Why are email click rates inflated and how to solve the issue?
Matthew Whittaker
Co-founder & CTO, Suped
Published 20 May 2025
Updated 26 May 2026
9 min read
Summarize with
Email click rates are inflated when automated systems click links before, during, or after the human recipient reads the email. The usual cause is security scanning by mailbox providers, corporate gateways, and link protection systems. I treat any sudden jump in click rate, especially a jump concentrated in Outlook, Hotmail, Live, or Office 365 addresses, as measurement contamination until the event data proves otherwise.
The fix is not one setting. You need to separate human clicks from non-human interactions, stop raw clicks from driving automations, report affected mailbox providers separately, and keep your authentication and reputation signals clean. DMARC, SPF, and DKIM do not stop bots from clicking, but weak authentication gives security systems more reason to inspect a message closely.
- Main cause: Security scanners and mailbox protection systems fetch links to assess risk.
- Fastest test: Group click events by mailbox provider, timestamp, URL count, and bot flag.
- Best fix: Report verified clicks, not raw clicks, and protect automations from bot-triggered events.
- Long-term control: Maintain clean authentication, stable sending patterns, and separate bot diagnostics.
Why click rates inflate
A click in most ESP reports means a tracking URL was requested. It does not always mean a person made a choice. Security systems request links to inspect redirects, check landing pages, classify URLs, detonate suspicious content in a sandbox, or update a risk score. The tracking system sees that request and records a click.
This is why the issue often appears as a sudden spike. One mailbox provider changes link scanning behavior, one security layer becomes more aggressive, or one sender gets additional inspection for a period of time. The sender sees a click rate that looks excellent, but the downstream behavior does not match it. Site sessions, add-to-carts, replies, purchases, and form fills stay flat.
Treat raw clicks as noisy
Raw click rate is a useful directional metric when the data is stable. During a bot-click spike, it is a contaminated metric. I do not use it for subject-line decisions, segment scoring, win-back eligibility, or campaign winner selection until the click stream has been filtered.
|
|
|
|---|---|---|
Outlook spike | Provider skew | Segment report |
Instant click | Seconds later | Flag event |
All links | Many URLs | Mark scan |
High opens | No sessions | Use conversions |
Unsub clicks | Proof list | Add guardrail |
Common click inflation patterns and first actions.
Public reports show the same pattern across different senders. A Klaviyo discussion describes inflated click rates tied to specific mailbox domains, and a public bot click analysis explains why automated systems click links in newsletters. The important point is practical: the click happened, but the intent behind it did not come from a person.
How to prove it is bot activity
I start by looking for concentration. If a campaign suddenly moves from a 2% click rate to a 35% click rate, but the jump sits mostly inside Outlook, Hotmail, Live, or a corporate domain group, the metric is not comparable with prior sends. If every link in the email gets clicked within a narrow window, that is stronger evidence.
The best data fields are event timestamp, recipient domain, mailbox provider, URL, user agent, IP, bot classification, delivery timestamp, and later web session behavior. Some ESPs expose only part of this. If IP and user agent are hidden, use the fields you do have: provider concentration, event timing, number of distinct links, and whether the clicks create normal web sessions.
Flowchart for separating scanned clicks from human click events.
- Timestamp clustering: Clicks within seconds of delivery, especially across many URLs, point to scanning.
- Provider clustering: One mailbox family driving most of the lift points to provider-side filtering changes.
- Link breadth: A human rarely clicks every tracked link, social icon, footer link, and unsubscribe path.
- Session mismatch: Clicks without matching site sessions or conversions need separate reporting.
Example event filter logicSQL
SELECT event_id, recipient_domain, url, clicked_at, CASE WHEN bot_click = true THEN 'bot' WHEN clicked_at < delivered_at + INTERVAL '30 seconds' THEN 'probable_bot' WHEN unique_links_clicked >= 5 THEN 'probable_bot' ELSE 'human_like' END AS click_class FROM email_click_events WHERE campaign_id = 'campaign_123';
The exact thresholds depend on your program. A short promotional email with one hero link behaves differently from a long newsletter. I use the logic above as a starting point, then compare filtered clicks against web analytics and conversion data. If filtered clicks return to a normal range while revenue and sessions stay consistent, the filter is doing useful work.
Click inflation triage bands
Use these internal thresholds to decide how much trust to place in raw campaign click rate during an abnormal spike.
Normal noise
0-10%
Raw clicks still usable with routine review.
Watch
10-30%
Check provider split before using click rate.
Investigate
30-60%
Filter events before reporting campaign performance.
Contaminated
60%+
Do not use raw click rate for decisions.
How to solve the reporting issue
The cleanest fix is to create a reporting layer that separates raw clicks, filtered clicks, and conversion-backed clicks. Raw clicks still have diagnostic value. Filtered clicks are better for campaign comparison. Conversion-backed clicks are best for revenue, lead scoring, and audience decisions.
Raw click reporting
- Easy export: Most ESP dashboards show it by default.
- Bot sensitive: Security scans and link previews inflate the number.
- Automation risk: A single scan can move contacts into the wrong segment.
- Poor test metric: Campaign winners can be chosen from scanner behavior.
Filtered click reporting
- Cleaner trend: Bot flags, timing, and link breadth reduce false lift.
