To scrape or not to scrape, a question for the golf industry

This article examines the practice of scraping tee time booking engines, a method increasingly used by various companies to gather data on golf course availability and pricing. While companies like Tee Time Snipe, Noteefy, and Loop Golf leverage scraping to enhance user experience by matching golfers with suitable tee times, others such as Priswing and RevTech (NBC Sports Next) utilize this practice to gain competitive intelligence, influencing market dynamics and business relationships in the golf industry. Noteefy, since its main customer is the golf course, scrapes at the request of the golf course when the golf course uses booking technology not integrated with Noteefy’s software.

The technical process of scraping involves automated bots extracting data from booking platforms, which, although beneficial for market analysis and strategic planning, raises significant concerns. These include the potential for market distortion through unfair competitive advantages, operational strain on booking platforms leading to degraded service quality, and data privacy and security risks, particularly when personal information is involved.

The fairness of using publicly available data without the platform's or users' consent is debated, highlighting the ethical dilemma between open access to information and the protection of proprietary and personal data. Furthermore, the competitive use of scraping for pricing intelligence can lead to a detrimental 'race to the bottom,' affecting profit margins and market stability.

The article concludes with strategies for golf course operators to mitigate the effects of scraping, such as direct communication with scraping entities, integrating advanced booking features like waitlist options, and adopting dynamic pricing models without resorting to competitive scraping. These measures can help maintain fair competition and leverage digital tools effectively to meet business goals, ultimately fostering a more equitable and sustainable golf industry ecosystem.

Scraping tee times

Scraping, in the context of tee time booking engines, refers to the automated process of using software tools to extract data from websites that list available golf tee times. These booking engines are platforms where golf courses list available slots for golfers to book tee times. Scrapers are programmed to systematically visit these booking websites, copying information about tee time availability, pricing, and other relevant details.

The purpose of scraping in this context can vary:

  • Some companies scrape booking engines to aggregate data on tee time availability, helping them provide comprehensive listings, comparisons and alerts to their users.
  • Others scrape for competitive intelligence, gathering pricing and timing data to adjust their own offerings or to analyze market trends.

The practice can become contentious when it is done excessively or without the permission of the booking platform, potentially leading to issues like server overload, data privacy concerns, and unfair competitive advantages.

Scraping tee time booking engines has become a strategic practice for companies like Tee Time Snipe, and Loop Golf, which use this method to match golfers with available tee times that fit their specific search criteria. These companies automate the extraction of data from various booking platforms, often without explicit permission from the paid licensor of the booking technology, to provide real-time availability information, thereby enhancing the service they offer to their users.

On the other side, companies like Priswing and RevTech (NBC Sports Next) engage in scraping to gather competitive intelligence. They focus on the booking engines of golf courses competing with their clients, aiming to gain insights into pricing and availability trends. Priswing, for example, employs a feature known as "Radar," which is designed to scrape the booking engines of non-client golf courses. A similar product from NBC Sports Next is said to be released to the market soon with the name of “Athena”. This tactic not only provides Priswing with valuable market data but also serves as an indirect incentive for these non-client courses to consider partnering with Priswing to protect their tee time data from being scraped. This invokes an imaginary conversation between the seller and prospect that resembles "an offer you can’t refuse".

A LinkedIn post from Priswing which can no longer be found on the site

The recent kerfuffle surrounding the city of Los Angeles' golf courses has become a significant inconvenience for golfers. Reports suggest that brokers are monopolizing tee times, likely utilizing some form of scraping to secure and resell slots at higher prices. This scandal highlights the broader issue of how digital manipulation can impact fair access to recreational facilities, creating frustration among the community of golf enthusiasts. Click HERE for more details.

