In today’s hyper-competitive hospitality landscape, where guests compare prices across 10+ platforms before booking and 70% of reservations come through digital channels, the ability to manage booking data effectively has become a make-or-break factor for hotels. From tracking real-time room rates across OTAs (Online Travel Agencies) to monitoring competitor inventory and analyzing guest behavior patterns, booking data fuels every critical decision—pricing, marketing, and operational efficiency. However, collecting, aggregating, and acting on this data is fraught with challenges: fragmented sources, aggressive anti-scraping measures, geographic restrictions, and the need for 24/7 real-time updates. This is where proxies emerge as a game-changing tool, enabling hotels to navigate these hurdles and turn raw data into actionable insights. In this article, we’ll dive into how proxies solve specific pain points in booking data management, explore core use cases, and explain why industry leaders trust solutions like OwlProxy to power their data-driven strategies.

The Strategic Importance of Booking Data in Hospitality

Booking data is the lifeblood of modern hotel operations, transcending mere transaction records to become a strategic asset that drives revenue, enhances guest experiences, and optimizes resource allocation. To understand its significance, consider the breadth of data points hotels must track daily: real-time room rates across 5-15 OTA platforms (e.g., Booking.com, Expedia, Agoda), inventory availability (standard rooms, suites, promotional packages), guest demographics (origin, booking channel, stay duration), cancellation patterns, competitor pricing strategies, and even local events that impact demand (concerts, conferences, holidays). Each of these data points, when analyzed collectively, empowers hotels to make decisions that directly impact the bottom line.

For revenue management teams, booking data is the foundation of dynamic pricing—an approach used by 85% of mid-to-large hotels to adjust rates based on demand, competitor pricing, and inventory levels. A 2023 study by Hospitality Technology found that hotels using data-driven dynamic pricing saw a 12-18% increase in average daily rate (ADR) compared to those with static pricing models. Without accurate, real-time data on competitor rates or OTA promotions, hotels risk underpricing rooms (leaving money on the table) or overpricing (driving guests to competitors). For example, a beachfront resort in Bali that fails to adjust rates during peak surfing season or a business hotel in Tokyo that misses a last-minute conference booking surge could lose 20-30% of potential revenue in a single week.

Marketing teams rely on booking data to refine targeting and channel strategies. By analyzing which OTAs drive the highest-value guests (e.g., longer stays, higher ancillary spend on spa or dining), hotels can allocate marketing budgets more effectively—boosting commissions on high-performing channels or investing in SEO for direct bookings to reduce OTA dependency (which typically charge 15-25% per reservation). Guest demographic data also informs personalized marketing: a hotel in Paris might run targeted ads for families on Booking.com during school holidays or promote romantic packages to couples on Expedia for Valentine’s Day.

Operations teams, too, depend on booking data to optimize staffing, housekeeping, and inventory. Knowing that 70% of check-ins occur between 3-6 PM allows for smarter front desk scheduling; tracking which room types are most popular (e.g., king suites with city views) ensures housekeeping prioritizes cleaning those first to maximize availability. Even food and beverage departments use booking data—if a hotel anticipates 200 guests for a weekend wedding block, the restaurant can adjust ingredient orders to avoid waste or stockouts.

The stakes are high: inaccurate or delayed booking data can lead to overbooking (a PR disaster that costs an average of $220 per displaced guest, according to a 2024 Hotel Management study), missed pricing opportunities, or inefficient resource allocation. Yet, collecting this data at scale—across multiple platforms, regions, and time zones—presents significant technical challenges. This is where proxies become indispensable, acting as the bridge between hotels and the data they need to thrive.

Challenges Hotels Face in Booking Data Collection and Management

While booking data is critical, collecting and managing it effectively is far from straightforward. Hotels operate in a complex ecosystem of data sources, each with its own barriers to access, and face technical, logistical, and regulatory hurdles that can derail even the most well-intentioned data strategies. Below are the key challenges that make manual or basic scraping methods ineffective—and why advanced proxy solutions are necessary.

1. Fragmented Data Across Disparate Channels – Hotels today distribute inventory across a fragmented landscape: 5-10 major OTAs, their own website, direct booking tools (e.g., Google Hotel Ads), metasearch engines (e.g., Kayak), and even offline channels (travel agents, corporate contracts). Each of these channels stores booking data in silos, with varying formats, APIs, and access restrictions. For example, Booking.com’s API limits data retrieval to 100 requests per minute, while Expedia requires separate authentication for rate and inventory data. Manually logging into each platform to export CSV files is not only time-consuming (taking 2-3 hours daily for a mid-sized hotel) but also prone to human error—missed updates, typos, or delayed exports that render data obsolete by the time it’s analyzed.

