Our client has a leading online hotel aggregator, allowing users to compare hotel prices in just a few clicks from hundreds of booking sites. With 17+ years of experience, the client is one of the leading global accommodation search websites. The client's website compares and displays different offers from many booking sites and receives a fee from partner websites if a user clicks on their specific deal. The firm works with several booking sites worldwide, including online travel agencies, accommodation chains, and independent hotels, covering more than 2.5 million hotels across 190 countries.
The client had a massive and continuously growing database of hotel records. Their partner hotels send a list of accommodations to be listed on the client's platform, which are automatically processed by the platform. However, the received information is often incomplete, duplicate, or existing entries for listing on the client's platform. This resulted in unmanageable travel data volume, making it difficult for the client to review new listing data effectively.
To address this challenge, the client sought BPO services for travel data support to match new listing data with their existing database. This process compares and tries to match the accommodations with the items in our inventory. This involved identifying duplicate, incomplete, and invalid records, categorizing accommodations, and marking new listings for upload into the client's portal. The entire process needed to be performed within the client's AI-dependent tech platform, using the latest guidelines received from the client.
Our AI tool is highly adept at processing listings, but there are instances where the automated process may fall short in detecting whether the listing data matches existing hotel records in our database. This is usually due to identical hotel names, city locations, or other factors., and so to address this, we needed professional data management experts to carry out a manual process to match and verify listings accurately.
After careful consideration, we decided to partner with DataEntryIndia.in. We began with a sample and were incredibly impressed with the results as they gave it a 100% accurate data matching solution. This led us to hand over the project to their team.
- Client
Due to the changed hotel name or address, it was difficult for the team to investigate the duplicate hotel listings. To address this, our experts had to manually search hotel details on different sources- websites, competitors' sites, etc. to identify and match accommodation details.
The client's AI-based platform has a constant flow of property listings data, these listings were to be constantly reviewed and matched in real-time. This required us to work under tight deadlines and manage time efficiently.
Manual verification of each listing was a daunting task. Mapping cities that exist in multiple states/countries or mapping hotels with similar names that exist in different locations further added to the complexity. Hence, it was crucial to avoid any discrepancies to ensure that it was complete and accurate.
Working within the crowd tool presented several challenges for our team. Firstly, we needed to familiarize ourselves with the platform's interface and learn how to use its various features effectively. Secondly, the software had a unique workflow that we needed to follow, and any deviations could impact our work's accuracy and efficiency.
In 2014, we began with a team of six professionals. Today, our team has grown to 130 employees, with 100 dedicated to data matching and 30 to quality assurance. With the client's expansion and more collaboration with partner websites, we scaled our team according to our client's business needs and provided the client with the following solutions:
Under this process, our team is required to match and identify duplicate listings coming from different partner hotels/websites to the client's existing database stored in the software.
For this, our team follows a five-step approach-
In instances where we do not find a suitable match for the hotel data in the client's existing database inventory, we move towards other steps involving:
It is a secondary process performed by our quality specialists over the crowd tool. In this process, we check and verify the correctness of the action performed in the earlier data matching stage via data verification techniques. If any mismatches or incorrect actions are identified, such as different closest city markings or the wrong hotel added to the wrong city due to confusion arising from identical hotel names in different cities or countries, our experts record the error on the QA panel of the tool and mark the entry correctly. This helps us maintain high levels of quality and precision in our data matching processes.
Whether we encounter a property data mismatch in our existing database or identify a match, we create a comprehensive Excel log that provides the reason for our findings. This provides complete transparency and accountability of our work done to the client.
Managing this project has been an exciting and challenging experience for our team. We have had to work under tight deadlines and handle a massive amount of data while maintaining accuracy and quality. Nevertheless, we have successfully delivered on our commitments to the client and are grateful for the opportunity to contribute to their business.
- Project Manager
Our team of experts was able to seamlessly integrate with the client's platform and provide the necessary data support. At present, we are processing 500k+ listings per month, helping the client effectively manage their travel data and maintain an accurate hotel listing on their portal.
While the client was dealing with customer complaints and poor customer experience due to inaccurate information on its website, however, with our continued efforts, the client has attained 98.99% accuracy.
Our data-matching process ensures that the client's database is clean, accurate, and up-to-date. This has not just enhanced the client's credibility but also enhanced the user experience for their customers.
DataEntryIndia.in’s human-in-the-loop highlights the importance of human expertise in automation. Despite the client having an AI platform for processing hotel listings, it still needed human expertise to accurately review and validate the data to ensure that new listings matched their existing database. Our approach of combining human expertise with automation guaranteed the success of the project by ensuring that the listings were processed accurately and in real time, reducing the risk of erroneous data being uploaded onto the client's platform.
To discuss your business challenges or get a free consultation, write to us at info@dataentryindia.in
info@dataentryindia.in
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