To make the regions more attractive for tourists, and the business in the field of tourist services to flourish, the winner of the acceleration program of the Technopark of the Novosibirsk Academgorodok Alena Kanina and her team have developed a service that analyzes large amounts of data and makes an emotional map of a tourist.
The problem of the low attractiveness of the regions can be solved by constant monitoring and control of the tourist flow. However, the situation is developing in such a way that even with big data, regional authorities do not know how to work with them and need additional tools.
Travel.stat is a service for creating a quality service strategy and managing guest loyalty. With its help, the customer will be able to get a clear idea of the points of attraction of tourists in a particular region. The Travel.stat team offers a ready-made service for collecting, processing data and making a forecast.
How the system works
1. Tourists leave references about their trip on the Internet (publications, hashtags, geotags, reviews, comments, etc.).
2. The platform collects this data from all kinds of sites.
3. The collected data is analyzed.
4. A map is formed, which shows the routes of travel and points of attraction for tourists.
5. Based on historical data, a forecast of tourism trends is being built.
Who needs it and why
The system will allow you to track the duration of the route; see the regions and cities visited by the tourist; learn about his travel experiences and points of attraction in a particular region. Analysis of this information will give a forecast for the development of the service and improve the quality of service. Now the project is at the testing stage, and active work is underway with the mechanics of information presentation.
This year, the Travel.stat team, together with the Ministry of Economic Development of the Novosibirsk Region, held an event to develop a tourist travel map in preparation for the Ice Hockey World Championship, which will be held in 2023 in our city. And Alena's team has implemented a case together with the agency of the city of Ryazan, engaged in urban projects.
“In Novosibirsk, we demonstrated how, using only data collected from different sources, it is possible to track which trends are already being laid. The main goal was to find the most popular places to visit and assess the level of service in these points of attraction for tourists. And experts from Ryazan, based on our mechanics, were able to analyze the information and build a map that shows the points of tourist congestion and made a CJM (tourist travel map)”, Alena explained.
Team, participation in A: START and future prospects
At the moment, the team led by Alena is a php programmer, fullstack developer and data science. In the future, it is planned to introduce machine learning, which will allow you to analyze data and, based on statistics provided by the customer, build more accurate analytics.
Alena has been working in the tourism services market since 2012 and is the head of a studio of marketing and it solutions for the tourism and hospitality industry. However, despite her extensive experience in business, she considers participation in the acceleration program to be a valuable experience:
“It was on A: START that I learned about the emerging trends in my field, for example, that the market for No-code solutions is gaining popularity. This proves that such acceleration programs are useful not only for novice innovators, but also for those who already have experience in entrepreneurship. Thanks to the experts, powerful networking is created on the site. Its main advantage is the ability to look at your own product from different points of view. So, I realized that we should not focus exclusively on the domestic market, but we can head for America and Asian countries. At A: START, we had the first negotiations on the possibilities of entering foreign markets,” Alena explained.
Another important perspective in the life of the project is the active search for a solution to enter the B2B market. The idea is simple: to share with business information about whether tourists need their services in the requested region and, if so, to what extent. The advantage is that Travel.stat will be able to show a specific point on the map, which, according to tourists, lacks a hotel, coffee shop, etc.