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How is Analytics Responsible in Airfare Ticket Pricing Fluctuations?

How is Analytics responsible in Airfare Ticket Pricing Fluctuations?

It is quite a gamble these days when as a part of your travel itinerary you have to book the airline tickets. Most people in recent times have given up the traditional travel agents for booking tickets and prefer booking tickets themselves. Booking airline tickets has become a massive decision making activity, where you have to do all your thinking hats, to make an informed decision. Should I buy now, or wait for a better rate, or should I use the price trend forecast to get recommendations on when to book so that huge fluctuations can be avoided.

Post regulation, airline industry, around 1980 – 2001, was a time of price wars, fluctuating fuel prices, and a general increase in the number of passengers opting to fly, along with great technological advances, between the handful of airline providers. Airlines with conservative overheads could offer low airfares as a blanket to all its customers. But in the long run, could not sustain on low margins and had to shut shop. On the other hand, few airlines, used a scientific and analytical approach in offering reduced pricing over a certain sector, during a particular period and maintained regular premium cost airfares for the remaining slots, and with this approach not only did they survive but also accounted profit.

This article will help you understand how could they do that….

The low airfares could be offered by airlines, by following a dynamic pricing mechanism for tickets, based on the demand and supply trend.

Predictive analytics takes stock of what happened in the past, that is historical data, and the forecasts are done by using scientific methods, and statistical models for reliable information, about possible outcomes in the future. Predictive analysis is most accurate because it tries to understand the behaviour of a person or a customer, by not only looking at the past information, but is able to predict what they will also do in the future based on the customer, and about that entire population. Thus by grouping people in segments, predictive analysis will be able to give predictions and recommendations on how people will react in the future.

Predictive Analytics has continued to factor essentially into how airfare prices are decided and fluctuate to maintain airline profitability even today. It is mainly because the airline industry is getting very competitive and is a low margin industry. The ability to forecast travel demand is crucial to gain market share. Predictive analysis tools are no longer the luxury of airlines selling tickets, travel booking sites offering Price Predictors Features, can now be used by consumers to see and make decisions for their own projection. Price predicting feature will help them decide whether the price of a particular route is likely to fluctuate, higher or lower, in the coming weeks.

Keeping in line with the trend Indian government is contemplating on introducing an analytical tool which will present the travellers with future ticket price trends, similar to the travel booking sites which offer price predicting features.

This is a positive step towards addressing the travellers concerns of facing steep fluctuation in airfares. Of course, this proposal is subject to sanction from the civil aviation industry. Since air ticket prices are dependent on supply and demand metrics, this step from the aviation industry will get some amount of transparency in the entire process.

This endeavour is crucial and a part of the digitization wave, under the ‘Digiyatra’ Initiative. Since India’s Domestic aviation market is projected to be the world’s 3rd largest by 2022, it is only fair that the industry uses analytical tools to provide a digitally unified flying experience to its travellers.

Using ‘Historical Data Analysis’ along with ‘Price Curves with Predictive Data Analytics’ will help travellers better project and plan their vacations, so as to gain maximum advantage over airfares.

In conclusion, it could be said that predictive analysis is touching our lives positively, in ways that we might not be aware, and the penetration is only going to increase with time.

To learn more about Analytics watch this space until next week for the big news!

 

  • December, 16th, 2017
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How Does Twitter Know What’s Trending?

A trend on twitter is any hashtag-driven topic that gets popular within a period of time. It is any marketing departments dream come true if their hashtag starts trending or in other words gets popular on Twitter. Did you ever ponder over the fact on how these trends on twitter get started? Who or what chooses which stories should appear in the trending section, and why others get left out. Also ever wondered twitter trends are tailored. What you might see as trending might not encompass all that is trending in the world or even in your area. Trends are determined by an algorithm and are tailored to an individual, based on what they like, or who they follow, location etc…, although there would still be some topics which will appear in the trends section in spite of personalisation.

There are algorithms of twitter that are responsible for hashtags trending. These algorithms determine what is trending by observing and favouring spikes over any gradual sustained growth. For any topic to trend would need a combination of volume, the time taken to create that volume. So to put it simply, if a hashtag gains volume in one day it is considered as trending, but at the same time if the volume takes 30 days to accumulate, then it will be considered as news in general and not a spike.

