Selection of the topic-
Text Analytics
Title-
Using text analytics to improve the hospitality experience of customers.
Key Words-
Text analytics, content categorization, sentiment analysis,
Abstract-
With advance text analytics solutions, the hotels and hospitality providers can analyze conversations on the social media and online public forums to extract valuable business insights and using the same to improve their customer’s experiences into their hotels and with their services.
Introduction-
Today’s travelers are vocal and willing to share their experiences with hotel and travel providers; they’re more apt to share their experiences online with others through means of social media like- facebook & twitter, in online review sites such as tripadvisor.com etc. From check-in process to the quality of services, their feedbacks provide valuable insights that hospitality providers can improve the guest experience with their brands, better target customers with offers and differentiate ‘emselves from the competitors in terms of products and services.
Collecting quantitative responses from the guests through surveys was the sole feedback method used by hotels and travel service providers. Of late, the trend has changed. These days, these providers recognize the value of collecting feedback through social media and other online sites. They even encourage open-ended comments in their surveys these days.
With thousands of reviews generated each day, compiling and interpreting this unstructured data manually can quickly overwhelm the resources of a hotel or travel provider. To make this process even more challenging, fake reviews also flood the sites. Research shows 48% of consumers combine social media and search engines in their buying process which in turn affects the booking behavior of other consumers. In a survey, 90% of the people said they trust the opinions of those whom they know while 70% trust recommendations of unknown users.
Literature Review-
Text analysis is analyzing the contents of large document collections using NLP techniques to extract valuable information and produce artifacts reflecting the lexical and conceptual content of these documents. The extracted information in applications which help people get value from document collections include- refining queries:-
1. Navigating through important concepts in the domain.
2. Browsing through document space.
3. Visualizing concepts and key information.
4. Presenting summaries and other documents.
5. Other knowledge management applications.

Sentiment Analysis- historically, hotels have been wary of the evolution of internet as the predominant reputation platform for measuring the guest experience. This hesitancy was rooted in the assumptions that only those guests who had negative experience would post their comments. But today, research has shown that the customer is social and is increasingly sharing their hotel experiences, both positive and negative.
Questions like- Do your customers like you? Do they prefer your competition? Are your marketing messages resonating? If so, why? If not, what are their issues?
Sentiment analysis helps hospitality providers know that the customers are thinking of their brands and offers. Knowing what the customer feels about their brand and services gives hotels a high-level view of the health of the business. Accordingly, they need to make changes to drive their business forward.

Non Sentiment Analysis-
NSA bases comments play an equally important role in customer feedback, containing valuable insights such as ideas or recommendations for new services, questions about a hotel property or intent to purchase a room.

Cross Channel Analysis-
Social media channels like twitter provide a real-time view of customer conversation; it’s important to remember that customers communicate with hotels in a variety of ways and analyzing these communications across all channels is important to have an accurate picture of the customer experience.

Automatically Discover Topics Of conversation-
Hotel property and brand managers are aware that customers are sharing their opinions and looking for recommendations in social media, on review sites, and in customer forums.
Traditional search and text analytics systems rely on building exhaustive keyword lists, while newer advanced analytics technology gives hotels and travel providers the ability to automatically discover topics of conversation as they are happening.
The threat of hotel issues and service missteps going viral, the early warning of issues and spot trends is becoming a key competitive differentiator.

Objective-
To create the user-generated content on social media, online public forums, surveys about any company, its products and competition a wealth for its business.
Hypothesis-
Null Hypothesis Testing- It states that the information extracted through social media and other sites is not true and is of no use.
Alternate Hypothesis Testing- States that the feedbacks and responses generated on the surveys, sites are true and posted by real users. They ain’t flooded by fake users or the competitors. And their responses ain’t biased.
Tools for Data Collection-
Omniture;
Google Analytics.
Conclusion-
Through the power of today’s advanced text analytics solutions, hospitality industry leaders can now conduct deep analytics and use those insights to drive key business decisions, deliver proactive services, and formulate competitive business strategies.
The key to unlocking this wealth of information lies in a deep understanding of language the ability to accurately pull out sentiment, key issues and relationship.
This report is just a small piece of analytics that the hospitality providers can engage into to achieve higher results.
References-
http://www.ait.ac.th/education/LanguageCenter/ait-writing-services/guide-book http://www.visioncritical.com/blog/5-ways-text-analytics-can-enrich-your-research http://www.attensity.com/wp-content/uploads/industry_report_hospitality.pdf