How to Identify Bot Traffic in Adobe Analytics

Based on Adobe's Analytics documentation (bot removal page updated 28 September 2026, bot rules page updated 26 May 2026), reviewed on 9 October 2026. Menu names can change, so check Adobe's current docs.

Quick Answer

To identify bot traffic in Adobe Analytics: (1) enable IAB bot filtering and review the Bots and Bot Pages reports to see what Adobe already catches; (2) in Analysis Workspace, break your traffic down by source and by bot-like characteristics such as single-page visits, unusual or unknown user agents and devices, missing referrers, new visitors and odd landing pages; (3) build a segment that combines several of those signals, because no single one is reliable; (4) cross-check the suspicious sources against click counts and conversion quality from the ad network; and (5) block what you can with custom bot rules (user agent, IP, IP range) or Adobe's ECID and Bot Flag method. A reply on Adobe's Experience League community puts it bluntly: no method identifies bots with 100% accuracy. And finding bots in Adobe cleans your reports but does not stop you paying for the clicks. If you buy traffic on adult or alternative ad networks, JuicyTraffic provides click fraud protection and ad tracking built for that traffic.

Why Most Adobe Bot Guides Fall Short

Search this question and you find three kinds of content. Generic advice such as "look for spikes and high bounce rates." Admin documentation that explains how to remove bots. And a few practitioner posts, such as one using a custom eVar set from a user-agent match. What's missing is a workflow for the person who buys traffic: how to tell which paid source is sending automated visits, and what to do beyond cleaning the report.

This guide covers that.

Step 1: See What Adobe Already Filters

Go to Analytics > Admin > Report Suites > Edit Settings > General > Bot Rules. You have two built-in options:

**Enable IAB Bot Filtering Rules.**This uses the IAB's International Spiders & Bots List, which Adobe updates monthly. Adobe recommends selecting it at a minimum. Adobe cannot share the detailed list, but the Botsreport shows which bots have accessed your site.
**Custom bot rules.**Rules based on user agent(starts with or contains), IP address(wildcards allowed) or IP range. The interface allows up to 500 manual rules, after which you manage rules in bulk through CSV import and export. Multiple conditions in one rule combine with "or." A new rule takes effect within about 30 minutes.

Know what this means before you rely on it:

Traffic that matches a rule is not collected in the report suite or included in traffic metrics. It is stored separately and shown only in the Bots and Bot Pages reports.
The IAB list is based solely on user agent. A bot that presents itself as an ordinary browser is not caught by it.
Removing bots typically lowers traffic and conversion volumes and often raises conversion rates, so tell stakeholders first. Adobe suggests trying it on a small report suite to estimate the impact.
Hits marked as bots are still billed as server calls.
Adobe Analytics' bot detection is separate from the bot detection service on Adobe's Edge Network, although both use the same IAB list.

Step 2: Break Down Your Traffic by Source

Open Analysis Workspace and build a freeform table with your campaign or tracking code dimension, or your marketing channel, as rows. Add visits, page views, bounce rate or single-page visits, time spent, and conversions. Then break each suspicious source down by:

Dimension	Why it can reveal automation
Country and city	Traffic from places you don't target, or concentrated in one city
Browser and operating system	Very old versions, or an unusually high "unknown" share
Monitor resolution	A spike in low or odd resolutions
Referring domain	Large volumes of direct or typed/bookmarked traffic
Entry page	Visits all landing on a page real users rarely start from
Hour of day	Activity at hours that don't match your audience

Adobe's own guide lists the behaviours that tend to define bots: single-access visits, unusual user agents, unknown device or browser information, no referrers, new visitors and unusual landing pages.

Step 3: Build a Bot-Like Segment, and Combine Signals

Build a segment in Analysis Workspace that uses several of those conditions together. Each one on its own is common among real users. A single-page visit with no referrer from a first-time visitor is ordinary. Combine three or four and the picture changes.

A practical approach, used by some practitioners, is to build two tiers:

**Likely bot:**matches two or three signals.
**Rule-matched bot:**matches a declared bot user agent or an investigated IP range; check for false positives.

Then measure how much of each source's traffic falls in each tier. Some analysts call this a "bottiness rate." Measure changes in the same report suite over time, using a consistent segment definition.

