Online travel aggregators such as Cleartrip have been at the forefront of adoption of data & analytics and have applied it to number of business areas.

In the travel sector, seasonality is a very important factor that can have a significant impact on day to day business goals. New-end BI tools even allow for responding to business questions like “what are the top travel destinations for Apr, May & Jun?” based on NLP (natural language based) setups.

The travel industry generates data in huge volumes. Analytics comes in handy with being the core of real-time alerting and monitoring systems to identify anomalies and rare observations.

In business, Analytics is helping organizations prioritize their investments. Analytics help optimize these investments by looking at past performance across different marketing channels, and prioritizing spends as per the business goal to drive enhanced value. 

Recommendation engines are helping identify the right content that’s relevant to a user given a certain context. And customers are being delivered the most relevant information at any point of time to help them make the best travel decisions, based on their individual stated and unstated needs.

Data analytics is also helping in the creation of smarter travel products. Take, for instance, the train PNR confirmation probability prediction feature improves service delivery and information availability for the customer. Travel companies are also starting to use chatbots. Chatbots are AI powered programs with analytical & predictive capabilities. 

In an annual business planning cycle for a travel organization the amount of variation in business due to seasonality, simple extrapolations almost never work for planning. Experimentation in pricing that almost all kind of travel players (airlines, OTAs and hotels) are trying out.