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Bots are a growing menace for eCommerce businesses across sectors including retail, travel, gaming, and more. Automated attacks hurt sales, steal data, and damage site infrastructure. Legacy defenses relying on behavior analysis and signatures fail against today's highly sophisticated bots mimicking human patterns.

A smarter approach is strategic deception using honeypots - traps that lure bots but have no production value. Integrating deception tactics into your defenses can divert and reveal attacks early while frustrating bot efforts.

Current good and bad bot detection falls short

 management solutions. These use various techniques to classify traffic as human or bot:

 - Bots get flagged for inhuman patterns like high click rates.

 - Known bot tools and patterns are recognized.

- Check for suspicious fingerprints like headless Chrome.

However, these approaches have severe limitations against modern bots:

Behavior analysis fails once bots mimic humans well.

Signatures only detect known bot tools. Newer tools go unnoticed.

False positives from incorrectly flagged humans disrupt business.

Updating detection patterns is complex and slow. Bots evolve rapidly.

Reactive approaches allow bots to attack before detection.

Due to these gaps, sneaky bots bypass legacy systems and hurt eCommerce businesses.

Ineffective bot management leads to major risks like:

Scalper bots quickly snap up limited inventory of hot products before real shoppers can buy them. This leads to PR backlash.

Scraping bots steal vast amounts of pricing data, product catalog information, customer reviews, and other original content. This undercuts competitive advantage.

Gift card fraudster bots check the validity of stolen card numbers and monetize active ones before merchants can react.

Bots attempt stolen username/password pairs on login forms to take over accounts and steal payment data.

Malicious bots overload servers with junk traffic, hurting site availability and performance.

Clicker bots generate fake ad clicks to inflate display ad costs.

Ticket scraping - Bots rapidly scrape ticket pricing and availability data from airline, hotel, and event sites. This undercuts competitive pricing strategies and drives up query costs.

Blocking seat/ticket inventory - Bots book seats or tickets en masse without purchasing, preventing real customers from accessing limited inventory and driving up prices.

Distorting analytics - Bots viewing listings without booking distort metrics like visitor counts used for marketing decisions.

Enabling account takeovers - Compromised loyalty program accounts let bots improperly access and use customer miles and points.

Reliance on OTAs - Airlines rely heavily on online travel agency bots for bookings, increasing their bot traffic and complexity.

Here are risks faced by the ticketing industry that can be faced with large volumes of traffic for key events:

Ticket scalping bots - Bots rapidly purchase tickets the moment they go on sale, making it difficult for real fans to buy tickets before resellers mark them up drastically. This draws public criticism.

Fake ticket botnets - Networks of bots impersonate customers to trick ticketing systems into issuing valid tickets that are sold illegally. This defrauds both ticketing companies and fans.

Price scraping - Bots continuously scrape ticket prices and availability to undermine competitive pricing strategies.

Ad click fraud - Bots generate fake ad clicks on ticket sale pages to artificially increase advertiser costs per click.

 to detect, deflect, or analyze malicious bot activity. As bots parse pages, execute links, and fill in forms, they can be detected and analyzed using honeypots. These honeypots are isolated, monitored traps mimicking real environments. These honeypots exist right on web pages as bots and users come to visit. Real users will not see the honeypots, but bots will detect and interact with a link or an additional button hidden in the web page, or through another honeypot trap. When bots interact with honeypots, it reveals their behavior so security teams can take defensive action.

Today’s honeypots are designed with advanced deception technology that complement legacy defenses. They are implemented by creating fake application pages like product listings and databases and making them highly visible to bots via links on real pages or SEO optimization. Bots will attempt to interact with these honeypots as they crawl and scrape sites, unaware they are fakes. Meanwhile, all activity with the honeypot is closely logged and analyzed. Based on what traps the bot falls for, mitigation responses can be crafted.

Here are some techniques honeypots use to attract and detect malicious bots:

Fake login page links to catch credential stuffing attacks.

Product pages with inaccurate data to divert scraping.

Fake gift card generators with valid codes to lure fraud bots.

Pages with spun content that seems unique to distract content scraping.

Bots aim to interact with as many application pages as possible to scrape valuable data or find vulnerabilities. Bots will hit fake product pages trying to extract pricing data, hit fake login forms with stolen credentials, and access fake databases. Without sophisticated logic to detect honeypots, bots fall for these traps revealing their presence and inner workings.

Why do honeypots have huge advantages over legacy detection?

 real users don't find or access honeypot areas

Bots get distracted exploring high-interaction honeypots instead of attacking production systems.

Attack footprints are captured as bots interact with traps. No need to wait for damage.

