit OTA availability and prioritize direct bookings to maximize revenue and control.

  • Low Season: Leverage OTAs for volume while using direct channels to maintain margin.


Booking Pace: Predicting the Future

What Booking Pace Reveals

  • How far in advance guests typically book.

  • When peak booking periods are expected.

  • When adjustments to pricing or marketing are needed.

Key Actions Based on Pace

Negative Pace

  • Launch early booking promotions.

  • Strengthen direct booking channels.

  • Review and adjust pricing strategy.

Positive Pace

  • Evaluate opportunities for price increases.

  • Focus on yield and revenue optimization.


Analysis by Nationality: Market Diversification

What to Monitor

  • Revenue contribution by country.

  • Seasonal booking patterns by nationality.

  • Dependence on a single market (risk assessment).

Marketing:

  • Target campaigns to the most profitable markets.

Operations:

  • Plan staffing and language skills based on guest nationalities.

Sales:

  • Expand into new markets while strengthening presence in current ones.

Partner Companies (B2B):

  • Optimize collaborations with different partner types:

    • Premium clients: High ADR, stable bookings.

    • Volume clients: Lower ADR, high number of nights.

    • Growing partners: Positive SPIT variances.

Retention Strategies:

  • Offer VIP packages for premium clients.

  • Implement loyalty programs for long-term partners.

  • Diversify the partner portfolio to reduce dependence.


Rate Optimization: Maximizing Revenue

Rate Performance Analysis

  • High occupancy does not always equal profitability.

    • Example: “Deluxe Rate” at 85% occupancy but low ADR — attracts guests due to low price, but loses potential revenue.

Performance Balancing

  • Seasonal price optimization.

  • A/B testing of different rate strategies.

  • Continuous monitoring of competitor pricing.

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