Analyze the behavior of tourists and increase their average spending

by | Nov 10, 2020 | 0 comments

Application Track:

Ready Made

Code:

REACH-2020-READYMADE-PLAY&GO_2

Proposed by:

Play&Go

Entity Logo:

Summary of the entity:

Play&go experience creates customized APPS that improves the user experience, based on serious games, geolocation and augmented reality. With geolocated data we provide the user information of interest getting more interaction. Besides that, it is a channel of real-time communication for organizations, obtaining geolocated information (socio-demographic and psychographic), for hypersegmented marketing campaigns and public policy planning.  JOT Internet Media is part of Cube Ventures, one of the leading digital groups in Europe. Based in Madrid and with offices in Germany, Mexico, Brazil and Italy and more than 280 employees, the group is focused on lead generation, services monetization, digital marketing, media and investments.

Summary of the challenge:

The main goal is to identify the behaviour of tourists who visit the destination and define what extra products or services can be offered to increase their average local spending.

Description of the global challenge:

It is intended to go a step further in the knowledge of the mobility of the tourists, increasing the complexity of the result to be obtained and above all focusing it on an economic benefit.

By adding other external sources of information, many more data can be obtained that affect tourist activity in cities. Geolocation is configured as the identifier that unites all this data and, from here, a complex system of geolocated information layers of a city can be made available.

The objective is to identify the behaviour of tourists who visit the destination (demand analysis) and define what extra products or services can be offered to increase their average local spending (supply analysis), to offer a global vision of the situation, identifying the areas where there is a lower balance between supply and demand, also identifying which factors are the cause of both situations.

For this, it is necessary to identify various data sources, analyse them and prioritize those that are most relevant to tourists, so that a Geographic Information System is generated that, through Machine Learning and Artificial Intelligence techniques, is capable of generating predictions about the future behaviour of tourists based on the development of certain areas and services that contribute to increasing their average spending in the destination.

Sub-challenges composing this experiment:

This challenge is composed of 2 sub-challenges:

  • Analysis and profiling of the tourist (REACH-2020-READYMADE-PLAY&GO_2.1)
  • Demand for non-existent services (REACH-2020-READYMADE-PLAY&GO_2.2)

Expected global results:

  1. The expected results are to identify the 3 main drivers of tourist behaviour
  2. Make a prediction of local development of resources, products and services that foresees an increase of 10% in average spending.

ANALYSIS AND PROFILING OF THE TOURIST

Code:

REACH-2020-READYMADE-PLAY&GO_2.1

Summary of the sub-challenge:

The aim is to predict and identify tourists interests when visiting a city.

Description of the challenge:

The sub-challenge consists in identifying, collecting, analysing, and selecting the data sources that may be most relevant in the city when it comes to analysing tourist behaviour.

From here, all these data should be integrated and, using smart location, search for the most relevant variables and try to generate a model that explains the behaviour of said tourist in the city.

Based on the tour made by the tourist, the aim is to identify habits such as where they shop, where they eat, what other attractions in the city they visit, etc. In this way, the most visited areas of the city can be identified and why, so that other areas are sought in which similar variables exist or can be promoted that favour the movement and consumption of tourists in these new areas.

As they are complex, multivariate and predictive analysis, it will be necessary to use Machine Learning and Artificial Intelligence techniques in order to generate these predictions, identify patterns and establish models.

Data to be used:

It would be advisable to combine these datasets with other data that help to achieve it, such as hospitality, commerce, transport, social networks, credit card spending, origin of tourists, areas from which access the city, etc.

Expected outcomes:

  • To identify the 3 main drivers of tourist behaviour.
  • To discover the 3 main areas of the city that attract them.
  • To discover the 3 areas with the most potential to do so based on the previous points.

DEMAND FOR NON-EXISTENT SEVICES

Code:

REACH-2020-READYMADE-PLAY&GO_2.2

Summary of the sub-challenge:

The objective is to identify what services, not present in current offer, could offer value to a tourist by knowing the route and the behaviour of the tourist.

Description of the challenge:

This sub-challenge consists in knowing where, when and what products and services tourists consume to identify those that could offer value and are not present. In this sense, it is necessary to delve into the datasets from the supply side, that is, to identify what local businesses are offering in each area of ​​the city.

The search for new non-existent services or services that have a high profitability, which can be incorporated into the destination service offer, the use of information sources from other similar events and destinations around the world will be needed.

As they are complex, multivariate and predictive analysis, it will be necessary to use Machine Learning and Artificial Intelligence techniques in order to generate these predictions, identify patterns and establish models.

Data to be used:

It would be advisable to combine these datasets with other data that help to achieve it, such as hospitality, commerce, transport, social networks, credit card spending, origin of tourists, areas from which access the city, etc.

Expected outcomes:

  • To identify opportunities for new businesses or services in the different areas of the city.
  • It would be necessary to know which are the 3 most balanced and profitable areas of the city and what is the type of services offered.

How do we apply?

Read the Guidelines for Applicants

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