GDPR in Marketing

June 21, 2020

The General Data Protection Regulation is a Privacy Law of the European Union which comes into force on 25 May 2018.This has been in the making for years, and is to replace the last big piece of EU privacy law dating back to 1995: a period when Geo cities became common, before Twitter, before Myspace, before  even Google.Much has changed in how the internet is used for business and the role of data and data sharing in our lives, so it's time for the law to be updated. GD PR updates the Privacy Act to reflect more recent technical developments and how we use them. In some cases, it also extends these restrictions and safeguards on what can and can not be done with your personal data to organizations based outside the European Union if they handle the data collected within it.Somewhat controversial, it's a good thing, too.The GD PR also defines the rights of individuals to access and control their data

1. The right to be notified

2. The right to Access 

3. The right to correction

4. The right to erase

5. Right of limitation of processing

6. Right to probability of data

7. Right to object

8. Rights in respect of automated decision making and profiling

Taken together, these principles and rights make the GD PR the most powerful and far-reaching law on privacy in the world.Because so much business is now very international, the effect will be that companies outside the EU will comply with GD PR privacy standards in order to have access to the 500 m rich consumer markets in Europe.

GD PR in Tourism Marketing

As with every industry dealing with personal and sensitive information, businesses will have to adjust.In this case, anyone who owns a tour business, a travel agency, carries out business activities, etc. within the EU or uses personal information from EU citizens.Generally speaking, GD PR leaves much to be interpreted as follows: (Clear guidelines are lacking). GD PR takes a broad view of what constitutes personal identification information. The biggest challenge is to turn the legal requirements imposed by GD PR into sustainable operational strategies to keep GD PR compliant.For example, tour operators share customer information with suppliers on a daily basis  this is part of the booking process.Booking engines are connected to and used by multiple APIs, databases, and third-party providers.The problem is how to manage the data.

Best Practices for GD PR for Tour Business:

• Keep a record of all existing personal information.
• Check how and when your client has consented.
• Make sure you know how to store and use the data.
• Manage how data is protected and secured.

Web Analytics and Tourism

Sunday, 14 June 2020

Web Analytics and Education

 

Web Analytics is the practice of measuring, collecting, analyzing and reporting online data with a view to understanding how visitors use a website and how to optimize its use. Web analytics focuses on understanding the users of a site, their actions and their activities.Studying the behavior and activities of online users generates valuable marketing intelligence, and provides:

1 Tests of Website efficiency against goals

2 Perspectives on user preferences and expectations, and how the platform meets those requirements

3 Fitness to make changes to improve the website

Even now, the entrance to museums, churches, or sites of interest in many tourist destinations , especially in provincial locations, has a person carefully collecting traveler data.Its place of origin, more specifically.Until recently, that was the way the tourism and hotel industries worked.

Process of Web Analytics

1. Collection of data : This stage is the collection of the simple, important information.Generally speaking, the knowledge is stuff reviews.This stage is aimed at accumulating the information.

2. Preparation of information into Data : This stage takes tallies more often than not and makes them linear, given the fact that there might still be a few tests.The purpose of this stage is to take the information into data , specifically measurements, and to accommodate it.

3. Creating KPI : This stage focuses on using the proportions (and controls) and mixing them with business methodologies, referred to as key markers of execution (KPI).Commonly, but not necessarily, KPIs handle transition perspectives.It trusts in the association.

4. Detailing on web procedure: This stage is concerned with the organization or company's online objectives, expectations and gauges.These procedures are typically identified with profit, some cash set aside or market shares expanding.

Analytical Tools : Web-Analytics Tools is used for Website Data Analysis and Reporting to measure and optimize web use.It is not only useful for traffic measurement, but can also be used for business and marketing research and website efficiency assessment and improvement.These free and paid tools enable you to track which keywords will send you traffic, which keywords will be profitable and which keywords will lose money.As soon as you begin to track results your campaigns become more efficient because you start to focus on the results.

Challenges of click-stream data in Tourism Industry

June 6, 2020

Challenges of click-stream data in Tourism 

Hi friends..

In this post i will be talking about the importance of the click-stream data in tourism industry. The term 'click-stream' describes how users navigate on websites.Clicking stream data is what we call user behavior data, tracking every single "click" over your website or application.To determine user behavior, most tourist companies already use a number of common analytics tools.

Click stream lets you track all of the events you want and broadcast them to our data warehouse, marketing or any other destination in real-time with the right platform.Travelers tend to use a range of sources of information, including social media, and look at the interactions between a limited number of sources of information here we use click stream data in predicting the behaviors of travelers by providing the detailed transnational information tracked and recorded.

Challenges of click stream data

• Because data streams are potentially unbounded in size, the amount of storage needed to calculate an accurate response to a data stream query can also grow unbounded.
• New data is continuously arriving even as the old data is being processed; the amount of computation time per data element must be small, or the computation latency would be too high and the algorithm can not keep up with the data stream.
• The continuous data stream model is most applicable to issues where timely query responses are relevant, and large amounts of data are generated continuously at a high rate over time.
•  To autonomously respond to changing conditions and data trends.
•  continuous data streams may be infinite, a blocking operator that has a data stream as one of its inputs can never see all of its input and will therefore never be able to generate any output.

Predictive Analysis in Tourism Industry

Predictive Analysis in Tourism Industry.

May 30

Hello Friends..

Travelers are looking more and more for customized experiences.