Even for hotels using channel managers (tools like SiteMinder or Cloudbeds), data aggregation remains limited. Channel managers excel at pushing inventory and rates out to platforms but struggle to pull in granular data like competitor rates, guest reviews, or OTA-specific promotions (e.g., “last-minute deals” only visible on Agoda). This leaves hotels with an incomplete view of their market position, forcing revenue managers to make decisions based on partial information.

2. Aggressive Anti-Scraping Measures by Target Platforms – To protect their data and prevent server overload, OTAs and booking platforms employ sophisticated anti-scraping technologies that block automated data collection. These measures include IP blocking (temporarily or permanently banning IPs that make too many requests), CAPTCHAs (which require human verification), rate limiting (restricting the number of requests per minute), and device fingerprinting (tracking browser settings, screen resolution, or cookie data to identify bots). A 2024 survey by the Web Scraping Academy found that 89% of hospitality companies had experienced IP bans while trying to scrape OTA data, with 41% reporting daily disruptions to their data pipelines.

For example, a hotel using a single office IP to scrape Booking.com might find its requests blocked within hours, as the platform detects an unusually high volume of traffic from that IP. Even rotating between a handful of residential IPs (e.g., using employee home networks) is risky—modern anti-scraping tools can识别 patterns in request timing or user behavior (e.g., no mouse movement, identical request intervals) and flag them as bots. The result? Gaps in data collection that leave hotels blind to sudden price changes or inventory updates from competitors.

3. Geographic Restrictions on Pricing and Inventory Data – OTAs and booking platforms often display different rates, room types, and promotions based on the user’s geographic location. This is due to regional pricing strategies (e.g., lower rates for domestic travelers in emerging markets), local partnerships (e.g., discounts for users in specific countries), or regulatory requirements (e.g., tax-inclusive pricing in the EU vs. tax-exclusive in the US). For hotels expanding into new markets—say, a boutique chain in New York launching in Tokyo—understanding these regional variations is critical to setting competitive rates and tailoring promotions.

However, accessing region-specific data is challenging. A hotel based in London trying to view Booking.com’s Japanese version will be redirected to the UK site unless it uses a Japanese IP address. Without a way to spoof geographic location, hotels risk basing their market entry strategies on inaccurate, region-biased data. For instance, a hotel might set rates 10% higher than local competitors in Bangkok because it only sees prices for international users, leading to poor occupancy rates.

4. Data Security and Regulatory Compliance Risks – Booking data often includes sensitive information: guest names, email addresses, payment details, and booking preferences. Collecting and storing this data requires strict adherence to privacy regulations like GDPR (EU), CCPA (California), or PDPA (Singapore), which mandate secure data handling, explicit consent for data collection, and breach notification protocols. Hotels that use unencrypted scraping tools or unreliable proxies risk exposing this data to hackers or violating compliance requirements, leading to fines (up to 4% of global annual revenue under GDPR) or reputational damage.

Even non-sensitive data—like competitor rates—carries risks. Some OTAs include “terms of service” clauses that prohibit scraping, making hotels vulnerable to legal action if caught. Using proxies that don’t mask the source IP or leave traces of scraping activity can increase this risk, as platforms may track the origin of requests and send cease-and-desist letters or pursue legal remedies.

5. Need for Real-Time Data to Support Dynamic Decision-Making – In a market where rates can change hourly (e.g., during peak travel seasons or local events), static, daily data dumps are no longer sufficient. Hotels need real-time updates to adjust rates, close discounted inventory when demand spikes, or reopen rooms when cancellations occur. For example, a hotel near a convention center might raise rates by 50% if it detects that a major conference has sold out, but only if it has real-time data on competitor availability.

Yet, real-time data collection requires constant, high-frequency scraping—exactly the behavior that triggers anti-scraping tools. A hotel that needs to check 10 OTAs every 5 minutes (1,440 requests per OTA daily) will quickly overwhelm basic scraping setups, leading to IP bans or throttled speeds. This creates a paradox: the more critical the data, the harder it is to collect without disruption.

