Sentiment AnalyticsHOTEL INDUSTRY

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

Traditional BI vs New Analytics approach

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Traditional analytics Sentiment Analysis Revenue change %

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

Sentiment Analytics process

• Data flow architecture

• Data load from defined sourcesExtracting

data E

• Transform data

• Add business logic

Transforming data T • Set

Analytics goal

• Define KPI and Rapporting env.

Loading to EDW L

Web scraping techniquePYTHON SCRIPT TO SCRAP DATA FROM TRIP ADVISOR

Making external data familiarDS: TRIP ADVISOR DATA SENTIMENT ATTRIBUTES

Trip Advisor review content

Trip Advisor sentiment

ETL framework

Extracting dataTransforming and cleaningStructure for un-structured dataLoading in EDWBuild OLAP on TopAutomate the process

Front End Solution – Reviews on TA

Front End Solution – Sentiment Analytics

Front End Solution – Customer Surveys

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 – peopleare 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.

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.

Besim IsmailiData Scientist, CIO of BeyondIT

Tom Olaf HammervoldCEO of BeyondIT