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Hotel industry sentiment analytics


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Sentiment Analysis and Text Mining over Hotel's guests ferdbacks in TripAdvisor.

Published in: Data & Analytics
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Hotel industry sentiment analytics

  1. 1. Sentiment Analytics HOTEL INDUSTRY
  2. 2. Text Mining/SA for the Hotel Industry • With the availability of huge volumes of text-based information freely available on the Internet, text mining can be used by hoteliers to develop competitive and strategic intelligence. • Accurate and timely competitor and customer intelligence enhances hotel effectiveness and customer satisfaction • Similar to data mining, text mining explores data in text files to establish valuable patterns and rules that indicate trends and significant features about specific topics
  3. 3. Traditional BI vs New Analytics approach 0 10 20 30 40 50 60 70 80 90 100 Hotel Chain I Hotel Chain II Hotel Chain III Hotel Chain IV Traditional analytics Sentiment Analysis Revenue change %
  4. 4. Concept of Sentiment Anlysis • environmental scanning of customer intelligence by analyzing digital portals like TripAdvisor • acquiring customer intelligence by analyzing social media • 3improving efficiency of internal knowledge management by analyzing internal data Importance Volume Trip Advisor 75 83 Travel Portals 15 10 Social Media 10 7
  5. 5. Sentiment Analytics process • Data flow architecture • Data load from defined sources Extracting data E • Transform data • Add business logic Transforming dataT • Set Analytics goal • Define KPI and Rapporting env. Loading to EDW L
  7. 7. Making external data familiar DS: TRIP ADVISOR DATA SENTIMENT ATTRIBUTES Trip Advisor review content Trip Advisor sentiment
  8. 8. ETL framework Extracting data Transforming and cleaning Structure for un-structured data Loading in EDW Build OLAP onTop Automate the process
  9. 9. Front End Solution – Reviews on TA
  10. 10. Front End Solution – Sentiment Analytics
  11. 11. Front End Solution – Customer Surveys
  12. 12. Business Value of Sentiment Analytics – Organisation perspective The hospitality and restaurant industries also benefit greatly from using text analytics to listen to the conversation. Much of the customer feedback for hotels, resorts, and restaurants takes place outside of the customer-company conversation (ex:TripAdvisor). Reviews can be placed on a plethora of websites, forcing companies to manually seek out and interpret the conversation. With automated text analytics tools, a hotel can quickly and easily assess whether they should be spending money on new linens or pool improvements. Text analytics can be used to develop a better understanding of the likes, dislikes and motivations of the customer. Changing loyalty program incentives to match customers’ desires can improve customer loyalty and increase sales. There are many other examples, and the uses of text analytics to listen to the conversation are essentially limitless. And, there is significant value in listening to the conversation. The conversation is immediate – people are talking in the moment they have an experience, in the moment they interact with the brand or the company. They are having conversations to try and figure out which brands they trust and want to have as part of their lives. While sales are a lagging indicator, discussions are a leading indicator.
  13. 13. Business Value of Sentiment Analytics – Customer perspective Humans are subjective creatures and opinions are important. Being able to interact with people on that level has many advantages for information systems.
  14. 14. Besim Ismaili Data Scientist,CIO of BeyondIT
  15. 15. Tom Olaf Hammervold CEO of BeyondIT