These challenges—fragmentation, anti-scraping measures, geographic restrictions, security risks, and real-time demands—are why hotels are turning to proxies. By masking IP addresses, rotating access points, and simulating human behavior, proxies enable secure, reliable, and scalable data collection. And among proxy providers, solutions like OwlProxy stand out for their ability to address the unique needs of the hospitality industry, from global coverage to enterprise-grade security.

How Proxies Solve These Challenges: Core Use Cases

Proxies act as intermediaries between a hotel’s data collection systems and target platforms (OTAs, competitor websites, etc.), routing requests through a network of IP addresses to bypass restrictions, ensure anonymity, and enable global access. For hotels, this translates to four core use cases where proxies deliver tangible value, transforming how they collect, analyze, and act on booking data.

Aggregating Multi-Channel Booking Data for Unified Insights

The first step in effective booking data management is aggregation: bringing together data from OTAs,官网, and offline channels into a single, actionable dashboard. Without aggregation, hotels are stuck comparing apples to oranges—e.g., analyzing Booking.com’s “revenue per available room” (RevPAR) in isolation from direct booking RevPAR, missing trends like “guests who book on Agoda spend 15% more on F&B” or “last-minute bookings on Expedia have a 20% higher cancellation rate.”

Proxies enable seamless aggregation by overcoming two key barriers: IP blocking and API limitations. By routing requests through a large pool of rotating IP addresses, proxies prevent target platforms from detecting and blocking automated scrapers. For example, instead of sending 1,000 requests from a single hotel IP (which would be blocked within minutes), a proxy network might distribute those requests across 100 different IPs, each making 10 requests—appearing as normal user traffic to the OTA’s servers.

Dynamic residential proxies are particularly effective here, as they mimic real user IPs assigned by ISPs (e.g., a residential IP from Paris for scraping Booking.com France, or a Tokyo IP for Agoda Japan). This reduces the risk of detection, as residential IPs have a lower “bot score” than data center IPs (which are often associated with scraping). For hotels managing data across 5+ OTAs, this reliability is critical—even a 1-hour outage in data collection can mean missing a competitor’s price drop or a sudden spike in demand.

OwlProxy’s dynamic residential proxy network, which includes over 50 million IPs across 200+ countries, is designed for this exact scenario. By rotating IPs with each request and matching geolocation to target platforms (e.g., using a London IP to scrape Booking.com UK), it ensures consistent access to OTA data without triggering anti-scraping measures. This allows hotels to aggregate data from even the most restrictive platforms, from niche regional OTAs (e.g., Ctrip in China) to global giants like Booking.com, and feed it into analytics tools for unified reporting.

The result? A single source of truth for booking data that eliminates manual errors, reduces aggregation time from hours to minutes, and uncovers cross-channel insights. For example, a hotel in Barcelona using proxy-powered aggregation might discover that guests booking through Google Hotel Ads have a 30% higher direct booking rate (via post-stay emails) than those from Expedia, prompting it to allocate more budget to Google Ads and reduce Expedia commissions.

Real-Time Pricing Intelligence and Competitor Monitoring

In the era of “rate parity” and dynamic pricing, a hotel’s ability to monitor competitor rates in real time is its most powerful revenue tool. Studies show that hotels with real-time pricing intelligence adjust rates 3-5 times more frequently than those relying on daily updates, leading to a 10-15% higher RevPAR. But to do this, they need to scrape competitor websites and OTAs constantly—often every 5-15 minutes—to capture sudden changes, promotions, or inventory adjustments.

This high-frequency scraping is exactly what triggers anti-scraping tools, making proxies essential. Consider a mid-sized hotel in Rome competing with 10 nearby properties. To monitor each competitor’s rates across 3 room types (standard, deluxe, suite) and 7 booking dates (next 7 days), it would need to make 10 competitors × 3 room types × 7 dates = 210 requests per scrape. At 15-minute intervals, that’s 840 requests per hour—far more than a single IP can handle without being blocked.

Proxies solve this by distributing requests across multiple IPs and mimicking human behavior (e.g., varying request intervals, adding random delays, or simulating mouse movements). Static proxies, which provide dedicated IPs for long-term use, are ideal here—they offer consistent performance for high-frequency scraping and can be whitelisted by target platforms (in cases where OTAs allow enterprise scraping with prior approval). For hotels with predictable scraping patterns (e.g., monitoring the same 10 competitors 24/7), static proxies ensure stability without the overhead of IP rotation.

