POI Data Enrichment for a Leading Hospitality Management Company

Data is valuable, but enriched data is priceless.

Data enrichment is the process of adding value and further information to an existing dataset to improve its quality, accuracy, and completeness. It involves taking raw, incomplete data and enhancing it with additional and meaningful information from external sources. It turns a basic dataset into something richer, more valuable, and most importantly – actionable! 

For example,

Imagine raw data as something basic like “Motto, New York”. You can enrich this simple information by adding: “Motto, New York | 5-star | Parent company: Hilton | Operator: Hilton Worldwide Hospitality | Latitude/Longitude | 250 rooms”. This gives a complete picture of the hotel that is being discussed to make strategic decisions. 

In this article, we will unravel how we helped a client achieve clarity and accuracy with POI data extraction and enrichment. 

TL;DR

• A global hospitality management company faced challenges with manual matching and enrichment of large property datasets (~70K for matching, ~450K for enrichment). 
• In-house efforts were slow, error-prone, and inconsistent. 
• By partnering with Grepsr, they leveraged POI web scraping and advanced data enrichment to unify records, append critical attributes (hotel operator, type, location, class), and gain accurate, scalable, and actionable property intelligence. 
• The result: faster operations, better analytics, and a future-ready data framework.

About the client

A global hospitality management company serving hotels, hostels and serviced apartments approached us with a POI data enrichment project. The solutions they offer are streamlining operations, improving guest experiences and providing actionable insights for property manager. To do that at scale, they wished to unify the raw data they already had with additional information and enhance property intelligence. For high-quality, consistent POI data across all property records, they wanted to build a scalable workflow and partnership with Grepsr. 

Project requirement

They came to us with clear requirements which were: 

1. Manual Matching
   • Compare two datasets (~70,000 rows each) with columns such as property name, address, city, postal code, and country.
   • Output a match_yes_no column indicating whether the records from the two sources referred to the same property.
2. Data Enrichment
   • For a larger dataset (~450,000 rows), enrich each property with:
     • Hotel Operator (management company, owner, or soft brand)
     • Hotel Type / Location Type / Secondary Type
     • Property Class / Scale
   • Ensure enrichment followed consistent taxonomy and was ready for downstream analytics.

Enrich POI Datasets with Web Scraping for Improved Insights | Grepsr

Discover how web scraping revolutionizes Point of Interest (POI) data enrichment, keeping your datasets accurate and up-to-date.

The challenges

First, the global hospitality management company tried to do these using manual effort and their in-house web scraping team. This created several issues such as: 

Time-Consuming Manual Matching

Without automated tools, the in-house team was burdened with manual comparisons of 70,000 rows of property records. The sheer volume would result in hours of tedious work to identify and reconcile discrepancies in address formatting, missing fields, and inconsistencies across datasets. This inefficiency significantly slowed down the entire process, leaving little time for strategic analysis or decision-making.

Volume & Scale

Handling 70,000 property records and 450,000 rows of data enrichment manually would put significant strain on any in-house team. The team needed to cross-check and enrich each record, adding essential attributes like hotel operators, property types, and classifications. This required a lot of manual effort, making it unbearable as the dataset continued to grow.

Missing Fields/Attributes

Manually enriching each record would leave the biggest holes in the data. Without a dedicated, automated web scraping solution, the in-house team would be prone to missing key attributes like hotel operators, property types, and classifications. This would result in incomplete data, making it impossible to generate accurate insights, conduct meaningful market analysis, or implement targeted marketing strategies.

Operational Risk

With manual data entry and comparison, there was always a risk of human error, from mismatched records to inaccurate data enrichment. These errors would have cascaded through the hospitality management company’s systems. This would cause issues in property management systems (PMS), CRM tools, and marketing databases. Eventually, compromises the quality of decision-making and reporting.

The solution: Grepsr’s expertise in POI web scraping

Grepsr specializes in web scraping solutions for large-scale data extraction and POI data enrichment. We have a proven track record of efficiently gathering high-quality property-related data from various sources, including public listings, directories, and industry-specific websites. 

Our ability to handle complex, unstructured web data is a core strength, especially when it comes to managing discrepancies in records and enriching them with valuable, business-critical attributes.

POI Data Enrichment Expertise:

• Data Matching: Grepsr’s advanced algorithms for fuzzy matching combined with human validation ensure high accuracy when aligning datasets, even with variations in spelling, address formatting, and incomplete fields.

• Data Enrichment: We specialize in enriching property data by appending key attributes such as hotel operators, hotel type, location types, and property classifications, using reliable external sources and proprietary methodologies.

• Scalability: Our data scraping infrastructure is highly scalable, meaning that we can handle datasets ranging from thousands to millions of records without compromising speed or quality.

The final outcome

By leveraging Grepsr’s POI web scraping expertise, the hospitality management company was able to resolve its data challenges efficiently and get ahead with competitive advantages like:

• Unified and Accurate Data: With Grepsr’s approach, the client received a clean, fully reconciled dataset where records were correctly matched, eliminating the need for ongoing manual reconciliation. This resulted in a dataset that was both comprehensive and reliable, ready for use in downstream systems.

• Enhanced Analytical Insights: The enriched data, now complete with attributes like hotel operators, property types, and classifications, enabled the client to conduct deeper market analysis, segment customers more effectively, and optimize pricing and marketing strategies.

• Operational Efficiency Gains: By partnering with us for the matching and enrichment process, the client’s internal teams were freed from time-consuming manual work, allowing them to focus on high-value, strategic tasks. This improved overall productivity across departments.

• Future-Ready Framework: Grepsr provided a scalable solution for continuous data enrichment and updates. We ensured that the client can maintain high-quality property data as their business grows. The solution was tailored to adapt to their evolving data needs, providing long-term flexibility.

Transform your property data into actionable insights—let Grepsr power your POI data enrichment today!

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