The scraping process

Scraping, in the context of extracting data from tee time booking engines, involves a multi-step technical process:

  1. Target Identification: The first step is to identify the booking engines or websites from which data needs to be extracted. These are typically online platforms where golf courses list available tee times.
  2. Data Request: The scraper, which is a software program, sends a request to the target website’s server, similar to how a web browser requests a page when a user wants to visit a website.
  3. Data Retrieval: Once the request is received, the target website’s server responds by sending the data back to the scraper. This data is usually in HTML (HyperText Markup Language) format, the standard language for creating web pages.
  4. Data Parsing: After retrieving the data, the scraper parses the HTML content. Parsing involves sifting through the HTML to find specific data points of interest, such as tee time availability, pricing, and other related information. This is often done using tools that can recognize patterns or specific markers in the HTML that indicate the relevant data.
  5. Data Extraction: Once the relevant pieces of data are identified during parsing, they are extracted from the HTML and stored in a structured format, such as a database or a spreadsheet. This structured data is what the companies analyze to gain insights.
  6. Data Processing: The extracted data may undergo further processing, such as cleaning (removing irrelevant or duplicate data), transforming (converting the data into a more usable format), or integrating (combining data from multiple sources).
  7. Data Analysis: Finally, the processed data is analyzed to generate insights. For example, companies might analyze the data to detect patterns in tee time pricing, availability trends, or to identify the best times and rates for booking golf rounds.

Scraping can be done at various frequencies, from multiple times a day to weekly, depending on the need for real-time data and the policies of the target website. It’s a powerful tool for companies to automate the collection of vast amounts of data from the web, which can then be used for a wide range of analytical purposes.

Scraping can lead to market distortion by creating unfair competitive advantages and impacting the dynamics of the market in several ways:

  1. Information Asymmetry: When companies scrape data from tee time booking engines, they gain access to a wealth of information that may not be equally available to all market participants. This information asymmetry can give scrapers an edge in understanding market trends, pricing strategies, and customer demand, allowing them to make more informed decisions than their competitors who do not engage in scraping.
  2. Pricing Manipulation: Companies that scrape for pricing intelligence can use the data to undercut competitors by setting lower prices or to artificially inflate prices by understanding the maximum willingness to pay in the market. This can lead to a distorted market where prices are not solely determined by supply and demand but are influenced by the strategic actions of a few players with access to comprehensive market data.
  3. Barrier to Entry: New entrants may find it difficult to compete in a market where established players use scraping to continuously monitor and adjust their strategies based on comprehensive data insights. This can create a high barrier to entry, limiting competition and potentially leading to monopolistic or oligopolistic market structures.
  4. Resource Strain on Target Sites: Extensive scraping activities can put a significant strain on the resources of the targeted booking engines, affecting their ability to serve ordinary customers and maintain operational efficiency. This can disadvantage smaller golf courses or booking platforms that may not have the resources to counteract the effects of heavy scraping, leading to a competitive imbalance.
  5. Market Sensitivity and Volatility: The rapid and automated nature of scraping can lead to overreactions in the market. For instance, if scrapers quickly react to changes in tee time availability or pricing, it can cause sudden shifts in the market, leading to increased volatility and potentially destabilizing the market for both providers and consumers.

While scraping can provide valuable data for market analysis and strategic planning, its unregulated use can lead to unfair competitive advantages, distort market dynamics, create barriers to entry, strain resources, and increase market sensitivity and volatility, all of which can ultimately harm the overall health and fairness of the market.

Can start-ups like TenFore and MemberSports handle the costs of being scraped? Constant scraping can significantly strain the operational capabilities of tee time booking platforms, affecting their performance and the user experience for other customers in the following ways:

  1. Server Overload: Scraping involves automated bots sending frequent requests to the booking platform's server to extract data. If many bots are scraping the site simultaneously or if the scraping is done too frequently, it can lead to server overload. This excessive demand can consume a large portion of the server's resources, slowing down the website and leading to longer load times for all users.
  2. Increased Costs: The additional strain on servers due to scraping activities can lead to increased operational costs for the booking platforms. These costs arise from the need for additional bandwidth, server capacity, and security measures to handle the increased traffic and protect against potential threats associated with scraping activities.
  3. Degradation of Service Quality: As servers become overloaded, the quality of service provided by the booking platforms can degrade. This degradation can manifest as slow response times, errors in loading pages, or even system crashes. For customers trying to book tee times, these issues can result in a frustrating experience, potentially leading to lost bookings and damage to the platform’s reputation.
  4. Resource Diversion: To combat the effects of scraping, booking platforms may need to divert resources from other important areas, such as customer service, feature development, or marketing efforts, towards enhancing server capacity and implementing anti-scraping measures. This diversion can impede the platform's growth and innovation, affecting its long-term competitiveness.
  5. Security Risks: Constant scraping activities can also pose security risks. The need to differentiate between legitimate user traffic and scraper bots can lead to complex security challenges. In some cases, scrapers might exploit vulnerabilities in the website’s infrastructure, leading to potential data breaches or other security incidents.
  6. Legal and Compliance Issues: Dealing with scraping can also involve legal and compliance considerations, especially if the data being scraped is protected by copyright or if the scraping violates the terms of service of the platform. Addressing these issues can require significant legal expertise and resources.

