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Top Use Cases of Agoda Data Scraping for Market Research in the Travel Industry
Discover how Agoda data scraping offers valuable insights for travel businesses, including key use cases for market research.
Table of Contents
Introduction
Data-driven decision-making is no longer just a process; it’s become a necessity as the travel sector continues to evolve rapidly. With travelers increasingly turning to digital platforms for planning and booking trips, travel companies need access to, collect, and analyze an extensive amount of market data. It effectively separates the level of competitive success. One of the largest platforms with a wide range of data available is Agoda. Considered a unique source of real-time, actionable information, travel companies can leverage Agoda through responsible and compliant data scraping methods to access information that has been previously hard to find or completely unavailable.
In this blog, we will delve into the top use cases of Agoda data scraping, for travel market research, and how this practice is evolving the way hotels, travel agencies, OTAs, and destination marketers develop their overall strategy moving forward.
What Is Agoda Data Scraping?
Agoda data scraping involves the automated harvesting of publicly accessible data from the Agoda platform, including hotels, flights, vacation rentals, reviews, prices, and policies. Cataloging that data enables market researchers and industry stakeholders to understand trends, monitor competition, and refine their businesses to meet the expectations of today’s travelers.
Why Agoda?
With 4.5 million properties and users from over 200 countries, Agoda has grown to become a major competitor in the online travel agency (OTA) market. It collects vast and continually updated datasets on travel trends, consumer preferences, and market fluctuations. Therefore, it is a functional data repository for holistic data and intelligence analysis. You can apply these insights from Agoda data scraping to a wide range of applications, including real-time pricing research, sentiment analysis, and competitor benchmarking.
Agoda Data for Market Research
The speed required by the tourism industry relies on three pillars:
- Real-time data,
- Competitor intelligence,
- Insight into customer behavior.
Related article: How Web Scraping Will Help Monitor Real-Time Hotel Pricing Data?
Top Use Cases of Agoda Data Scraping for Market Research in the Travel Industry
Below, we outline the main use cases of Agoda Data Scraping for market research and the value it creates for the travel industry:
Competitive Pricing Intelligence
Monitor competitor pricing and seasonal trends.
Through scraping Agoda pricing for hotels and other accommodations, businesses can perform dynamic pricing analysis, which enables them to identify how room pricing changes across various seasons, weekdays, events, and market fluctuations. By recognizing both short-term fluctuations and long-term price behaviour, travel agencies and managers of hospitality have many advantages:
- Competition benchmarking as a comparison point.
- The ability to react in real time to sudden shifts like festivals or crisis pricing.
- Identifying price-sensitive market segments
This use case can also be applied to flights, vacation rentals, packaged deals, and last-minute pricing, providing a 360-degree view of the competition.
Use Case Example
A hotelier in New York scrapes daily rates for three-star properties and notices competitor pricing drops midweek, so they adjust their rate and occupancy strategy, resulting in more bookings during their formerly slow periods.
Real-Time Inventory and Availability Scraping
Map Room, Flight, and Package Availability in Real-Time.
Travel demand is typically affected by availability, whether it is hotel rooms surrounding a city convention or package deals for family vacations. Scrape real-time inventory levels from Agoda to enable:
- Estimated sell-outs or under planned periods.
- Targeted promotions during the time that competitors have little to no inventory.
- Revenue lost by overbooking or by underpricing.
For OTAs, utilizing scraped inventory data in their offerings can entail presenting customers with the most up-to-date and competitive options.
Use Case Example
A resort chain tracks real-time room availability among regional competitors. When other hotels reach full occupancy, they quickly push unsold availability to OTAs at premium prices, thus satisfying and capturing the overflow demand and maximizing revenue for whatever visitors stay during these peak periods.
Trend Analysis & Destination Intelligence
Discovering New Destinations and Changing Preferences.
Combining Agoda data, researchers can analyze mental shifts in prominent trends like the following:
- Destination frequency by booking (which destinations are booked the most).
- Shifts in search behavior from users (e.g., ecolodge interest in new eco-tourism destinations),
- Analyzing the seasonality of migration patterns and shifts between long-haul trips versus short-haul trips.
Travel marketers and destination management organizations will benefit immensely from this intelligence. They can develop campaigns that effectively respond to changing traveler priorities and identify new market opportunities.
Use Case Example
A travel agency is noticing a booking trend related to fast-rising Southeast Asian destinations. Picking up a spike in interest for Da Nang in Vietnam, they have time to create some early-bird packages and improve their visibility before their larger competitors become aware of the sudden influx of interest they are missing.
