What Bot Traffic Is
Bot traffic is any activity in your funnel produced by software rather than a person. In the context of mobile campaigns, that means automated ad clicks, scripted app installs and fake in-app events that are counted, attributed and often paid for as if real users had produced them.
Not every bot is a problem. Your website gets visits from search crawlers, link previewers and AI assistants every day, and many of those are welcome. Bot traffic becomes fraud when it imitates users inside a paid funnel to collect payouts.
Types of Mobile Ad Bots
Bots range from crude to sophisticated. The simplest are click bots that hit tracking links from servers, producing large volumes of clicks in the hope that some coincide with real installs, a pattern known as click flooding or click spamming.
A step up are emulator and device bots, which run your app on emulated or real hardware under script control. They produce installs that look physical, and can complete onboarding or registration steps. Device farms that automate their phones fall into this group.
Then there are server-side bots that skip the device entirely and send fabricated SDK requests to the MMP, known as SDK spoofing. Finally, malware on real users' phones can open ads, click links or fire install-time clicks in the background, mixing bot behavior into otherwise genuine traffic.
How Bot Traffic Distorts Your Numbers
Bots do more damage than the payouts they collect. Fake clicks inflate click volumes and drag down conversion rates. Fake installs inflate install counts and drag down retention and revenue per install. Stolen attribution moves organic installs into paid columns.
The second-order effects are worse. Ad platforms that receive bot conversions through postbacks learn to buy more of that traffic. Your cohort reports mix bots with users, so LTV estimates fall and budget decisions shift. A channel can look like it is scaling when it is mostly feeding automation.
Signals That Expose Bots
Network origin is the first check. Real phone users connect through mobile carriers and home broadband, not data centers. Clicks and installs from hosting providers, cloud ranges or Tor exit nodes are rarely human.
Timing is the second. People are irregular. Bots often act at fixed intervals, complete events in the same sequence with the same gaps, or produce flat click-to-install time distributions. Device data is the third: an unusual concentration of models, OS versions, screen sizes or languages that do not match your normal audience.
Behavior is the final test. Bots rarely sustain activity. A source with normal install volume but almost no second-day sessions, no purchases and identical event paths is not sending people.
Flagging Bot Traffic in Linkrunner
Linkrunner's Fraud Control uses data-center and Tor IP lists maintained by the engine, rules for click flooding by IP and by device, SDK spoofing templates and SDK request signing. You can describe a rule in plain English, preview how many past installs it would have caught, and set it to tag installs or withhold postbacks so ad networks stop optimising toward that traffic. Flagged installs remain in reporting totals for review rather than disappearing. See fraud protection for the full rule library.
Reducing Bot Exposure
Bots follow money, so look at where your money goes. Sources paid per click or per install with little oversight attract the most automation. Ask networks for sub-publisher transparency, review new sources closely in their first weeks, and pay on deeper events where you can. Keep fraud rules running continuously rather than as a one-off audit, because bot operators move to new sources and IP ranges as soon as old ones are blocked.
Bot Traffic on Your Website vs in Your Campaigns
Website bot traffic and campaign bot traffic are related but separate problems. On your website, bots include search crawlers, AI assistants fetching pages to answer questions, uptime monitors and scrapers. Many are useful: search and AI crawlers are how people find you. You manage them with robots rules, rate limits and bot management tools, and you usually exclude them from analytics so they do not inflate visits.
In campaigns, bots are almost always a cost. They click your ads, trigger your attribution links and sometimes produce installs and events that look like users. Excluding them from reports is not enough, because the damage is already done once a network has been paid and its algorithm has learned from the conversion.
Keep the two separate in your processes. Web analytics filters protect your dashboards; fraud rules and postback controls protect your ad spend and the signals you send to ad platforms. Treating campaign bots with website tools, or the other way round, leaves gaps.