Already sold out? Stop bots derailing limited sales.
Limited and rare items, like special edition sneakers, are coveted by fans and collectors alike. The more exclusive and unique they are, the more the obsession grows. The fashion and lifestyle industry uses artificial scarcity, also known as a “drop”, to boost sales and provide exclusive brand experiences. Resellers can and do exploit this, reselling products for several times their original value. You might be thinking, “Kerching!”. But this is really an unwanted side effect – one which more and more companies are taking technical steps to tackle.
Spot the bot
Special sneakers or fashion products by “Supreme” harness the principle of supply and demand intelligently. They’re only sold at certain locations, at specific times, and in a limited quantity. This practice is highly effective. In seconds, they’re sold out! Similar offers are available online and resellers snap up these branded products hungrily.
To do this, they increasingly use automated programs (bots), grabbing sought-after items at lightning speed. Mass use of these bots results in poor store page performance, as a flood of orders are submitted in a short timeframe. That means real fans, itching to buy, get left with empty shopping carts. Even if the shop sells out, companies need limited products to end up in the hands of genuine fans, as this promotes brand loyalty. To successfully run limited drops, they must prevent store visits by bots.
Here are some live bots and how to recognize them
Prevent and protect
By using technical analyses, you can spot bots and block them at different points of the order process. Here are some methods we use.
- Behavior pattern analysis - User behavior on the website is analyzed for suspicious activity. A normal user clicks through products and is unsure what to buy. By contrast, bots move deliberately and with precision, revealing their presence.
- Speed analysis - The speed at which bots connect to and open webpages is much faster than a person can achieve. Unlike a real-world robber, their pace makes them easier to catch.
- User-agent header analysis - Many bots use similar user-agent headers. It pays to compare them with known signatures or those already flagged as suspicious.
- IP address analysis - IP addresses can be compared with those from known botnets and either blocked or allowed.
- Long-term analysis - The behavior of some bots can be categorized by connection requests, actions and activity time. For example, if certain connections are made at certain times of day – and they visit the same websites every time – they may be bots. Even the biggest superfan isn’t likely to have this schedule.
- Browser analysis - JavaScript libraries can force a requesting system to solve mathematical problems. A browser can provide answers. Meanwhile, bots are equipped with minimal functions and so cannot respond.
- Anomaly analysis - Requests can be checked for word sequences, typing errors, format, double spaces and other imperfections – the kinds only found in a certain bot network.