Publicado en 3C Tecnología. Edición Especial – Noviembre 2019

Autores

• Md. Alauddin
• Ting Choo Yee
• Ian Tan Kim Teck

Resumen

Abstract

The new era of digital world with the rapid expansion of social network and mobile applications created wider scope to expand airline industry for new way of promoting their business. Due to several social media and other digital platforms, we need to emphasize on target marketing/customer profiling. Hence, to do target marketing, a new web technology is created to collect each of the raw events of their web data and mobile app data for tracking the way user is searching flights. In the proposed method BigQuery is used to process huge volume of online customers’ data. The proposed method is to understand the airline ecommerce online visitors effectively by analysing the event data stream collected from various digital properties. The obtained raw digital data consists of lot information with a semi-structured and it needs to be cleansed before analysing it. So, the first stage of proposed system is to extract the data from various digital sources in real-time, then chose which data is appropriate for analysing and finally extract the key insights to improve the airline business. From the extracted variables, search patterns, the predictive models such as flight search forecast, seat sales forecast and digital channel attribution models can be developed.

Artículo

Palabras clave

Keywords

Click stream processing, Big Query, Digital data processing, digital marketing, Data Cleansing and Enrichment.

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