OwlProxy’s static ISP住宅代理, which combines the reliability of dedicated IPs with the “human-like” characteristics of residential IPs, is a popular choice for this use case. Unlike data center proxies, which are easily flagged, ISP住宅代理 are assigned by real ISPs, making them indistinguishable from regular user traffic. This allows hotels to scrape competitor data at scale—even every 5 minutes—without interruptions. For example, a luxury hotel in New York using OwlProxy’s static ISP proxies can monitor rates at the Ritz-Carlton and Four Seasons in real time, adjusting its own rates within minutes to stay competitive.

The impact on revenue is significant: hotels using real-time pricing intelligence report a 12-18% increase in RevPAR, according to a 2024 study by the International Society of Hospitality Consultants (ISHC). By reacting instantly to competitor moves—whether matching a price drop, undercutting a rival by $5, or raising rates when competitors sell out—they capture more bookings at optimal prices.

Bypassing Geographic Restrictions to Understand Regional Markets

For hotels expanding into new regions or managing multi-location chains, understanding regional variations in pricing, inventory, and guest behavior is critical. OTAs often display different rates, room types, or promotions based on the user’s geographic location—a practice known as “geo-targeting.” For example, Booking.com might show a lower rate to users in Brazil for a hotel in Rio de Janeiro (to attract domestic travelers) while displaying a higher rate to users in the US (targeting international tourists). Similarly, Agoda offers region-specific discounts for users in Southeast Asia, and Ctrip tailors promotions to Chinese travelers based on their city of origin.

To compete effectively in these markets, hotels need to see the same prices and promotions as local users. Without this, they risk setting rates too high (pricing themselves out of the domestic market) or too low (leaving money on the table for international guests). For example, a hotel in Bangkok that only views Agoda’s US-facing prices might miss that local Thai users are seeing a 15% discount, leading it to underprice rooms for international guests or overprice for domestic ones.

Proxies enable hotels to bypass these geographic restrictions by routing requests through IPs located in the target region. By using a proxy with a Brazilian IP, a hotel can view Booking.com’s Brazil-specific rates; with a Thai IP, it can access Agoda’s local promotions. This “local view” is invaluable for market entry strategies—whether launching a new property in Tokyo or adjusting rates for a seasonal push in Sydney.

The key here is proxy coverage: to access region-specific data, the proxy network must have IPs in the target country, ideally from major cities (e.g., a Mumbai IP for scraping MakeMyTrip India, or a Sydney IP for Wotif Australia). Generic “global” proxy networks often lack deep coverage in emerging markets (e.g., Vietnam, Indonesia), limiting their usefulness for hotels targeting those regions.

OwlProxy’s global proxy network, which includes IPs in over 200 countries and territories, addresses this gap. For hotels expanding into Asia, for example, it offers extensive coverage in key markets like China (with IPs in Beijing, Shanghai, and Guangzhou), India (Mumbai, Delhi), and Japan (Tokyo, Osaka), allowing them to scrape local OTAs like Ctrip, MakeMyTrip, and Rakuten Travel with region-matched IPs. This ensures they see exactly what local users see—from promotional banners to hidden discounts—and can adjust their strategies accordingly.

Consider a hotel chain based in Europe looking to enter the Indian market. By using OwlProxy’s Mumbai IPs to scrape MakeMyTrip and Yatra, it can identify that domestic Indian travelers prioritize free breakfast and airport transfers, while international travelers on the same platforms value flexible cancellation policies. Armed with this data, the chain can tailor its OTA listings and rates to appeal to both segments, increasing occupancy in its first year of operation.

In a global industry where 60% of hotel bookings come from international travelers (per WTTC’s 2024 report), this ability to “see like a local” is no longer optional—it’s a competitive necessity.

Enhancing Data Security and Compliance in Booking Data Handling

As hotels collect increasing volumes of booking data—including guest PII (Personally Identifiable Information), payment details, and behavioral data—data security and regulatory compliance have become top priorities. The hospitality industry is a prime target for cyberattacks: a 2024 report by Verizon found that 32% of data breaches in hospitality involved customer PII, with an average cost of $4.2 million per breach. Additionally, regulations like GDPR (EU), CCPA (California), and PDPA (Singapore) impose strict rules on data collection, storage, and consent, with penalties for non-compliance reaching up to €20 million or 4% of global revenue (whichever is higher) under GDPR.

Proxies play a critical role in mitigating these risks by adding a layer of security to data collection. By routing requests through proxy servers, hotels hide their origin IP addresses, making it harder for hackers to trace data back to their internal systems. This is especially important when scraping data from third-party platforms, which may be vulnerable to malware or man-in-the-middle attacks. Proxies also encrypt data in transit (via protocols like HTTPS), ensuring that sensitive information (e.g., guest email addresses scraped from booking confirmations) isn’t intercepted.

