Can Crowd Analytics benefit tourism? The Hangzhou Lake Use Case

Hangzhou panorama


July 30th 2015  – Hangzhou, China


Whether it is eco tourism, tourism for development or mass tourism, the tourism industry has sunny days ahead. According to the World Tourism Organization, “international tourism receipts earned by destinations worldwide have surged from US$ 2 billion in 1950 to US$ 104 billion in 1980, US$ 415 billion in 1995 and US$ 1245 billion in 2014.”[1]

As the importance of the tourism industry is becoming bigger and worldwide, city managers as well as private organisations are working hard to try to do the best to make the tourists’ experience more enjoyable. The essential question to answer is what can benefit tourism, where the actionable tasks are and how to support and implement those.

Big data and footfall analytics have an important role to play in this effort.

While travelling to Hangzhou, China, we decided to visit the West Lake area, a famous tourist attraction and world heritage site. Once there, we measured the footfall activity around the lake as well as the trend patterns during the late evening time, with our LBASense sensors that passively count people through their anonymous mobile phone signals.

Although it was during the early evening, it was possible to measure a large number of visitors around the lake, on this clear summer day, enjoying the view and the serenity of the lake. Furthermore, by analyzing the footfall’s pattern changes, we could see that the number of visitors decreased very slowly which indicated that the tourists probably wanted to stay (or at least prefer to stay) far behind the official closing hours of the shops located nearby.

One of the lessons learned, thanks to this crowd analytics experiment, is that businesses targeting tourists in this area could open for longer or shifted working hours, in order to increase both the satisfaction of the tourists as well as their overall revenues, taking into account a correct balance between demand and costs.

Hangzhou shopping activity index: the activity goes below normal with shops closed and rises over average as long as they keep open. A sunset at West Lake.
Crowd analytics to benefit tourism: Hangzhou shopping activity index shows a below average activity when shops close and rises over average as long as they keep open. A sunset at West Lake.

As big data and crowd analytics can be implemented for tourism, as well as for other economic sectors, the key is to remember that making your city more attractive means knowing how to better understand human behaviours, in a non-intrusive but valuable way that brings satisfaction to visitors and respects cultural sites as much as their inhabitants. Benefit tourism means benefit us all.

[1] UNWTO Tourism Highlights 2015 Edition

Credits:

All images of Hangzhou by Tobias Wahlqvist, licensed under Creative Commons Zero.