Compare Dynamic Pricing Vendors

Privacy and security implications of scraping

Data privacy and security are significant concerns when it comes to the scraping of tee time booking engines, especially if personal information is involved. Here are the main issues:

  1. Unauthorized Access to Personal Data: When booking engines are scraped, there is a risk that personal information of individuals, such as names, contact details, and payment information, could be accessed without consent. This unauthorized access raises serious privacy concerns and can lead to violations of data protection regulations.
  2. Compliance with Data Protection Laws: Many regions have stringent data protection laws, such as the General Data Protection Regulation (GDPR) in the European Union or the California Consumer Privacy Act (CCPA) in the United States. These laws require that personal data be collected, used, and shared with consent and for legitimate purposes. Scraping activities that collect personal data without consent can result in legal penalties and damage to the company’s reputation.
  3. Security Risks: Scraping can expose booking platforms to increased security risks. Scrapers often probe different parts of a website to extract data, which can lead to the discovery of vulnerabilities in the site's security architecture. These vulnerabilities can then be exploited for more malicious activities, such as hacking or data breaches.
  4. Data Integrity and Misuse: The data collected through scraping may not always be accurate or may be taken out of context. This misrepresentation can lead to incorrect conclusions or decisions based on the scraped data. Moreover, if the data falls into the wrong hands, it could be used for fraudulent activities, leading to further privacy breaches.
  5. Resource Diversion for Data Protection: To counteract the risks associated with scraping, organizations must invest in robust security measures and data protection protocols. This often means diverting resources from other important projects to enhance security infrastructure, monitor data access, and ensure compliance with data protection laws.
  6. Erosion of Trust: Frequent incidents of data scraping, especially those involving personal information, can erode trust between users and the booking platforms. Users may become reluctant to use platforms they perceive as unable to protect their personal information, leading to a loss of business and reputation.

In light of these concerns, it is crucial for entities involved in scraping activities to consider the implications on data privacy and security. They must ensure that their practices are in line with legal standards and ethical considerations, safeguarding personal information from unauthorized access and misuse.

The debate over the fairness of using publicly available data through scraping, without the consent of the platform or its users, hinges on several key points:

Arguments for Fair Use

  • Public Accessibility: Proponents argue that if data is publicly accessible on the internet, it should be considered fair game for scraping. The information is already available for anyone to view, and scraping is merely a method of collecting this data more efficiently.
  • Innovation and Competition: Scraping can drive innovation and competition by allowing companies to use publicly available data to create new services or improve existing ones. This can lead to a more dynamic market and potentially better services for consumers.
  • Research and Analysis: Scraping is a valuable tool for researchers and analysts to collect large amounts of data for studies, market analysis, and trend forecasting. This use of data can contribute to academic, economic, and social advancements.

Arguments Against Fair Use

  • Violation of Terms of Service: Many websites have terms of service that explicitly prohibit scraping. Ignoring these terms can be seen as an unethical breach of contract, questioning the fairness of using data without consent, even if it's publicly available.
  • Potential Harm to Businesses: Scraping can harm the businesses being scraped by placing additional load on their servers, leading to increased operational costs and potentially degrading the service for other users. There's also the risk of competitive harm if the scraped data is used to undercut prices or copy services.
  • Privacy Concerns: Even if the data is publicly available, scraping can aggregate vast amounts of information, leading to privacy concerns, especially if personal data is collected and used without explicit consent from the individuals involved.
  • Intellectual Property Rights: Some argue that the data on a website, while publicly viewable, is the intellectual property of the site owner. Scraping this data without permission can infringe on these rights, especially if the data is used for commercial gain.