Easy to quickly deploy new traps mimicking latest targets. Bots get frustrated finding no value.

Low performance impact since traps are served selectively to suspicious visitors.

Honeypots provide 360-degree protection against various threats:

- Fake product and inventory pages divert scrapers. Generated content with spun text wastes scraper time and resources.

 - Honeypot login forms catch credential stuffing without locking out real users.

 - Fake gift card generators lure fraud bots allowing merchants to track and blacklist them.

 - Bots get distracted trying to scalp fake limited inventory honeypots.

 - Traffic to honeypots reduces attack load on production servers.

Most sites already use commercial bot mitigation services. The ideal approach is to complement legacy defenses with honeypots:

Handoff hard to detect sneaky bots to honeypots for diversion.

Reduce dependence on ineffective behavior analysis.

Detect more attack variants to update legacy tool signatures.

Retain backup protection if any bots get past the traps.

The advantages of the PhotonIQ Honeypot Service

Honeypot services like PhotonIQ Honeypot Service, powered by the 

, handle the complexity of building, deploying, and managing sophisticated traps tailored to each business's needs at the edge. PhotonIQ lets eCommerce businesses take a dynamic approach to outsmarting bots by using honeypot trap triggers to detect bots in real time.

Honeypots utilize various traps that are dynamically created and managed to attract and deceive bots. For example, unused form fields called "honeytokens" can be embedded within real applications. Enticing "honey files" like PDFs or documents are also deployed as bait for bots.

These honeypot traps are randomly placed across different pages. Their links, forms, fields and cookies are generated dynamically to stay one step ahead of bots and prevent them from learning to avoid the traps.

By continuously monitoring bot interactions with the honeypots in real-time, analytics can correlate which honey triggers to use to block future bots. These insights are applied to create and deploy new unpredictable traps as needed.

Bots are a complex and constantly evolving threat. But their own techniques can be turned against them using smart honeypots that lure and deceive them.

Adding this potent deception capability can help 

Proactively divert attacks instead of waiting to get hacked.

Outsmart persistent bots frustrating their efforts.

Extract valuable insights into emerging bot behaviors.

Strengthen defenses by complementing legacy tools.

Honeypots deliver a crucial edge against the bot menace. Fight back against bots on your terms with strategic honeypots. If you would like to learn more about how the PhotonIQ Honeypot Service can bolster your bot defenses, please schedule a chat with an 

Victorious warriors win first and then go to war, while defeated warriors go to war first and then seek to win." - Sun Tzu

Outsmarting Bots: How Honeypots Can Boost eCommerce Security

In today's data-driven world, seamless data connectivity is essential for businesses and organizations that want to harness the full potential of their data. Connectors play a pivotal role in enabling seamless data flow between various systems and databases.

In this blog post, we will explore Macrometa Connectors that allow you to extract and send data to and from existing collections in different databases and services. Whether you're working with BigQuery, MongoDB, OracleDB, PostgreSQL, or Snowflake, Macrometa Connectors have you covered. We'll go over each connector type and how to get started. But first let’s talk about how data works within the Global Data Mesh, a component of the Macrometa Global Data Network (GDN).

 is a hyper distributed cloud that has three components: 

. Macrometa takes a new approach to data by combining free-flowing data, analytics, and low latency for real-time insights.

The Global Data Mesh breaks down data silos to make information easily discoverable, accessible, secure, and usable anywhere. Connectors further simplify the data mesh approach, allowing companies to connect data from common databases and other sources. Edge Compute puts that data into action, and Data Protection offers data privacy and sovereignty.

 bridge your data across a variety of databases or Macrometa document collections. These connectors are designed to facilitate data extraction and data transfer, making it easier to work with your existing datasets.

empowers you to seamlessly interact with your BigQuery collections. You can effortlessly extract data from or send data to an existing BigQuery collection, streamlining your data workflows.

 allows you to work with data from any Macrometa document collection, regardless of its location within a 

 or even in a different tenant. This connector provides the flexibility you need to access and manage your data efficiently. You can send data to and from a Macrometa document collection.

, Macrometa offers a dedicated connector to extract data from or send data to your existing MongoDB collection. Seamlessly integrate your data for more comprehensive insights.

 simplifies data transfer from your OracleDB collection. Enjoy efficient data management with this connector.

, Macrometa's connector is here to assist. Extract data from or send data to your existing Postgres database with ease.

 users can take advantage of Macrometa's connector to extract data from or send data to their Snowflake collections. Ensure your data operations are seamless and efficient.

