12 February, 2019
Analytical company Marketing Logic has completed a project to develop an analytical module for the business travel management system of the company "Peacock-Travel". Machine learning has allowed to save up to 40% of the cost of business travel costs.
The travel management system automates the key processes in the organization of business trips: selection and booking of tickets, booking accommodation, organization of meetings and complex events. The system allows you to set and use the most favorable algorithms and rules for the selection of dates, time, mode of transport, departure and destination points for employees whose activities are related to work in different cities.
When integrating with the business processes of the client company, artificial intelligence is trained on the most effective scenarios for the use of working time and makes recommendations on the feasibility of sending an employee on a business trip, depending on his work profile, travel costs and results achieved. The principles of Geologistics, which form the basis of the module, allow the system to calculate the best way a combination of home and guest cities and build routes for each employee, taking into account the maximum efficiency for business. In the end, the expenses of the organization on business travel is reduced to 40% without compromising the results.
"As part of any classical tasks in marketing, sales growth, network management, corporations are faced with the tasks of optimizing the movement of employees, the limit of the expediency of business trips. The use of machine learning allows you to more accurately determine the rules of travel policy, reduce travel costs without losses in the company's business indicators: sales, market share and coverage level. We plan to integrate the developed system with the travel plan of the organization that will completely get away from human involvement in the selection and ordering of business travel and to save even more due to early booking and optimizing the travel policy"– says the managing partner of Marketing Logic and expert in the field of Big Data and geomarketing Dmitry Galkin.
"Everyone knows that earlier booking is usually more profitable than sudden purchases. Machine learning on different quality cases allowed us to see how much: when organizing a business trip for one week, the cost of travel is on average 30% lower than in the organization for one day, earlier booking saves up to 40%, because booking prices do not change until the date of actual payment by the client. Analytics, predictive models and clear financial and mathematical planning allow the organization of business trips to become even more profitable for our users," – says Vladimir Pavlin, General Director of Pavlin-Travel.
In addition to significant budget savings, the travel management system facilitates the exchange of documents and the approval process: invoices and closing documents are sent directly to the company's accounting Department, and the travel budget is agreed with the management.