Bots include search crawlers, monitoring tools, scrapers and malicious scripts. GA4 filters known bots and spiders automatically, but not all, so unusual spikes in sessions with no engagement can be automated.
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Spotting it
- Sudden traffic spikes from one country or city
- Near-zero engagement time with high session counts
- Odd user agents or screen resolutions
- Hits to URLs that don't exist or aren't linked
Dealing with it
Block abusive traffic at the firewall or CDN, and use segments or filters in reporting to exclude suspicious patterns. Analytics-level fixes only clean the numbers, not the load on your server.
Common mistakes
Reading a traffic spike as success
Check engagement and conversion before celebrating.
Frequently Asked Questions
Not directly, but heavy bot load can slow a site, and misleading data leads to bad decisions.
Keep reading
- Google Analytics 4: Google’s current web and app analytics product, which records visits and actions as events and reports where visitors come from and what they do.
- Internal traffic filter: An internal traffic filter excludes your own team's visits from analytics so they don't distort the numbers.
- Engagement rate: Engagement rate is the share of sessions that were engaged sessions. In GA4 it is engaged sessions divided by total sessions, the inverse of bounce rate.
- Log File Analysis: Log file analysis means reading server access logs to see exactly which URLs search engine and AI crawlers requested, when, and what they got back.
- Assisted conversions: Assisted conversions count conversions where a channel appeared in the path but was not the final touch, showing its supporting role.
- Attribution window: An attribution window is the period after an interaction during which a conversion can still be credited to it.
- Channel grouping: Channel grouping sorts traffic sources into buckets like Organic Search, Paid Search, Email and Referral using rules based on source, medium and campaign.
- Cohort analysis: Cohort analysis groups users by a shared starting point, such as sign-up week, and tracks how each group behaves over time.