Macrometa Connectors are a valuable resource for simplifying data workflows and ensuring efficient data management. Macrometa customers can get started by contacting 

 to have it added to their tenant, since the feature is currently in beta.* Be sure to check out 

 for more information on the fields, functionality, and other options. If you need more information about Macrometa, please reach out to 

. We look forward to speaking with you!

*See 

Bridging Data With Macrometa’s Connectors

As we wrap up the summer season and check off the back to school list, the countdown is on to the busiest sales period in US eCommerce. Traffic can surge up to 

 during Cyber 5. Retailers risk losing millions if sites experience disruptions or delays over the Black Friday weekend.

and shoppers ready to splurge, Cyber 5 can account for a significant part of annual revenue. A 2021 

 showed shoppers plan to spend 50% of holiday budgets during Cyber 5. However, consumers can’t buy when a site goes down. And 50% won’t stick around if pages take 

The Cyber 5 peak shopping period puts eCommerce infrastructure through the ultimate stress test and any consequences can have a long lasting impact. The key is taking action now to improve website resilience, get control of bots, optimize virtual waiting rooms, safeguard coupons, and improve performance even at scale.

Say bye to "bad" bots, DDoS attacks, and peak traffic crashes

Modern eCommerce landscapes often experience overwhelming traffic surges during promotions, pushing websites to the brink of crashing. Virtual waiting rooms emerge as a remedy by effectively regulating user access and preventing overloads, ensuring stability even during peak demand. This proactive approach safeguards smooth user experiences and cultivates loyalty by reducing frustration during spikes.

While managing traffic is a necessity, it's worth noting that not all visitors are genuine customers. In the midst of the Black Friday shopping frenzy, virtual waiting rooms play a pivotal role in filtering out approximately 

 attributed to bots and fake users, conserving valuable computing resources for authentic customers. Furthermore, these waiting rooms act as a deterrent to bots attempting to hoard limited-stock items for resale, preserving fair access for actual shoppers.

, exploiting legitimate traffic to mask malicious activities. By distinguishing and filtering out such traffic, virtual waiting rooms bolster the overall security of platforms.

 seek discounts and offers when deciding to buy from a retailer or brand. This trend intensifies during the holiday season, as 

 businesses compete to capture consumers' attention with irresistible deals.

Securing these incentives is vital, striking a balance between engaging users and curbing misuse. Fraud prevention is key to tackling code exploitation. Careful tracking mechanisms are essential to deter misuse proactively.

In the anonymity of online shopping, unclear customer details enable easier coupon abuse, damaging profits. 

 counters this by assigning unique identifiers to track coupon usage without cookies. Each coupon receives its own distinct fingerprint made of letters, numbers and symbols, linking it to transactions or users.

During redemption, the system checks the coupon's fingerprint against valid codes, foiling counterfeits by comparing fingerprints. Over time, it spots suspicious patterns like identical prints by multiple users - indicating potential fraud. With 

, fingerprinting detects odd behaviors, triggering alerts to resolve disputes. Fingerprinting enhances coupon security and traceability.

Ecommerce website optimization is now essential

Fast website performance isn't just a choice – it's a competitive necessity. Users expect quick, seamless experiences, and delays lead to lost conversions and revenue. Extensive research confirms the link between site speed and business success. Sites loading in a second see 

 and even a 0.1-second speed improvement can mean an 

 say page speed affects their buying decision. However, large eCommerce businesses and retailers face complex challenges in maintaining fast site speed at scale. Fragmented efforts and legacy tech can complicate matters. Automated performance proxies offer a unique solution to optimize pages and assets on-the-fly from any device, at scale.

The edge advantage: Macrometa eCommerce & retail solutions

Navigating the ever-changing digital landscape of 

 requires prioritizing exceptional user experiences and robust defenses against online threats. From enhancing fraud detection and site resilience to driving up performance, Macrometa’s real-time approach addresses the diverse challenges of eCommerce and retail.

Optimize experiences and defenses with virtual waiting room services

Beyond limiting users and filtering traffic to help thwart DDoS attacks and bots, Macrometa’s Virtual Waiting Room Services act as an effective buffer between users and origin services to ensure optimal performance. A continuous feedback mechanism dynamically adjusts the dequeuing rates, while a seamless user experience and fairness in resource allocation are maintained. Upon visiting the waiting room page, users are informed of wait times and queue status in real time. Administrators can see valuable insights into user behavior and queue metrics, and receive threshold alerts. 

Enhance user tracking and fraud detection with fingerprinting

Macrometa’s Fingerprinting creates non-cookie identifiers from browser attributes to identify customers. Fingerprint profiles update in real time instead of becoming stale. Advanced machine learning models strengthen accuracy, address fingerprint shifts, and detect spoofing or misuse like coupon fraud. This is critical during sales events when attackers are active and consumers may misunderstand coupon rules. With responsible fingerprinting, Macrometa empowers companies to maintain personalized experiences while adhering to privacy regulations. The solution uses lightweight code to minimize performance impact, unlike heavy fingerprinting scripts.

