Travel & Hospitality

It is well known fact that data science is widely deployed in the hospitality sector – with applications in demand forecasting, targeted marketing , detailed customer analysisand the management of operations,& supply chain.

As more and more bookings are done online though smart phones,there is greater need for real time analytics to push personalized deals to the customers by approaching them at the right rime through location based marketing campaign –using Geo-fencing and data on past browsing patterns .

Once the guests are in the hotelpremises,based on customer preferences and on real time occupancythe hotel apps offer instant discounts coupons on range of recreation activities in the hotel to boast revenue per guest.

Though AI/ ML algorithms, the customers are segregated based on the preferences and tastes and hyper-personalised campaigns are launched. For instance, the SPA coupons are sent for those customerswho are interested only in SPA and related leisure activities while additional night stay can be provided to another set of customers who are interested in spending nights in the hotel. Personalisation of services leads to increase revenue per customer and improved customer experience.

Pricing is another key factor that controls key metrics such as the occupancy rate, revenue per room, cancellations and margins. AI controlled dynamic pricing models get trained on enormous data and take into account multiple factors such as weather, holidays, airlines data, &seasonality.