However, not all proxies are created equal when it comes to security. Free proxy services, for example, often log user activity, sell data to third parties, or contain malware—putting hotels at risk of data breaches or non-compliance. Even paid proxies may lack essential security features like encryption or IP authentication, leaving data vulnerable.

OwlProxy prioritizes security with enterprise-grade features designed for hospitality compliance. All proxy connections are encrypted via HTTPS and SOCKS5 protocols, ensuring data remains private during transit. Additionally, OwlProxy does not log user activity or request data, aligning with GDPR’s “data minimization” principle and reducing the risk of accidental data leaks. For hotels handling EU guest data, this commitment to privacy is critical—GDPR requires that data processors (including proxy providers) implement “appropriate technical and organizational measures” to protect data, and OwlProxy’s no-logging policy and encryption standards meet these requirements.

Another compliance concern is consent: under GDPR, hotels must obtain explicit consent before collecting personal data. While proxies themselves don’t collect data (they only route requests), they can help hotels ensure compliance by enabling targeted scraping of non-personal data (e.g., competitor rates, public OTA listings) and avoiding PII where possible. OwlProxy’s ability to filter and route requests allows hotels to focus on public booking data (rates, inventory) while excluding sensitive information, reducing compliance risks.

For example, a hotel in Berlin using OwlProxy to scrape Booking.com can configure its proxy settings to collect only public data (room rates, availability, and non-personal guest reviews) and block requests for pages containing PII (e.g., guest profiles or booking history). This targeted approach ensures compliance with GDPR while still gathering the pricing and inventory data needed for revenue management.

In an industry where trust is paramount—guests expect their data to be protected—proxy security isn’t just a technical consideration; it’s a competitive advantage. Hotels that can demonstrate robust data security practices are more likely to win guest loyalty and avoid costly breaches, making enterprise-grade proxies like OwlProxy a smart investment.

Key Considerations When Choosing a Proxy Provider for Hotels

Not all proxy providers are suited for the unique demands of the hospitality industry. Hotels require proxies that balance reliability, scalability, geographic coverage, and security—all while remaining cost-effective. With hundreds of proxy providers on the market, from budget “free proxy” services to enterprise solutions, choosing the right one requires careful evaluation of key factors. Below are the critical considerations to guide this decision, along with a comparison of OwlProxy against common alternatives.

1. IP Pool Size and Diversity – The size and diversity of a proxy provider’s IP pool directly impact its ability to avoid detection and ensure consistent access. A small IP pool (e.g., 100,000 IPs) will quickly lead to repetition, as the same IPs are reused across requests—triggering anti-scraping tools that flag “unusual” traffic patterns. For hotels scraping multiple OTAs or high-frequency data (e.g., real-time pricing), a large pool is essential. Diversity is equally important: the pool should include residential IPs (to mimic real users), data center IPs (for speed), and ISP proxies (for reliability), as well as support for both static (dedicated) and dynamic (rotating) IPs.

OwlProxy’s IP pool, which includes over 50 million dynamic residential IPs and 10 million static IPs (including ISP住宅 and data center proxies), offers the scale and diversity needed for hospitality use cases. This ensures that even hotels scraping 10+ OTAs hourly can rotate through unique IPs, avoiding detection and maintaining access.

2. Geographic Coverage – As discussed earlier, geographic coverage is critical for accessing region-specific OTA data. A proxy provider with limited coverage in key markets (e.g., no IPs in China or India) will hinder a hotel’s ability to compete in those regions. Look for providers that offer IPs in 200+ countries, with deep coverage in major hospitality markets (e.g., the US, EU, Southeast Asia, and the Middle East).

3. Protocol Support – Proxies use different protocols to route traffic, each with its own strengths. HTTP/HTTPS proxies are ideal for web scraping (the primary use case for hotels), as they’re optimized for HTTP requests. SOCKS5 proxies, which support more traffic types (e.g., UDP), are useful for advanced use cases like accessing APIs or streaming data. A provider that supports multiple protocols offers flexibility, allowing hotels to adapt to different target platforms (e.g., using HTTPS for OTA scraping and SOCKS5 for API access).

OwlProxy supports HTTP, HTTPS, and SOCKS5 protocols, ensuring compatibility with all major scraping tools (e.g., Scrapy, Beautiful Soup) and OTA platforms. This versatility eliminates the need for multiple proxy providers and simplifies integration into existing data pipelines.