If you want a hashtag created by you to trend, there are certain factors that can be practised to add to the volume. Be creative with the name of the hashtag, keep it simple with one objective, for example, if you want to create a Hashtag you need to drive one message, #standwithIndia is a better example than #standwithIndiancitizens.

Next thing is to make sure you get more than 500 tweets within the first hour, a point to remember is that not only the number of tweets is important, but it is equally important on how many individuals are tweeting.

To elaborate, common hashtags like #cat, #food, #music are very common and are tweeted every day, hence such hashtags might never start trending, however now if a totally different set of people start using these hashtags then there is a high possibility that they start trending.

So to conclude there are many factors that could push your hashtag trending on Twitter. It is Twitter’s trending algorithm eventually that finds topics that many people start tweeting at once. Like when there is noise about a particular launch of an album, television show, a natural calamity like an earthquake or a tsunami, or a death of a famous personality. At the same time, if a lot of people start tweeting about rain, it will never start trending as it is a common topic.

According to a study by HP labs, 31% of trending topics comes from retweets. 72% of those originate from 20 major news sources which are mostly based in the United States and the UK.

Like explained before, hashtags start trending if they haven’t been through the algorithm before, they might trend, then go off the grid and later start trending again if a totally different set of users discover the topic and start tweeting about it. The trending might not appear more than 40 minutes at a time, however, the trends on Twitter are considered as such prime spots for the marketing teams in general that a promoted space at the top runs at $120,000 per day.
Interesting thought!

To learn more about twitter trending algorithm watch this space until next week for the big news!

  • December, 7th, 2017
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What is the Scope of Analytics?

Analytics

The word analytics has come into focus over the last couple of years. Analytics is considered to be pivotal especially in an era where internet and technology have taken centre stage in our daily lives. Analytics is essentially a field which brings together, Data, Information Technology, Statistical Analysis, Quantitative Methods and Computer-Based Models to one platform. All this put together to form data, that is accumulated through various ever growing channels, due to the integration of technology in our daily lives, from phones to applications to online movement, any traction on the internet creates data. Analytics done on this data gives decision makers information on which to base their informed decisions.

In recent times, with changing business dynamics, organisations are looking for innovative methods through which they can enhance productivity and cut costs. Companies have large volumes of data being created from almost every area of function. Performing Descriptive, Predictive or Prescriptive Analytics on this data will assist the organisation to identify potential risk areas, understand which areas need intervention and strategy reformation, and with the application of Computer-Based Models also run a simulation, on performance based on the said strategy, and gauge application based on the results.

Hence, the application of analytics in businesses is very vast, if applied with the right vision and strategy, the possibilities are limitless. Analytics can be applied to Customer Service, Acquisition and Retention, Financial Management of an Institution, Supply Chain Management, Human Resource, Government functions, Sports, Marketing, to name a few.

The scope and use of data analytics is not only a global phenomenon, but as it is turning out, India is being considered as a big market for data analytical skills sets. A career in business analytics is very fulfilling and is one of the fastest paced developments in the current market scenario. India is hence fast becoming the most preferred destination for offshoring data analytics capabilities. In India, the development or the use and scope of analytics is massive and noteworthy mainly in Media Communications, Outsourcing Companies, Internet business Companies, etc…,

Looking at these trends it is only obvious that the future of analytics will only continue to grow upward. Outlined below are a few future opportunities in Analytics,

  • Since data is expected to grow exponentially in the future, the application of analytics will only increase in businesses.
  • Nevertheless, there will be a development of the tools used for data analysis, an example could be ‘Spark’
  • One will see an integration of Prescriptive Analytics in the Business Analytics Tool.
  • Going forward people will be able to see real-time insights in data and will be able to make real-time decisions.
  • Moving forward, Machine Learning will be a necessary element for data preparation and Predictive Analysis for businesses.
  • There will be Big Data staffing shortages, but the crunch might ease when companies start using internal training and innovative recruitments approach, Chief Data Officer will be a position that will open up in most organisations.

Whatever the debate on the future application of data analytics might be, one thing is clear, analytics has the capability of impacting profitability and productivity of a business colossally. Hence, there is no doubt in stating that the ‘Future is in Analytics’.

  • October, 9th, 2017
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