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Tourism Intelligence Platform
Datactif® Athena
Knowledge is not only vital for the enterprise profitability but integral part
of its core business process no matter the ...
Contact UsDIRECTING Intelligence
DATACTIF Athena Big Data Analytics is an open
architecture system, based on Artificial Intelligence (neural
networks, fuzz...
Today an enterprise is evolving into a complex economic, social and
business environment, co existing with suppliers, prod...
Tourism Ecosystem
Tourism products and services attract travelers to a country. Cultural
and natural attractions, beaches ...
Data from all Specialized Tourist Sites
Reputation. Rating Index
Rating Index of each Hotel, is based on ratings
made by travelers in specialized sites such as
Tr...
Terms extraction discovers attributes from
comments that travelers wrote about an hotel in
the specialized sites.
In the c...
Sentiment Analysis retrieves user reviews in the
specialized sites (Trip Advisor, Booking, Expedia,
etc..) and lists them ...
Data from Social Media
In the case of Social Media, we analyze not only each enterprise official FB, Twitter or Instagram
...
Why Face Book is more important than Trip
Advisors and other sites.
Because travelers express their sentiment about
their ...
Sentiment Analysis that retrieves user reviews
on Face Book reveals a gap between Face Book
evaluation and Trip Advisor on...
Influencers identification is the number one objective
in every social media as specific users exercise
influence over an ...
Face Book. Luxury Hotel. Influence Analysis
Influencers identification in the Face Book page of
the “Luxury Hotel” shows t...
Data from Booking Systems
Clustering allows to discover, groups (clusters)
of users with common characteristics. Data used
are consumer-tourist atti...
Booking System. Prediction
Based on booking systems historical data and
Face book trends, we can predict arrivals by
natio...
Booking System. Prediction
Prediction is updated each month based on real
bookings and arrivals, but also comments on
Face...
Corporate and social media data
Correlation between analysis created by
corporate data and Social Network analysis is
the ...
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DATACTIF_TOURISM

