Bardeen saves me at least 2-3 hours every day. Manually collecting and analyzing data on hotel locations and prices across various countries used to take me several hours. Now, with Bardeen, I can gather and process the same amount of data in just about 30 minutes. It's an absolute game-changer for my research workflow!
Vilane G. Sales is a researcher at Ca’Foscari University in Italy, focusing on climate change and economics. Her research involves an in-depth study of the global hospitality sector. She uses Bardeen to automate the process of collecting and analyzing data of hotel locations and prices across various countries.
Before discovering Bardeen, Vilane faced the significant challenge of manually collecting and analyzing vast amounts of data on hotel locations and prices across various countries.
As a researcher, she tried to solve this problem by coding the scraping process personally. This process was not only time-consuming but also required a high level of coding ability to scrape the necessary data.
Initially, Vilane had to manually collect links of hotels from Google Travel, which was a task in itself.
After gathering these links, she had to create another script to run on each individual hotel link to collect the necessary data.
This two-step process was cumbersome and inefficient.
The data collected was initially stored in .csv files, which added another layer of complexity to the data management process.
While this approach was somewhat successful, it was far from efficient.
The coding process was time-intensive and lacked the capability to be easily replicated or scaled.
This meant that she was spending a disproportionate amount of time on data collection rather than on the analysis and interpretation of the data, which was the primary objective of the research.
With Bardeen, Vilane could automate the process of collecting data on hotel locations and prices and enabled her to gather more comprehensive information than previously possible -- all with a single button click!
Bardeen significantly sped up the data collection process, saving the researcher approximately 2-3 hours every day.
Enhanced Data Collection
With Bardeen, she was able to gather more comprehensive data than was previously possible. This led to a richer dataset, which in turn improved the quality of the research outcomes.
Bardeen's scraping tool provided a scalable solution for data collection. It eliminated the need for manual coding, making the process easily replicable for different countries and regions, thereby broadening the scope of the research.
This case study underscores the power of automation in the field of research.
Through Bardeen, Vilane could focus more on her core research work, exploring the interplay between climate change and economics, rather than spending excessive time on manual data collection.
For researchers grappling with similar challenges, Vilane's experience serves as an inspiration to the transformative power of automation in research.