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May 23, 2018June 29, 2021Nedyalko Kostadinov

Big Data Analytics: Customer journey analytics in the hospitality industry

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Top performers utilize their company’s data to its fullest potential – and that’s what differentiates them from the rest. The hospitality and leisure industry is well
positioned to grasp the benefits of data analytics, leading to improvements in customer satisfaction and retention, ultimately benefitting both the industry and the clients it serves.

TABLE OF CONTENTS

  • Hotel Yield Management >
  • Companies can enrich the datasets they use >
  • The Client Challenge >
  • Our Approach >
  • Deliverables >

Identifying which variables from your data drive satisfaction and lifetime value can help understand customers better and identify priority products or services on a customer segment or even individual customer level.

Hotel Yield Management 

Knowing when and how to price and offer your rooms is a becoming more and more crucial in the age of mobile. Customers can easily flick through hundreds of hotels in an area before making their choice, comparing what they offer for a specific price point. Understanding the optimal price of each rooms depends on many factors. For example, a small hotel room in Kiev might cost 60 EUR per night, but for the night of the Champions League final, the same hotel is charging around 9000 EUR. Yield management relies much more on external data to understand what would drive hotel demand up, and when to trigger an optimal pricing strategy and marketing campaign, which would result in the highest possible revenue.

Companies can enrich the datasets they use

Transactional data helps you identify spending trends in customers, such as time periods when spending is highest, group sizes which spend the most on extra services, etc. This type of data is already readily available in most companies billing systems and can provide a starting point for basic insights.

Demographic data allows you to segment your customers based on common characteristics. At a very bare level, this would include country of residence, age, gender, size of group. The granular the analysis, the better you can use it to target the relevant groups. Customer experience data, traditionally obtained from primary research on customer satisfaction and other relevant KPIs, helps you understand your strengths and weaknesses, and customer preference trends.

Many companies struggle to unlock these different data sources, due to technical or structural issues. We at GemSeek can enrich a company’s database through web scraping and text analytics. For hotels, this would mean gathering data from multiple review sites, and extracting key topics people talk about, along with basic demographics and time periods. This helps us link back the data to the transactional records to unlock actionable insights and offer a complete view of the customer journey.

Unlocking insights from data in the hospitality industry improves the customer journey from start to end – and increases revenue along the way.

Hotel Chain Red Roof Inn are amongst the first to implement analytics in hotel management. During the harsh winter of 2013/14, they realized that they could use
their strategic location close to airports to their advantage. Analysing publicly available data on weather conditions and flight cancellations, they launched a targeted marketing campaign aimed at mobile users in the areas most likely to be affected, leading to a whopping 10% increase in business in targeted areas.

Hospitality data can also be used by non-hospitality companies working with travel and leisure B2B customers to understand how to target their offerings. At GemSeek, we specialize at enriching datasets and identifying trends, which would allow you to utilize your data to its fullest potential.

The Client Challenge

Our client, a global telco leader, was looking to maximize upsell potential with clients in the travel & leisure space. Existing data on clients & prospects in this space was scarce & unstructured.

Our Approach

Our team collected & cleansed all internal CX, transactional & billing data. As a next step, we augmented the database through web scraping of relevant customer account information – type (hotel, restaurant, golf club, etc.) locations, facilities, star ratings, incl. ratings & reviews from travel websites (Booking, TripAdvisor, etc.). This information was fed into a predictive model based on micro-segmentation and propensity scoring which prioritized leads and provided insights on which bundles would be most attractive for each specific lead.

Deliverables

We provided our client with a user friendly hands-on dashboard linked to the analytical model and the database which was directly integrated with their Salesforce. This allowed sales people to have easy access to all necessary information when prioritizing and targeting leads and greatly improved sales rep’s success rates and overall ROI of the sales initiatives in travel & leisure B2B customers

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