Hotels: Data -Driven Evolution

May 13, 2019 0 comments

Unlike many industries, the primary focus and most important KPI for Hotels is customer experience. If a customer has one bad experience they will move to another brand. High competition with low switching cost makes this a big area of concern for hotels.

The bar for expectations from a hotel is high as the internet and portals like TripAdvisor make it extremely convenient for consumers to compare hotels in terms of facilities and services.

There are various touchpoints for a customer from booking to post stay reviews and the experience at each of these is important. Data helps hotels strategically plan to increase guests’ experience and also to create personalized and effective marketing communications.

There is a rich reservoir of customer data available to hotels from transactional data for all stages of the customer journey to third party data (for instance, event calendars for those driving sales).

The key to success is being able to look at all the data and estimate and focus on Customer Lifetime Value (CLTV). Also, finding what would be a more compelling proposition for a high lifetime value customer to make repeated bookings.  

Additionally, data enables Hotels to be better at the other two goals (along with Elevating Customer Experience) that are important to any business i.e. Increase Revenue and Reduce Costs. Here’s how this is being done in the industry.

 

Elevate Customer Experience

Data such as likes/dislikes on Social, and Guest Surveys helps Hoteliers to do Sentiment Analysis. Guest Surveys help understand Behavioural Motivators – information on how guests make their booking decisions and why they return.

Denihan Group used Facebook and Guest Profile data to uncover various comments on what guests wanted in their rooms and restructured rooms accordingly. They found that guests were looking for Flexible Spaces that may be used for a variety of different needs. Hence, they incorporated a workspace, relaxation space and a sleep zone in rooms. More storage and kitchenettes were added for families.

Denihan has also placed analytics in the hands of front-line staff. They look at dashboards to anticipate what a particular guest desires- restaurant meals or excursions to local places. Housekeeping staff can also know which room needs an extra pillow and who will order a sandwich at 2am. Transactional customer data along with unstructured data from sites like TripAdvisor is combined to gain this understanding.

 

Increase Revenue

There are 2 areas that enable Hotels to Increase Revenue directly. One is Better Demand Forecasting and the other is Yield Management.

Better Forecasting is enabled by Time Trend analysis which helps hotels to more accurately forecast seasonal events, understand booking behaviors and also predict cancellation rates.

Red Roof Inn used this type of analysis which resulted in about a 10% increase in revenue. They realized that flights were getting cancelled in certain areas as they were facing a record winter. Close to 90,000 passengers were being left stranded at the airports each day.  Their hotels are placed near airports. Hence, their Marketing and Analytics Teams used Public Datasets on weather conditions and flight cancellations to launch a targeted marketing campaign for mobile users in affected areas

Data also enables hotels to do better Yield Management which in hotel terminology signifies ‘The Right Room at the Right Price’, extended to be offered to the Right Guest at the Right Time. This is optimized by taking into account the peaks and troughs in demand through the year as well as other factors such as weather and events. Yield Management can impact the number and type of guests checking in. Different data sources such as Yelp, TripAdvisor, Social Media and CRM together help signify the right price value equation.

For instance, Denihan Group, which is a privately-held hotels group in North America equips its revenue management team with reports at the start of the day that help them predict:

•  What type of business in going to be booked?

•  How much in advance?

•  At what kind of rate?

•  Through which channel?

•  In what segment?

•  For what length of stay?

This helped them charge 200% of competitor rates during a high demand period.

 

Reduce Costs

Big Data can be used for managing various costs for hotels. Occupancy Rates are forecast which helps minimize under/over staffing, helps save on utility costs and plan renovations for off peak times.

Analytics gives reports which tell hoteliers all info about guests, patterns of business & predicted usage. It also helps Sales Teams understand

•  What Channel business comes through?

•  What are the most profitable channels?

•  And how they can encourage guests to book through channels which helps hotels serve them better as well as are good for the bottom line

Denihan Group made a productivity saving of 40% using such predictions

The Marriott Group Pricing Optimizer tool also helps reduce costs by enabling a faster response time; quick, finely tuned rates for multiple dates and hotels and providing a range for price negotiation. It also suggests alternate dates or hotels easily in case of unavailability.

An additional goal for hotels and in which data is helping them is better Marketing Effectiveness. This contributes indirectly to all the three goals which in turn helps in increasing customer lifetime value and catering better to customers with a high CLTV.

The core of better Marketing effectiveness is make it as personal as possible and sway purchase decision. This can be done by processing individual data through the lens of data analytics. Instances of the same are as follows:

•  A complimentary visit to the spa for a customer who goes to the spa every time

•  Denihan reached high potential/ High LTV guests and similar people who are not guests yet

Big Data Analytics also helps make a distinction between a one- time big spender and a frugal business traveler who comes again and again and hence has a greater LTV

Denihan used this for winning back high LTV guests. They received a 300% ROI from the program.

A/B Testing can also help in making marketing more effective by fine tuning the landing page experience and other areas of their website. This helps hotels compete with Online Travel Agencies (OTAs) which are a complimentary yet competitor service.

Data therefore plays a key role for hotels to not only better themselves but also achieve their objectives in this competitive landscape.

 

Author

Sonal is currently working as Senior Associate, Marketing Strategy & Analysis at Publicis Sapient. Her moto is to help customers get creative and build value through data analysis to building strategies for growth. In her career, she has transitioned from New Product Development at a leading FMCG to building a brand of her own to being a Data Analyst. Extremely passionate about marketing and the science of backing decisions with data.

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