In the contemporary landscape of hospitality industry, data-driven decision-making has emerged as a pivotal tool for maximising profitability and elevating guest satisfaction in hotels.
NB: This is an article from Aro Digital
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With advancement of data analytics technologies, hoteliers can now harness vast pools of data to gain insights and make informed strategic choices while drive direct revenue growth.
Let’s dive deeper into how data analytics revolutionises various aspects of hotel industry, particularly focusing on revenue optimisation and guest experience enhancement.
UNDERSTANDING CUSTOMER BEHAVIOUR:
The use of data analytics empowers hotels to learn more about customer preferences, booking patterns, and customer behaviours.
By analysing past bookings, website interactions, feedback, and demographic information, hotels can gain invaluable insights for informed decision making.
These insights aid in understanding booking patterns, tailoring offerings to meet specific needs, identifying distinct customer segments, and maximising customer lifetime value.
With specific information on customer behaviour, hotels can create their offerings and promotions exclusively customised for their audience segments.
COMPETITIVE BENCHMARKING:
Analysing competitor pricing, market demand, and trends is imperative for hotels to stay ahead in the game.
Comparative pricing analysis, understanding market demand trends, and assessing competitors’ strengths and weaknesses enable hotels to differentiate their offerings effectively and target specific market segments.
With information on competitor information, hotels can access their offerings and make informed decisions on their packages and promotions.
FORECASTING DEMAND:
Accurate demand forecasting is key to optimising pricing and rooms inventory management.
By analysing historical data, booking trends, and external factors like major events or seasons, hotels can predict future demand accurately.
Hotels can leverage advanced forecasting models allowing for precise optimisation of room rates and inventory allocation to maximise revenue.
With demand forecasting, hotels can also allocate premium rooms for upgrades to special guests and manage the standard room inventory accordingly.
PERSONALISED PRICING:
Data analytics facilitates the implementation of dynamic pricing strategies for hotels based on various factors such as time of booking, room type, booking season and customer segments.
Dynamic pricing algorithms, segment-specific pricing, and customised packages enhance the guest experience and increase the likelihood of conversion and repeat bookings.
For example, with dynamic pricing, a room that is £200 two months before the actual date of arrival, could potentially be £350, a week before the said date depending on the demand.
Hence, dynamic pricing involves real-time adjustments of room rates in response to changes in demand, competition, and market variables.
By leveraging data analytics tools, hotels can set optimal prices that maximise revenue while maintaining competitiveness.
