White Capers opens up new dimensions into the decision making process of the travel & hospitality industry by providing a data driven framework. Actionable insights are provided to marketers to measure and maximize every customer interaction in the travel & hospitality domain. This helps very much in reducing operational costs, in increasing revenues, and improving customer satisfaction levels. Our strength in predictive modeling gives us that extra edge in predicting behaviours that matter and eventually gaining from the customer's experience to lead a favourable outcome.
Using data from multiple sources – customer profile data, transactional data, customer support data, and data related to the various SKUs we work on finding relationships amongst customer behaviours and brand activities. Insights into the changing dynamics of a purchase appetite, brand/SKU association behaviour helps very much in channelizing the marketing efforts of the company. Thus, Travel & Hospitality Data Analytics utilize the historical data to make an impact on the future customer's buying tendencies.
Customer Acquisition Effectiveness: The world on the internet is growing at an immeasurable pace, and customers want to be heard, liked, and offered what they are looking for. Setting up multilevel inbound marketing channels allows the travel industry to acquire new customers at an optimal cost.
Our service offerings include designing keyword campaigns in a way that builds over and above the standard keyword selection practices. This advanced 'data driven' technique uses our own developed monitors and dashboards to scan the historical keyword performances and predict the upcoming trend hence extracting the maximum benefit possible from favourable keywords. Keyword Analytics, as it is called, allows a company to track costs and align practices with the tactical decisions of the company.
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Customer Response Modeling: Statistical Modeling uses customer demographics, behavioural data, and preferences to predict the propensity of prospects in responding favourably to:
Specifically, advanced analytics in Travel & Hospitality gives us the comfort to understand answers to the following questions:
Clustering & Segmentation: Our solutions help categorize Customer Segmentation Schemes to differentiate between potential profitable and unprofitable customers by studying needs, attitudes, behaviours and demographics. Analytical techniques like Recency, Frequency, and Monetary Value (RFM) Analysis are used to assess customer lifetime value and help estimate the profitability and revenue potential of various customer segments. Statistical Simulations are built around the customer segments and their predicted propensities to attract other customers and provide personalized service based on their needs and preferences.
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Cross-Selling: Cross-Selling & Up-selling techniques are the quickest ways to capitalize on the existing customers by marketing additional products and services to existing customers. Purchase data when combined with the customer profile gives a powerful way to predict the likely customers who are prone to buy additional products from the company. The Cross-Sell and Up-sell behaviour of the customers from the historical data is extensively studied to measure the tendencies that result into a selling, and using that as a benchmark the new unexplored customer base is ranked for their probabilities of buying additional products and at favourable discounts only allowing into more sales.
Advanced Data Analytics - Yield Management: Travel & Hospitality industry faces urgent needs of balancing premium and leisure customers and companies need to work out booking limits and protection levels to make a profit juggling between the ever-changing revenues and costs. When the future demand is uncertain & the excess resources are expensive to bear, strategic ways to handle price discrimination play a pivotal role in the profit making of the business keeping the utilization as high as possible. Yield Management solutions work excellently well by predicting the cumulative probabilities of utilizing full capacities for given period of time. 'Expected Marginal Seat Revenues' and 'Overbooking' techniques, if carefully worked out considering variability and mobility of capacities, come into the favour of the company and bring excellent results.
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"Started with one assignment, they satisfy all my analytics needs. Good quality, cost effective - Our godsend analysis partner we much needed."
Director, E-commerce company, UK
