Optimise the range of ads in the hotel and restaurant industry

Challenge:

Choosing an ad to show customers is a critical part of marketing in the online tourism sector. It is necessary to choose one that attracts consumers, but also ends in a potential sale. Analysing user search data must allow the probability and profitability of a specific ad to be defined and estimated.

Solution:

GCD@UB and an online travel company collaborated on the design of a tool to estimate the click-through rate of ads in the hotel and restaurant industry. The algorithms, which were developed based on regression models, have the capacity to process millions of attributes and allow decisions to be made in real time regarding the best ads to show at any given moment.

Image

Impact:

Making decisions about which ads to show customers should aim to increase the effectiveness of marketing so that it is relevant to the consumer and, in turn, profitable for the company.

Related Articles

E-Learning and the use of data

cat. Consulting
10.04.2018

Thanks to the emerging technologies of e-Learning, the analysis of data offers professionals in the education sector, advantages with the ability to impact and revolutionize in the future the way we analyze and evaluate the learning experience.


Interpretation of maps of the territory with deep learning

cat. Consulting
29.01.2018

Within the framework of the Cartographic Plan of Catalonia, the Cartographic and Geological Institute of Catalonia is working on the elaboration of the technical specifications of the land covers Map of Catalonia. The ICGC has commissioned us a study to explore the viability of the application of deep learning techniques in the generation of maps.


Analysis of customer behavior (Customer Journey Modelling)

cat. Consulting
29.01.2018

A company in the online sector has generated a large volume of data that provides a history to be able to extract information from clients and develop a predictive model based on the behavior of users. This behavior include the navigation through the platform, the interaction with others channels, messages to the community, etc. The ultimate goal is to provide a better customer service by recommending products based on the specific time of the customer journey.