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 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

Contact Us DIRECTING Intelligence

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

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

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.

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

Trip Advisor, Booking, etc…

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

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

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.

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

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

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

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

Data from Booking Systems

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

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

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…)

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.