Guest Feedback and Review Analytics
Extract and analyze customer reviews at scale.
The sheer volume of reviews on Agoda provides a pulse on guest sentiment across markets, properties, and types of stays. By scraping and analyzing this data, hotels can:
- Find operational processes that need to be improved on (cleanliness, amenities, hospitality service quality).
- Predict guest satisfaction and demand.
- Compared to peer properties
AI-driven sentiment analysis of reviews also brings attention to emerging issues (such as COVID-19 safety practices and the desire for contact-free check-in). It rectifies them before they become widespread issues.
Use Case Example
A collection of hotels scrutinizes guest reviews and ratings from Agoda to understand the recurring complaints guests make about the same topic. They discover that guests are frustrated with delays in checking in, and by reviewing the front desk’s workflow, they can make adjustments to the process to improve guest feedback scores and increase the volume of positive mentions in reviews.
Competitor Offerings and Differentiating Service
Analyzing competitors’ amenities, policies, and market differentiators.
Travelers are differentiating themselves even more, now evaluating not only price but also amenities, cancellation policies, bundled experiences, and continued loyalty. By scraping Agoda, you will get:
- Side-by-side comparisons of features, amenities, and inclusions into your room with competitors.
- Visibility on unique offerings such as complimentary breakfast, airport shuttles, or spa credits.
- Will track and monitor changes to cancellation/refund policies.
All of this information can inform product and service innovations by hotels and agencies in alignment with guest expectations.
Use Case Example
A boutique hotel discovers that most of its competitors are lacking wellness-related offerings. Knowing this, they develop a spa and wellness package and promote it across their marketing campaigns, thereby gaining a competitive advantage and eventually specializing in attracting discerning travelers seeking health & wellness-related products.
Performance Benchmarking and Market Positioning
Comparative Key Data: Star Ratings, Reviews, Location Scores.
Scraped Agoda data allows for continuous monitoring of:
- Star rating,
- Location scores,
- Popularity scores.
Regular benchmarking and positioning in the marketplace are crucial for hospitality businesses to establish their market position and set targeted improvement goals, both for individual hospitality properties and property collections (such as hotel chains).
Use Case Example
A hospitality group reviews its Agoda review score, average room price, and occupancy rate against local competitors. Learning that hotel ratings consistently score low compared to their competitors, they implement service training to improve guest experience and meet or exceed guest expectations. The hotels were able to review the metrics they had originally baselined after they made the improvements in guest satisfaction metrics.
Personalized Travel Recommendations
Scalable Data-Driven Personalization.
With extensive insight on user reviews, booking cycles, and feature preferences, travel agencies and OTAs would be able to provide:
- Relevant recommendations (hotel, experiences, destinations),
- Tailored marketing efforts (family deals, solo-traveler offers), and,
- More conversions and better customer retention.
The AI algorithms that fuel tailor-made travel recommendation systems require scraped data, essentially turning generalized travel platforms into personalized trip planners.
Use Case Example
A tour operator scrapes traveler preferences from their reviews and behaviour on Agoda and builds a dynamic recommendation engine which offers their distinct itineraries based on their activity. Using the reports, the travel operator was able to improve their rates of customer engagement and travelling experience across its platform.
Expansion, Market Entry, and Location Analytics
Expansion, Market Entry, and Location Analytics
With Agoda’s extensive coverage, businesses can analyze the viability of entering a new market for:
- A hotel opening (finding an underserved location),
- An OTA or aggregator entering a new territory,
- Evaluating competitive saturation.
Geospecific demand and price elasticity facilitate more informed strategic decisions regarding when and where to launch a new property, where to target investments, and where to incur risks.
Use Case Example
A hotel brand embarks on a regional expansion activity and discards travel data from secondary cities. It becomes apparent that there is a strong demand in Los Angeles, with a limited supply; therefore, the brand prioritized its development in that market to capitalize on a first-mover position in a rapidly growing market.
Monitoring and Predicting Travel Demand Shifts
Real-Time Indicators for Demand Planning.
Ongoing data harvesting from Agoda provides real-time signals about:
- Steep surges (event-driven demand),
- Bursts (e.g., political events, health events),
- Geographic shifts (emerging vs. declining market).
By applying advanced analytics, firms can predict the future with greater confidence, enabling them to effectively calibrate their business strategies to present and upcoming market realities.