**Watch out for false positives.**Single-page visits can be normal for content sites. Many users arrive with no referrer. And an IP address is not always unique to one person: Google notes that offices, universities and mobile carriers share one public IP across many devices, which applies equally here.

Step 4: Cross-Check Against the Ad Network

Adobe shows what reached your site. The ad network shows what you paid for. Compare them by tracking code:

**Clicks paid versus visits recorded.**A large gap can mean clicks that never loaded a page. Some discrepancy is normal, since ad platforms and analytics count differently, so look for sources that are far out of line with the others.
**Conversion quality.**Check whether leads or sign-ups from a source contain fake or duplicated details.
**Pattern by sub-source.**If your network lets you tag placements or sub-IDs, check whether the bot-like segment concentrates in a few.
**Server logs and IP concentration.**Useful for confirming a custom rule is worth writing.

Step 5: Act on What You Find

**For obvious cases:**add a custom bot rule on user agent, IP address or IP range. If you have IP obfuscation enabled and the last octet is removed, Adobe notes that rules should be written to match addresses ending in zero.

**For bots that slip past rules:**use Adobe's layered method:

Pass the visitor's Experience Cloud ID into a new declared ID.
Use segmentation in Analysis Workspace to identify bot-like visitors.
Export the Experience Cloud IDs for that segment through Data Warehouse.
Upload them as a customer attribute, with a "Bot Flag" column.
Create a segment that excludes the flagged IDs.
Apply it as the filter on a virtual report suite.
Repeat regularly. Adobe suggests at least monthly.

**At the source:**pause or exclude the sub-sources and placements that your cross-check flags, and ask the network to review them.

The Limit of Finding Bots in Adobe

Everything above fixes your reporting. It does not recover the money already spent, and it does not stop the same visits from firing other pixels and tags. Some analysts make this point directly: by the time a visit is recognised as a bot, the data may already have reached your analytics, ad platforms and other tools.

That is why identification inside analytics works best as a second line of defence. The first is catching invalid clicks where they are bought. For advertisers on adult and alternative ad networks, JuicyTraffic provides click fraud protection and ad tracking built for adult traffic, investigating landing-page click quality by campaign, source and placement with per-click evidence. It requires a tracking link and an on-site probe; automatic responses depend on supported integrations and configuration.

FAQ

Does Adobe Analytics filter bots automatically? Only if you enable it. The IAB bot filtering option is a checkbox in the report suite's Bot Rules settings, and Adobe recommends turning it on at a minimum.

Where can I see the bots Adobe removed? In the Bots and Bot Pages reports. Removed traffic is not included in your normal reports.

Does the IAB list catch click fraud? Only declared bots and spiders. The list matches on user agent, so traffic that looks like an ordinary browser needs segmentation or custom rules.

How long do custom bot rules take to apply? Adobe says a saved change should take effect within about 30 minutes. Rules apply to incoming data, and cleaning historical reporting uses the customer attribute method instead.

How many custom bot rules can I add? The interface allows 500 manually defined rules. Beyond that, manage rules in bulk through CSV import and export.

Are bot hits still billed? Adobe says hits marked as bots are billed as server calls.

Can I identify bots with certainty? No. A reply on Adobe's Experience League community says no approach identifies bots with 100% accuracy. Combine signals and treat results as likely rather than proven.

What about AI agents and crawlers? Practitioners recommend looking for "bot" or "crawler" in the user agent and adding a custom parameter to tag AI-referred traffic, then building separate "likely bot" and "rule-matched bot" segments.

Will blocking IPs in Adobe stop bots from costing me money? No. It stops them appearing in your reports. To stop paying for them, act on the ad network or with click fraud protection at the point of purchase.

Next Steps

Adobe gives you solid tools to see and remove bot traffic from your reports: IAB filtering, custom rules, segmentation and the ECID and Bot Flag method. Use them together, and cross-check paid sources against what the network billed you. Just remember that clean reports are not the same as protected spend. If your traffic comes from adult or alternative ad networks, JuicyTraffic provides click fraud protection and ad tracking built for adult traffic, to help you investigate suspicious sources and decide where to act.

For a practical next step, How to Stop and Block Bot Traffic on Your Website.

Official References

About the Author

Dylan Dan is the founder of JuicyTraffic. He has spent 15 years specializing in adult advertising and ad-fraud prevention, helping advertisers assess traffic quality, identify invalid clicks and protect media budgets across dedicated ad networks.