Balancing Interests

The debate often centers on finding a balance between the benefits of open access to information and the need to protect the interests of website owners and individuals. Ethical scraping practices, such as respecting robots.txt files (which tell scrapers which parts of a site can be scraped), adhering to terms of service, and not collecting personal data without consent, can help navigate the fine line between fair use and infringement. Legal frameworks like copyright and privacy laws also play a crucial role in defining the boundaries of fair use in the context of web scraping. There's an opportunity to create a Fair Scraping Agreement in the golf industry and publish who participates and who does not. This would serve to enhance any existing acts of fairness. Join the group HERE.

Downward pressure on pricing

The use of scraping for competitive price intelligence can indeed create a dynamic where two or more competitors continuously undercut each other, potentially leading to a "race to the bottom" in pricing. Here's how this scenario might unfold:

  1. Continuous Monitoring: Companies use scraping tools to constantly monitor the prices of their competitors. When one company detects a price reduction by another, it responds by lowering its own prices to remain competitive.
  2. Automatic Price Adjustments: Some businesses may employ dynamic pricing algorithms that automatically adjust their prices based on the data obtained through scraping. This can accelerate the cycle of price reductions, as these adjustments can happen in real-time or near real-time.
  3. Short-term Consumer Benefit: Initially, this competition can seem beneficial to golfers, as it leads to lower prices. However, the long-term implications might not be as positive.
  4. Erosion of Profit Margins: In a race to the bottom, companies continually undercut each other's prices, which can erode profit margins. While this may be sustainable in the short term, over the long term, it can lead to reduced financial stability for the companies involved.
  5. Reduced Investment in Services: With shrinking margins, companies might have less capital to invest in improving their services, maintaining quality, or innovating. This could lead to a decline in the overall quality of the services or products offered to consumers.
  6. Market Consolidation: In extreme cases, a prolonged race to the bottom could result in market consolidation, where only the largest or most financially resilient golf courses survive. Smaller businesses, unable to compete with continuously lowering prices, may be forced out of the market, reducing competition and potentially leading to higher prices in the future. This may be a reason why we see large management companies using scraping to pricing strategies.
  7. Sustainability Issues: The focus on maintaining the lowest price might lead companies to compromise on other important factors such as sustainability, employee wages, and working conditions, as they look for ways to cut costs further.

Options for success without scraping

To mitigate the negative impacts of a race to the bottom, companies may need to focus on differentiating their offerings through quality, customer service, or unique features rather than just competing on price. Additionally, regulatory interventions or industry standards could be introduced to prevent unsustainable pricing practices and ensure a healthy competitive environment.

Golf course operators have several options to manage the impact of scraping on their booking engines and to leverage technology to enhance their services:

  1. Opting Out of Scraping: For golf course operators who wish to prevent their booking engines from being scraped, a proactive step is to directly contact companies known for scraping activities and formally request that their data be excluded. This often involves legal and technical measures, such as sending cease and desist letters or configuring their websites’ robots.txt files to disallow scraping by certain user agents.
  2. Implementing Waitlist Functionality: To offer golfers the convenience of waitlist options without relying on external scrapers, golf courses can partner with technology providers like Golf Geek Software and Club Unity. These companies offer integrated waitlist features in their booking engines, allowing golf courses to manage high demand periods efficiently and improve the customer experience by offering potential booking slots as they become available.
  3. Adopting Dynamic Pricing Without Scraping: For golf courses interested in dynamic pricing strategies without the need to scrape competitors’ pricing data, working with specialized vendors like Golf Geek Software, Sagacity, and GolfBack can be beneficial. These vendors provide dynamic pricing tools that analyze the golf course's own supply and demand data, market trends, and other relevant factors to adjust tee time prices dynamically. This approach allows golf courses to optimize their pricing strategy based on their unique data and market position, rather than relying on competitive price intelligence gathered through scraping.

By exploring these options, golf course operators can better control their online presence, protect their data, and utilize advanced technology to improve their business operations and customer service. This strategy not only helps in maintaining fair competition but also ensures that the golf courses can leverage digital tools effectively to meet their business goals.

Several sources (golf course operators and golfers) contributed information for this article including: Ross Liggett, Metolius Golf

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