Our client operates a premier online hotel aggregator that enables users to compare hotel prices from hundreds of booking sites with just a few clicks. With over 17 years of experience, the client has become one of the top global accommodation search platforms. Their website compares and showcases offers from various booking sites, earning a commission when users click on a specific deal. The platform collaborates with numerous booking sites worldwide, including online travel agencies, hotel chains, and independent properties, offering access to over 2.5 million hotels in 190 countries.
The client maintained a vast and rapidly expanding database of hotel records. Partner hotels submitted accommodation lists for inclusion on the client’s platform, which were processed automatically. However, the data received was often incomplete, duplicated, or contained entries already listed on the platform. This led to an overwhelming volume of travel data, making it challenging for the client to efficiently review and manage new listings.
To resolve this issue, the client sought BPO services for travel data support to match new listing information with their existing database. This process involved comparing the new accommodation data with the client’s inventory, identifying duplicates, incomplete or invalid records, categorizing accommodations, and flagging new listings for upload onto the platform. The entire procedure was conducted within the client’s AI-driven tech platform, adhering to the most up-to-date guidelines provided by the client.
“Our AI tool is highly efficient at processing listings; however, there are instances when the automated system may not fully detect whether the listing data aligns with existing hotel records in our database. This typically happens due to factors such as identical hotel names, city locations, or other similar details. To resolve this, we required professional data management experts to manually verify and match listings accurately.
After careful evaluation, we chose to partner with Adobe Enter Price. We began with a sample, and the results were exceptional, delivering a 100% accurate data matching solution. Impressed by their performance, we entrusted the entire project to their team.”
-Client
Managing Duplicate Travel/Hotel Data: The team faced challenges in identifying duplicate hotel listings due to changes in hotel names or addresses. To resolve this, our experts manually researched hotel details across various sources, such as websites and competitor sites, to accurately match accommodation information.
Processing New Hotel Listings Quickly: The client’s AI-based platform continuously receives property listing data, which requires real-time review and matching. This demanded our team to work under tight deadlines while efficiently managing time.
Manually Identifying and Correcting Outdated Data: Verifying each listing manually was a complex task. Mapping cities that appear in multiple states or countries, or matching hotels with similar names in different locations, added additional layers of complexity. Ensuring complete and accurate data was essential to avoid discrepancies.
Working Within the Client’s Crowd Tool: The client’s crowd tool posed several challenges. Our team needed to quickly learn its interface and effectively utilize its features. Additionally, the software followed a unique workflow that required strict adherence, as any deviations could impact both accuracy and efficiency.
Adobe Enterprise’s human-in-the-loop approach emphasizes the critical role of human expertise in automation. While the client utilized an AI platform to process hotel listings, human oversight was essential to accurately review and validate the data, ensuring new listings aligned with their existing database. By combining human expertise with automation, our approach ensured the project’s success, guaranteeing that listings were processed accurately and in real time, minimizing the risk of incorrect data being uploaded to the client’s platform.
In 2014, we started with a team of six professionals. Today, our team has expanded to 130 employees, with 100 focused on data matching and 30 on quality assurance. As the client grew and formed more partnerships with websites, we scaled our team to meet their evolving business needs, providing the following solutions:
