Hi! Today I want to share a short case study about using Binom Protect.
A small private ad network reached out to the Binom team — they had started receiving bot traffic complaints from advertisers.
The team allocated a test volume of clicks, and we got to work. First, we configured the publisher ID to be passed into Token 1 in Binom:
added an extra column to the stats showing the percentage of bot traffic:
Traffic run dates: October 20 – November 10, 2025.
After several experiments with Binom Protect settings (the parameters and their combinations were adjusted manually to avoid cutting off good traffic), we’ve got the following settings:
Now, we can identify the main bot-generating publishers in the stats:
Using the drilldown feature, we can dive into each publisher and see on which GEOs and devices the bot traffic appears. In this case we discovered that the publisher was completely inflating traffic from some of the most expensive US and UK GEOs.
Our colleagues from the ad network talked with the advertisers, collected statistics on their side, and concluded that the obtained data could be extrapolated to the publisher’s entire traffic volume and that their payout should be reduced proportionally to the fraud percentage.
Thus, Binom Protect helps filter out low-quality traffic and increase business profitability.