4. Reliability and Uptime – For hotels relying on real-time data, proxy downtime is costly. A 1-hour outage can mean missing a competitor’s price drop or a sudden demand spike, leading to lost revenue. Look for providers with a proven uptime record (99.9% or higher) and redundant infrastructure to minimize disruptions. Additionally, check for features like automatic IP rotation (to replace blocked IPs) and 24/7 technical support to resolve issues quickly.

5. Pricing Model – Proxy pricing varies widely, with models including pay-per-IP, pay-per-gigabyte (for dynamic proxies), or subscription-based (for static proxies). Hotels should choose a model that aligns with their usage: static proxies (billed monthly with unlimited traffic) are ideal for long-term, consistent scraping (e.g., daily competitor monitoring), while dynamic proxies (billed by traffic) work better for variable or high-volume scraping (e.g., seasonal data aggregation).

OwlProxy offers flexible pricing to suit hospitality needs: static proxies are available as monthly subscriptions with unlimited traffic, while dynamic proxies are billed by the gigabyte (with no expiration on purchased traffic). This allows hotels to scale costs with usage—paying more during peak seasons (e.g., summer travel) and less during slower periods.

6. Security and Compliance Features – As discussed, security is non-negotiable. Ensure the provider offers encrypted connections (HTTPS/SOCKS5), has a strict no-logging policy, and complies with global regulations like GDPR. Avoid free proxy services, which often lack these features and pose significant security risks.

To illustrate these considerations, below is a comparison of OwlProxy with two common alternatives: generic proxy providers and free proxy services.

As the table shows, OwlProxy outperforms generic and free providers in key areas like IP pool size, geographic coverage, security, and reliability—factors that directly impact a hotel’s ability to collect and manage booking data effectively. While free proxy services may seem appealing for cost savings, they introduce significant risks (data breaches, downtime, legal issues) that far outweigh the upfront savings. For hotels serious about data-driven decision-making, investing in an enterprise-grade provider like OwlProxy is the only viable choice.

FAQ: Proxies and Booking Data Management in Hospitality

Q1: Are proxies legal for hotels to use when scraping OTA data?
Yes, the legality of scraping OTA data depends on the platform’s terms of service (ToS) and local laws. To mitigate risk, hotels should: (1) avoid scraping copyrighted or proprietary data (e.g., OTA algorithms); (2) limit scraping to public information (rates, inventory, public reviews); (3) use proxies to mimic human behavior (e.g., rotating IPs, varying request intervals) to avoid disrupting OTA servers; and (4) consult legal counsel to ensure compliance with local laws (e.g., GDPR in the EU). OwlProxy’s enterprise-grade proxies help reduce legal risk by enabling targeted, low-impact scraping and avoiding detection, but hotels should always align their practices with OTA policies.

Q2: How do proxies impact the speed of booking data collection?
Proxies can slightly increase latency compared to direct connections, as traffic is routed through an intermediate server. However, this tradeoff is minimal with high-quality proxy providers. OwlProxy minimizes latency by using a global network of proxy servers with low ping times (average 50-100ms) and optimizing routing for target platforms (e.g., using a US-based proxy server to scrape Expedia.com). For most hospitality use cases—scraping 10-20 OTAs every 5-15 minutes—the latency is negligible, and the benefits (avoiding IP bans, ensuring reliability) far outweigh the minor delay. In fact, proxies often improve overall data collection speed by preventing interruptions from IP blocks, which can halt scraping for hours with direct connections.

Q3: Can small hotels with limited budgets afford enterprise proxy solutions like OwlProxy?
Yes, OwlProxy offers flexible pricing models that accommodate hotels of all sizes. For small hotels with basic needs (e.g., scraping 2-3 OTAs daily), dynamic proxies (billed by traffic) allow for pay-as-you-go pricing, with no minimum monthly commitment. For example, a boutique hotel in Lisbon might spend $50-100 monthly on dynamic proxies to collect competitor data, a fraction of the revenue gained from better pricing decisions. Static proxies, which are ideal for high-frequency scraping, start at competitive monthly rates and include unlimited traffic, making them cost-effective for long-term use. Compared to the cost of manual data collection (e.g., hiring a full-time analyst at $3,000-5,000 monthly) or the revenue lost to poor pricing, OwlProxy is an affordable investment for small and large hotels alike.