Use Case Example
A travel technology company is monitoring spikes in search and booking returns for hotels in coastal areas, which occur rapidly as domestic travel has resumed following the lockdown. The companies take the bait and adjust their advertising spend and update their inventory based on a wave of revived travel interest, ahead of the competition.
Strategic Marketing and Campaign Optimization
Improve Marketing Campaigns and Targeting Using New Data.
Scraping Agoda keeps marketing teams aligned with real market conditions:
- Finding trending markets and customer cohorts
- Contextualizing digital ads/content by seasonality.
- Running A/B tests for promotions using competitors as benchmarks.
This use case enables sharper, more effective campaigns with measurable ROI.
Use Case Example
A digital marketing team tracks promotional campaigns run by competitors, as well as activity shown on Agoda. Realizing that users were responding well to the premise of no-required-upfront-deposit, and user bank preferences for “book now, pay later” packages and products, they implemented a further “don’t tell anyone” No-required-upfront-deposit. This adjustment improved ad performance and bookings.
Monitor Review Fraud & Brand Management
Safeguard Brand Reputation & Authenticity.
Data scraping to analyze review trends can identify:
- Sudden spikes in negative (or questionable positive) reviews,
- Unfortunately-placed review manipulation,
- Poor customer service or safety issues that could tarnish brand reputation.
Timely, data-driven brand management minimizes response times and risks.
Use Case Example
A hotel was performing sentiment analysis and flagging reviews where a hotel’s ratings were experiencing a sudden downturn. In investigating the source, they found significant and calculated negative campaigns by a key competitor. They responded publicly, limited their actions within legislative frameworks, and reported on Agoda as abuse after releasing their response, thereby maintaining their reputation and strengthening brand confidence.
Practical Case Study: Hotel Chain Competitive Benchmarking
A regional hotel chain seeking to expand its market share in the United States employed competitive benchmarking to inform its competitive strategy and tactical business decisions, leveraging data scraping on Agoda via ASCI. The hotel chain collected, in real-time, data on nightly rates, room availability, review scores, and amenities for over five destination cities and its key competitors. The hotel chain then adjusted its pricing to undercut key competitors during the off-season, engaged in targeted marketing that highlighted amenities to distinguish itself from competitors, and responded to customer complaints quickly and positively by improving service using feedback from reviews.
The hotel chain realized, in one quarter, evidence of revenue growth in occupancy and overall customer review scores, demonstrating, in a very tangible way, that continuous market intelligence can affect outcomes.
Ensuring Compliance and Data Privacy
It is essential to note that Agoda data scraping must comply with Agoda’s strict terms of service and all other applicable legal and regulatory requirements. By only scraping publicly available information and adopting responsible data practices, the benefits of market research will not be seen as either unethical or illegal.
The Future: Moving from Reactive to Proactive Market Strategy
As online data takes precedence over the decision-making process within the travel industry, Agoda data scraping will allow the industry to transition from a reactive mindset to a proactive, data-driven market leader. Companies that use scraped data to supply advanced analytics, machine learning, and AI can achieve tremendous capabilities in the following three categories:
- Dynamic Pricing and Auto-Adjustment: Using real-time competitor, demand, and data to make intelligent, automated pricing decisions.
- Hyper-Targeted, Context-Aware Marketing: Leveraging personalization on a scale not previously possible based on traveler behavior, market trends, and intent signals.
Innovative Use of Inventory and Yield - Management: Apply forecasting based on data to optimize allocation of fixed room night inventory, employee hours, and prices for revenue management.
Travel companies and travel professionals who adopt and implement these dynamic, data-driven strategies can develop ongoing profitability and a sustainable competitive advantage in an ever-evolving market.
Bottom line
Data-driven strategies are essential for success in today’s travel industry. In today’s fast-paced, data-driven, and information-rich environment, intelligent real-time insights have become crucial to competitiveness, rather than simply a nice-to-have. Agoda data scraping provides unparalleled visibility into competitor pricing, customer sentiment, and demand fluctuation. This visibility enables travel businesses to make timely and strategic decisions in their competitive strategy.
Web Screen Scraping is a trustworthy partner in the effort to extract structured data, including real-time data, to help shift from historical approaches to real-time ones, when traditional web APIs cannot achieve the same effect.
Leveraging the strengths of diverse data sampling from market signals and structured data sources enables travel businesses to gain timely access to real-time marketplace elements, including information such as nightly rates, availability, guest reviews, and policies. By utilizing this data, tourism businesses can adapt to a reactive environment with immediate details and thrive within a proactive marketplace driven by signals.