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DATACTIF_TOURISM

  1. 1. Tourism Intelligence Platform Datactif® Athena
  2. 2. Knowledge is not only vital for the enterprise profitability but integral part of its core business process no matter the sector of its operability. Business Intelligence as entity that process information and transforms information into knowledge, must be in the centre of Business and Technology unified conceptual and operational processes. DIRECTING INTELLIGENCE bridge the gap between business and intelligence by creating the foundations for an Intelligent, Operational, Evolutionary Enterprise Ecosystem. Aligned to each enterprise Ecosystem, DIRECTING INTELLIGENCE designs and creates adaptive, collaborative Intelligent Open Architecture Platforms based on machine learning methodology and algorithms (neural network, fuzzy systems, genetic algorithms, SVM, etc…), platforms that processes transactional data from operating systems and data from the Web, numerical as well as unstructured text data, allowing real time and on line, substantive assessment of holistic knowledge for each enterprise. DIRECTING Intelligence
  3. 3. Contact UsDIRECTING Intelligence
  4. 4. DATACTIF Athena Big Data Analytics is an open architecture system, based on Artificial Intelligence (neural networks, fuzzy logic, support vector machine, genetic algorithms, etc...) that processes aggregated data from : 1. Reservation Systems, 2. Specialized in Tourism Sites (Trip Advisor, Booking, Trivago, Expedia, etc ...) 3. Google Analytics, 4. And Social Media. DATACTIF Athena designed specially for the Tourism Industry combining Social Network Analysis and Text Mining, performs the following tasks : Data Collection from the web. Communities Detection. Influence Measurement. Sentiment Analysis Clustering. Recommender System. Polarization Analysis. Term analysis & Fact extraction. DIRECTING Intelligence in Tourism DATACTIF
  5. 5. Today an enterprise is evolving into a complex economic, social and business environment, co existing with suppliers, producers, competitors, other stakeholders and customers. Global trends of production and distribution in one hand, business dependence on technology evolution on the other (Internet of things, Cloud and Smart Systems) are leading into an era where people, machines, devices, sensors, and businesses must all be connected and be able to interact with each another. A new paradigm of doing business is necessary, the creation of an Enterprise Ecosystem that will offer an operational and profitable symbiotic relationship between an enterprise and its environment. In this context a modern Enterprise must create a business strategy development (linear model) being sensitive in same time to internal and external changes (non linear model) Business Intelligence aligned to the Enterprise Ecosystem Knowledge is not only vital for the enterprise profitability but integral part of its core business process no matter the sector of its operability. Business Intelligence as entity that process information, transforms information into knowledge, must be in the centre of Business and Technology unified conceptual and operational processes. DIRECTING since 1999 has for mission the design and creation of Big Data Analytics aligned with the business engineering of each sector and within aligned with each enterprise strategy From federation of systems to Enterprise Ecosystem
  6. 6. Tourism Ecosystem Tourism products and services attract travelers to a country. Cultural and natural attractions, beaches and resorts, sports events are all products that appeal to travelers. Within this country attributes and strategy there is destination identity and within destination every single enterprise's identity and offer. The best way to achieve a sustainable growth or retention of profitability for each enterprise is through a three-step process: analyze and understand the evolution of the tourism sector ecosystem; analyze the relation between destination and tourism sector ecosystem and develop strategic positioning and value proposition of the given enterprise aligned with the above framework. In this context Big Data Analytics has to understand each traveler needs and wishes, transform information into actions to be taken and design a business and communication guide of actions that an enterprise must undertake. For the success of this task, data coming from all sources (specialized in tourism sites, social media, booking systems) must be processed in a unified platform and analyzed with machine learning techniques as we have both transactional (numerical) data and data expressing thoughts and feelings, structured and unstructured data, data concerning the whole tourism ecosystem and data concerning the traveler's social community.
  7. 7. Data from all Specialized Tourist Sites
  8. 8. Reputation. Rating Index Rating Index of each Hotel, is based on ratings made by travelers in specialized sites such as Trip Advisor, Booking, etc…
  9. 9. Terms extraction discovers attributes from comments that travelers wrote about an hotel in the specialized sites. In the case of Santorini, we observe that travelers expect “sunset”, “honey moon atmosphere”, “perfect moments” and feel a “breathtaking” From their hotel a view from their room, etc… But also BREAKFAST ! Reputation. Terms Extraction
  10. 10. Sentiment Analysis retrieves user reviews in the specialized sites (Trip Advisor, Booking, Expedia, etc..) and lists them in Positive, Negative or Neutral Probability. Using Term analysis and Fact extraction we can identify and understand the reasons (some times unknown to an enterprise) for clients’ satisfaction and dissatisfaction. In the case of “Luxury Hotel” in Santorini we observe that “cuisine” and “view” makes disappear other attributes, as the excessive price. But the feeling of something missing from an ideal holiday creates a high neutral and negative sentiment that must be taken under consideration from the direction of the hotel Reputation. Sentiment Analysis Index
  11. 11. Data from Social Media In the case of Social Media, we analyze not only each enterprise official FB, Twitter or Instagram but also every channel, concerning the destination. Social Media of communities, of individuals, of local enterprises, in order to understand the Destination Ecosystem and realize the positioning of each enterprise in the national and local context.
  12. 12. Why Face Book is more important than Trip Advisors and other sites. Because travelers express their sentiment about their personal moments and feelings, in a more free way, sharing it with other travelers and friends. We collected data from any Face Book page concerning Santorini (communities, individuals, professional, etc…) and as we can see terms that appears are not only “staff”, “service”, “view’ but also psychological expectation such as “romantic”, “need to love this place and love in general”, “need to live a special moment”. And this is the Unique Selling Proposition of the destination as well as of each Hotel Face Book. Destination. Terms Extraction
  13. 13. Sentiment Analysis that retrieves user reviews on Face Book reveals a gap between Face Book evaluation and Trip Advisor one. The deep meaning is that each hotel in Santorini must find the balance between professionalism and personalized “amateur” behavior Face Book. Destination. Sentiment Analysis
  14. 14. Influencers identification is the number one objective in every social media as specific users exercise influence over an organization and its potential customers. Influencers are activists, well-connected, have impact, have active minds, and are trendsetters, though this set of attributes is aligned specifically to consumer markets. Targeting influencers, is seen as a means of amplifying marketing messages in order to counteract the growing tendency of prospective customers to ignore traditional marketing efforts. Example of INFLUENCE ANALYSIS & RECOMMENDER SYSTEM for Santorini based on Face Book. We see that despite of the thousands of photos with “sunset” that are everywhere, Influencers and mostly Asian-Chinese travelers propose culture ! Face Book. Destination. Influence Analysis
  15. 15. Face Book. Luxury Hotel. Influence Analysis Influencers identification in the Face Book page of the “Luxury Hotel” shows that its target group contains more French people that Santorini average. Nationalities in general are very important to business strategy of an hotel and as we will see in the following pages, combined with booking system information helps to increase profitability
  16. 16. Data from Booking Systems
  17. 17. Clustering allows to discover, groups (clusters) of users with common characteristics. Data used are consumer-tourist attitudes, preferences and life style data from sources such as booking systems and Face Book. There are 4 distinct Hyper Clusters : 1. Sentimental, 2. Experience Destination, 3. Planners, 4. Time Relatives Those Groups constitute the GRAF model. Why they are important. Because each group has specific requirements, standards, expectations (from the composition of breakfast, up activities based on which choice hotel) and definitions as to what is "romantic", "luxury", "original" etc. ... Understanding the composition of travelers concerning a destination first and then for a specific hotel and being able to predict the composition for next season is of a highly importance in the efficient design of the marketing mix and business plan of each enterprise focusing on next season. Booking System. Clustering
  18. 18. Booking System. Prediction Based on booking systems historical data and Face book trends, we can predict arrivals by nationality and booking month for a destination and within a destination for a given Hotel
  19. 19. Booking System. Prediction Prediction is updated each month based on real bookings and arrivals, but also comments on Face book, mostly on those comments making reference to future plans of holidays (destination, month, etc…) allowing this way to an hotel business and marketing strategy efficient implementation (SEO optimization, price and promotion policy, etc…)
  20. 20. Corporate and social media data Correlation between analysis created by corporate data and Social Network analysis is the holly grail for all Big Data Analytics. DATACTIF® Big Data Suite of Analytics and DATACTIF®Soneta, creates the bridge between those two worlds. As result, we have a full profile for clients and prospects increasing this way business strategy effectiveness. We obtain also the enrichment of transactional data with the necessary qualitative information, that no other research can offer. Through historical holistic information on customers evolution, we can measure the efficiency of each enterprise strategy and predict with high accuracy results of future actions.

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