The job is impossible without predictive analytics.Systems need to anticipate what the customers want within a few milliseconds and then adjust the product accordingly.For example, putting together a trip, extra luggage, a hotel while also dynamically changing the price slightly and considering real-time deals from competitors.Worldwide there are over 3 billion air passengers a year.This generates a huge number of transactions online that need to be checked in real-time.The losses from payment fraud and other related transactions are substantial.Predictive analytics is useful for inferring missing data and also for matching various sources adding new travel systems capabilities. In a tourism industry powered by analytics , predictive analytics and in-depth customer testimonials and data can be integrated to inspire purchases and loyalty by customization.All-inclusive bundles, flexible travel and accommodation packages, and historical and budget-based car rental choices are advantages that merely scratch the surface of what predictive analytics can produce.

Predictive analytics differs from conventional business intelligence programs by taking a predictive approach to data. Predictive analytics predicts how the customer will behave in a potential situation and how it will respond to the various "touch points" that a company has with it.Predictive Analytics offers a rare ability to predict developments in the future and helps companies to capitalize on them.

Five basic ways of making use of predictive analytics in the Tourism industry.

1. To Grow-Most tourism industries use analytical methods to rate each customer based on their behavior, experiences and reactions to attitudes.They then use these outputs to drive improvements in their own actions in customer-facing market segments

2.Competition -Another common reason tourism companies use predictive analytics is to gain competitive advantage and learn about market place changes, customer patterns and trends from customers before their competitors.

3. To Please -Successful businesses frequently spend just as much time and energy (if not more) in retaining the customers they already have as they seek to acquire new customers.

4. To Inform -You probably already do some sort of analysis of the past performance data from your company.

5. To Defend- Many companies use it to guard against fraud or other illegal activity.

I strongly believe that predictive analytics offers potential benefits to tourism business.

Finding Value using Data Analytics in Tourism Industry

May 24 2020

Last week, it was discussed the concept of Big Data and how its main objectives is to create value for the Tourism industry.Now going further I would like to share thought over how tourism industry use data analytics.

Analysis of Data

The tourism industry is working for the modern traveler to create the perfect experience and provide a number of facilities in one shot.Nearly every modern travel and tourism industry which works on data science.Travel service providers are now specializing in using state-of-the-art technology such as Big Data Analytics to increase their business efficiency, and standing out among their competitors.Tourism industry players can now take informed decisions based on analytics and data driven by numbers.At each stage of the trip planning process, we can identify targeted groups of potential customers.Big data can even be used to predict which new products could function well in their market.

Analysis of customer sentiment-Customer reviews play an important role in the travel industry, Travelers read reviews posted on various websites and web platforms, and make decisions on their basis.Sentiment analysis is the process of computationally identifying and categorizing opinions expressed in a piece of text, in particular to determine the attitude of the writer towards a particular product or subject is positive , negative or neutral.

Time analyzes play a key role in the tourism field.Models of tourism forecasting help much to predict travel activities for specific segments and segments of customers.The key role of real-time analysis is to find prospects for new deals over the long and short term.From past customer data a company can predict future business expansion opportunities.Customers travel trends and can all analyze their behavior using the data collected.Customers travel trends and can all analyze their behavior using the data collected. Data can be collected about previous travels of the customers, their liking. 

Analysis of data can be done, insights can be collected, changes in trends of customers or behavioral trends can be extracted and future trends of customers can be predicted.Customers travel trends and can all analyze their behavior using the data collected. Data can be collected about previous travels of the customers, their liking. Analysis of data can be done, insights can be collected, changes in trends of customers or behavioral trends can be extracted and future trends of customers can be predicted.

Introduction

Hey I'm Roney Jose
I am a Travel Agent in Dublin, https://rjctourism.blogspot.com currently doing Masters in Digital Marketing with Dublin Business school.My ultimate aim is to provide enjoyable quality excursions/trips on time and on budget.

Big Data in Tourism

This is my first blog on Tourism sector from my views and experience

I am Roney Jose from India and currently doing my masters in Digital  Marketing like me most of the people likes to explore the world. Tourism is one of the important economy sector for most of the countries and generating lot of employment opportunities.

What is Big Data ?
Big data is a mixture of structured , semi-structured, and unstructured data generated by companies that can be used for knowledge purposes and used in machine learning applications, predictive mode[ling, and other advanced analytics.Big data is collected from various platforms like social media, CCTV footage, GPS- enabled tracking system, asking customers directly for data.


DATA IN TOURISM

Big data is a critical part of the tourism business.Travel companies are renowned for the processing and storage of vast volumes of data.We collect data such as customer details, flight routes, purchases, yields, check-ins, etc. during and travel journey phase. Every hotel has a CRM package and let's not forget that yield management was invented in the travel industry years ago.

Until recently this data was only processed, so it was difficult for travel companies to actually use this data by integrating various datasets.With the sheer amount of computing resources, inexpensive and efficient storage solutions and multiple analytics start-ups waiting to help, this knowledge can finally be used to make the consumer more valued and better serviced, contributing to more sales



IMPORTANCE OF BIG DATA IN TOURISM TECHNOLOGY MARKET:

Big data will help those in the tourism industry in a variety of important ways, enabling more decision taking based on facts.These include the ability to more reliably predict potential demand, refine pricing strategies, more specifically target promotions and improve customer experience.

4 Ways Big data can benefit the tourism sector

1.Governing revenue
To order to optimise financial performance, hotels and other tourism companies need to be able to deliver the right product to the right consumer at the right moment, at the right price, through the right channel, and big data can be invaluable for this

2.Reputation Management
Customers can leave comments on a wide variety of different outlets during the internet era, including social media sites, search engines and dedicated review websites, sharing thoughts and experiences online.

3.Strategic Marketing
Big data will help tourism companies take a more systematic approach to the marketing campaigns, reaching the right people in the right direction.

4.Customer Experience
Hotels and other tourism businesses have a wide range of customer interactions and each of these interactions can provide valuable information that can be used to enhance the overall customer experience.