Drive up page loads, performance, and revenue

Macrometa's PhontonIQ Performance Proxy (P3)

 optimizes delivery between CDN and origin infrastructure. PhotonIQ employs AI optimization, edge processing, and holistic monitoring to dramatically improve site speed. Running on Macrometa’s 

 (GDN) of edge nodes, P3 accelerates your site transparently without any changes to code and works seamlessly with existing infrastructure and apps. Unique capabilities include AI-Powered dynamic page optimization that can increase site speed over 70% and significantly boost Core Web Vitals scores - even at scale.

Get ready for the holiday season in just 60 days!

Learn about Macrometa’s AI-powered solutions, which are designed to boost website resiliency, effectively manage bots, protect coupons, and streamline virtual waiting rooms. Or 

 today to ensure uptime and peak performance during the holiday sales crunch.

Holiday Countdown: Optimize eCommerce Defenses & Performance

Edge Side Tag Management Series

Welcome back to our series on tag management! In our previous post, we looked at traditional tag management approaches including their benefits and limitations. Now, we’ll explore edge side tag management - and how it aims to provide improved flexibility, speed, scale, and control.

In this post, we’ll examine the benefits of edge side tagging, including instant iteration, built-in redundancy, and enhanced performance. Let’s dive into the potential opportunities edge side tag management enables for digital teams and then cover Macrometa’s PhotonIQ solution.

Massive opportunity of edge side tag management

 - offers a vastly superior approach compared to browser-based and centralized server side models.

With edge side tag management, tags are executed within cloud functions distributed globally at the network edge: By running tags as close as possible to 

, edge side architecture provides unmatched benefits:

Tags can fire at the first network request before anything is sent to origin servers. You get full insight into the entire 

No more tag traffic needs to flow back to central servers. Pages load faster.

- Custom code can be executed at the edge to customize tag logic and capabilities.

 - Data stays within your controlled edge environment instead of leaking to external tags or central servers.

 Changes deploy at the edge in seconds without centralized release processes.

 - Stateless edge servers easily scale to handle spikes without provisioning delays.

- Edge networks provide native redundancy across data centers and regions.

For all these reasons, leading digital organizations are adopting edge side tag management to achieve new levels of flexibility, performance, scale, and cost efficiency.

Introducing PhotonIQ - edge side tag management from Macrometa

Macrometa provides a cloud native edge side tag management called PhotonIQ as part of their dynamic site performance acceleration suite built on its 

With PhotonIQ, tags execute within isolated secure edge functions distributed across 

 globally. This geo-distributed architecture brings tag management to the edge near end users.

 PhotonIQ executes tags in <50ms at the edge for real-time data flow.

 - Send tag data to tools like Google Analytics, Amplitude, Snowplow, Segment out-of-the-box.

 (streaming and complex event processing engine within Macrometa) with Javascript capability allows edge side tags to do things impossible in browser solutions.

- Deploy tags across global regions to keep traffic local and redundant.

 - View tag performance, traffic, errors, and more through PhotonIQ dashboards.

 Update tags and business logic in seconds without any backend deployments.

For digital teams, PhotonIQ provides an enterprise-grade edge side tag management system that's simple, flexible, and affordable. Organizations gain fine-grained control without the DevOps overhead.

Benefits of edge side tag management with PhotonIQ

Migrating to PhotonIQ edge side tag management creates tremendous business value including:

 - Capture every user action from the first network call for perfectly accurate 

 by 50% or more by eliminating excess tag requests and trips to central servers.

 - Roll out new tags, experiments, and experiences in seconds without engineering bottlenecks.

 - Gain visibility into tag performance, sequencing, and data to build organization-wide trust.

- Reduce developer time spent on tag management by 90% or more. Focus talent on innovation.

 - Keep data within your controlled edge environment to meet 

 - Scale to billions of tag executions per month without architecture limits or DevOps delays.

 - Distribute tags globally to cut latency and keep traffic within regions.

Tag management has evolved from early browser-based solutions to centralized servers and now next-generation edge side models like Macrometa's PhotonIQ.

For organizations where customer experience, developer productivity, and marketing agility are critical to growth, PhotonIQ 

By executing tags at the edge globally, PhotonIQ overcomes the constraints of legacy solutions to provide flexibility and scale not possible just 24 months ago. For digital teams racing to convert, engage, and retain users, PhotonIQ edge side tag management is the future. Learn more today by chatting with a 

Unlocking Speed With Edge Side Tag Management

Tag management is now essential infrastructure for digital analytics, marketing optimization, and personalization. However, legacy browser-based tag management has major limitations in flexibility, performance, accuracy, and control for websites.

