[GUIDE] How to Tell Good Bots from Bad Bots
Picture this: a ticketing platform is hit with a wave of automated traffic seconds after tickets go on sale. A retailer sees inventory vanish during a product drop. A travel site notices unusual sequences of activity before bookings.
In the past, the solution was simple: block all bots.
But commerce has changed. Agentic AI has blurred the lines between good and bad automation. Some bots really are malicious, exploiting your systems for fraud or resale. Some are essential, like search crawlers or QA scripts. And some are actually buyers – automated agents making legitimate purchases on behalf of customers.
The challenge is telling them apart.
When all automated traffic gets treated the same, two things happen:
- Good automation gets blocked. False positives, lost revenue, and customers who may never return.
- Bad automation gets through. Fraud, chargebacks, and abuse pile up downstream.
The focus has to shift from detection alone to understanding intent. That means:
- Looking at behavior across sessions, not just at login or checkout
- Persisting identity even when devices, IPs, or accounts change
- Deciding based on context so you can approve the right traffic quickly and stop the wrong traffic before it escalates
In How to Tell Good Bots from Bad Bots, you'll learn more about the three types of automation you’re seeing today, why legacy signals break down against Agentic AI, and how intent-based detection works in practice.
Download here.
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Be'Anka Ashaolu is the Senior Marketing Manager at Spec, the leading customer journey security platform leveraging 14x more data to uncover fraud that others miss. With over a decade of experience driving growth for B2B SaaS companies, she has built a reputation for developing high-impact strategies that fuel demand and elevate brand visibility. Be'Anka earned her degree with honors from Saint Mary’s College of California, majoring in Communications with a minor in English.
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