How Burton proactively stopped 4K+ scam websites before they could steal its customers’ payment details

By combining instant URL triggers, AI-driven detection, and predictive scoring, Burton began removing fake websites instantly before their customers could even find them, preventing over 5k fraudulent transactions from occurring and preserving trust in the brand.

Overview

Burton has shaped snowboarding culture for over 40 years. With a loyal global community and a digital-first retail model, trust is core to the brand.

But as momentum grew, so did imitation. Customers began reporting that they’d purchased from websites they believed were Burton, only to discover their payment information had been stolen or orders never arrived.

To protect riders online and avoid reputational damage, Burton needed a way to stop fake sites before customers encountered them.

The Challenge

Burton’s team initially tried to tackle fake sites manually. They searched, reported, and escalated individual cases, only to watch new scam domains appear just as quickly.
There was no scalable process, no automation, and no proactive detection. The brand only saw scams after a customer was harmed.

Burton needed a systematic, always-on approach that could operate faster than fraudsters without pulling the team into constant manual work.

“We needed always-on detection, faster enforcement, and centralized reporting.”
Andrea Richiardone, Omni E-Commerce Operations Specialist

The Turning Point

The shift came when the Burton team saw that automated enforcement and URL-based triggers could stop fraud before it reached its customers.

Instead of checking each suspicious site manually, Burton could automatically detect domains containing “Burton,” instantly route them to enforcement, and surface other high-risk domains via machine-learning signals.

This moved the team out of firefighting mode, and into proactive protection.

The Solution

Automated rules and AI to spot fake sites the moment they appear
Burton combined smart rules with AI to catch scam domains automatically instead of reviewing them one by one.

• Any website that includes “Burton” in the URL is instantly flagged and submitted for enforcement, stopping obvious impersonation sites without manual review.
• In parallel, AI scans the web for suspicious patterns (like sites that copy Burton’s layout, product images, or pricing), even if “Burton” isn’t mentioned in the domain.
• This helps uncover multi-brand fraud stores and disguised copycat sites that traditional URL monitoring alone would miss.

Together, these controls replaced manual checks with proactive, always-on detection.

Deny/Allow lists and infringement prediction to focus on the right threats
To avoid noise and move quickly, Burton layered prioritization rules on top:

• Allow lists confirm trusted partners so they never get flagged by accident
• Deny lists immediately block known unauthorized sellers or repeat offenders
• AI-based infringement scoring ranks new incidents by likelihood of fraud, surfacing high-risk sites first
This let Burton spend time only where it mattered, instead of sifting through every alert.

Strategic CSM partnership to improve accuracy
Burton partnered closely with Red Points to refine rules and strengthen validations, leading to a +40% in enforcement accuracy and faster takedown cycles across their program.

“Now enforcement happens way faster, saving us time and letting us focus on strategic work instead of repetitive takedowns.”
Andrea Richiardone, Omni E-Commerce Operations Specialist

The Result

Burton evolved from reactive to proactive enforcement that protects customers before they can find the scam websites.

As a result, Burton received fewer scam-related customer complaints, and fraud attempts no longer stretched internal resources.

With monitoring running continuously, Burton can focus on growth and innovation, knowing protection scales with it.