This blog examines the role and value of tag management, compares architectures and sets the stage for the transformative benefits edge side tagging delivers for modern digital enterprises.

Tags are snippets of tracking code used to collect data on visitor and customer actions on websites, apps and other digital touchpoints. Tags enable real-time data collection to understand digital experiences and optimize business outcomes.

Tag management systems (TMS) provide a way to deploy and manage tags used for tracking, 

, advertising, and more. With a TMS, tags can be managed from a central interface instead of hard-coding them on every page.

Tag management enables connecting insights across 

, audiences and systems to improve experiences end-to-end.

Key benefits of tag management include faster implementation, improved consistency, enhanced flexibility, lower risk, and optimized 

. With these advantages, the majority of large companies rely on tag management solutions to deliver high ROI.

However, traditional browser-based tag management (i.e., client-side tag management) has major limitations in today's business environment.

The high hidden costs of browser tag management

Since the early days of tag management, solutions have relied on a browser-based architecture. With this model, the TMS script is loaded in the header of web pages. This script asynchronously requests tags from a central server and loads them into the page after the initial HTML is parsed.

This offers obvious benefits over hard-coded tags. But there are also serious limitations including:

 -  Browser tags load late in the page request lifecycle, after the initial HTML is returned. This means key user actions like Initial 

 timing, time to first click, early page scrolling and engagement etc are missed. Without capturing these vital events, your analytics data will be incomplete and inaccurate. Critical parts of the user journey are lost.

 - While asynchronous browser tags seem "invisible", they still require additional HTTP requests and JavaScript execution that blocks other downloads and slows page rendering. This drag on performance hurts 

- External tag management systems have full access to fire tracking pixels and cookies on your site with little visibility or control from your end. This introduces security vulnerabilities and 

 - Although easier than hard-coded tags, deploying new tags in browser-based systems still often requires QA and troubleshooting support from your development teams. This bottleneck limits your ability to make rapid changes to support agile optimization and experimentation.

 - Browser tag management only allows packaged JavaScript tags. There's no ability to run custom code for advanced logic. This curtails innovation, such as creating enhanced tags with edge computing capabilities.

With the limitations of browser-based tagging exposed, many companies have explored centralized server side tag management solutions. With this model, tags are executed on a dedicated tag server, cloud-based TMS, or within backend application servers.

Tags can fire earlier before the HTML response is sent, improving data capture.

Tag management is controlled in your own infrastructure.

No frontend website changes are required.

However, centralized server side tagging has significant pitfalls:

- While tags fire earlier, you still have increased latency from the extra network hop to the central TMS server. 

 - Scaling requires procuring more centralized tag management infrastructure to handle traffic spikes. Costs grow rapidly.

 - New tags still need to be deployed on centralized servers. Agility is curtailed, especially for globally distributed teams.

 - A failure in the tagging server or zone can disrupt data collection across all traffic. Redundancy requires even more infrastructure.

In summary, centralized server side tagging improves data capture over browser-based solutions, but still falls short in achieving maximum performance, scalability, reliability, and deployment velocity.

Edge side tag management offers a superior model compared to browser and centralized server options. With edge side tagging, tag execution happens globally at the network edge near 

. This unlocks major advantages we’ll explore in Part 2 such as:

For organizations where customer experience and agility are critical, edge side tag management delivers the next evolution. In Part 2 of this series, we’ll do a deep dive into the benefits of edge side tagging, how it works, and introduce Macrometa’s 

. Stay tuned! If you want to learn more about Macrometa’s PhotonIQ solutions, chat with a 

The Evolution And Limitations of Tag Management - From Slow Pages To Fast Revenue

Data protection is a critical aspect of any organization's data strategy, and in today's world, it is becoming increasingly important. In 

Unlocking Speed With Edge Side Tag Management

Outsmarting Bots: How Honeypots Can Boost eCommerce Security

Bridging Data With Macrometa’s Connectors

Holiday Countdown: Optimize eCommerce Defenses & Performance

Unlocking Speed With Edge Side Tag Management

The Evolution And Limitations of Tag Management - From Slow Pages To Fast Revenue

Data Protection In The Age Of Stringent Privacy Regulations And Cyber Threats

The Advantages of Ready-To-Go Solutions Vs. From Scratch Solutions

Emotional Personalization: The Secret to Boosting eCommerce Sales

Device Fingerprinting for eCommerce: An Overview