- Better segments: Engagement groups use human-like behavior.
- Safer scoring: Lead and intent models avoid scan-only activity.
- More review: Rules need audits when mailbox behavior changes.
If your ESP has a bot-click flag, use it in segments and reports. A common rule is to count click events only where the bot flag is false. If the flag is per event, a scanner event and a later human event can coexist for the same person. That is good. You should keep the human event and ignore the scanner event.
If your ESP does not expose the right fields, build a simple export process. Pull campaign click events, group by provider and domain, then apply timing and URL-count rules. For newsletters, I also like comparing click events with website sessions because a scanner often stops at the tracking URL or landing page fetch while a person creates a normal navigation pattern.
A dedicated click domain helps, but it is not a cure
Dedicated click tracking can make your tracking domain more consistent with your brand and easier to reason about in reporting. It does not stop Microsoft, corporate gateways, or link protection systems from checking links. Treat it as a hygiene and attribution control, not as bot-click prevention.
- Create views: Keep raw clicks, filtered clicks, and conversion-backed clicks in separate columns.
- Protect segments: Exclude bot-flagged events from engaged, VIP, win-back, and suppression logic.
- Split providers: Report Microsoft-family domains separately during known spikes.
- Review automations: Do not let one raw click trigger high-impact flows without another signal.
- Audit tests: Compare filtered click trends with sessions, revenue, replies, and form submits.
For a practical test, send a real message to seed accounts and inspect how it is received with an email tester. That will not prove every scanner path, but it helps catch authentication, content, and rendering issues that confuse the diagnosis.
Email tester
Send a real email to this address. Suped opens the report when the test is ready.
?/43tests passed
Preparing test address...
How authentication and reputation fit
Email authentication does not tell a mailbox provider, "do not scan my links." Scanning still happens on authenticated mail. But poor authentication, DMARC domain mismatch, broken DNS, strange redirect domains, and blocklist (blacklist) problems make the message look riskier. That can increase scrutiny and make measurement problems harder to interpret.
Before I blame a mailbox provider, I want a clean baseline: DMARC passes, SPF and DKIM are valid, sending sources are known, and reputation checks do not show a blocklist (blacklist) issue. A quick domain health checker pass is a useful first check, then deeper DMARC monitoring keeps the source inventory honest over time.
Issues page showing top issues, verified sources, unverified sources, and authentication pass rates
This is where Suped's product fits the workflow. Suped is a DMARC and email authentication platform, so it is not a magic bot-click remover. It is useful because it gives you the authentication and reputation side in one place: automated issue detection, steps to fix, real-time alerts, DMARC policy monitoring, hosted SPF, SPF flattening, hosted MTA-STS, and blocklist monitoring. For teams and MSPs managing multiple domains, that unified view makes it easier to separate a reporting problem from an actual authentication or reputation problem.
The strongest practical baseline
Suped's product is the best overall DMARC platform for most teams that need simple authentication monitoring, clear fix steps, hosted SPF controls, and reputation visibility without turning every sender change into a DNS project.
There is one more operational guardrail: avoid using raw click events for destructive or compliance-sensitive actions. Keep required one-click List-Unsubscribe behavior compliant, but add confirmation where appropriate for preference-center changes, sales alerts, internal proof workflows, and any action where a scanner click creates real damage.
What I would change first
When click rates inflate overnight, I do not rewrite the content strategy. I freeze decisions that rely on click rate, find the affected mailbox group, and build a clean metric before making marketing changes. The goal is to stop bad data from spreading into segments, tests, and revenue attribution.
- Pause decisions: Do not choose winners, suppress contacts, or score leads from raw click spikes.
- Split domains: Compare Microsoft-family, Gmail, Yahoo, corporate, and custom domains separately.
- Use flags: If your ESP exposes a bot flag, exclude true values from engagement segments.
- Add timing rules: Classify very fast clicks and many-link clicks as probable non-human activity.
- Check baseline: Verify authentication, DNS, sending sources, and blocklist (blacklist) status.
If you need a deeper operational playbook, the related guide on bot click filtering covers newsletter reporting, and the guide on artificial opens explains why open rate and click rate often break together.
Do not hide diagnostic links in production
Invisible or honeypot links can identify scanners in controlled tests, but they create their own deliverability and trust risks when used carelessly. If you use them, keep them for diagnostics, document the rule, and never treat the result as the only proof of bot activity.
Views from the trenches
Best practices
Check click timestamps by provider before trusting a sudden lift in campaign engagement.
Keep bot-flagged click events out of segments that define engaged or high-intent users.
Compare filtered clicks with site sessions and purchases before changing campaign strategy.
Common pitfalls
Treating every tracking request as a person click inflates tests and lead scoring.
Letting one raw click trigger unsubscribe-adjacent or internal proof-list actions.
Assuming dedicated click tracking prevents security systems from checking every link.
Expert tips
Track mailbox provider splits so Microsoft-family spikes do not mask normal audience behavior.
Ask your ESP which bot-click fields exist and whether the classification is per event.
Keep authentication clean so scanner behavior is not mixed with avoidable domain issues.
Marketer from Email Geeks says timestamp review is the first step when click and open spikes appear near delivery.
2024-06-08 - Email Geeks
Marketer from Email Geeks says Microsoft-family domains can drive a temporary click spike that later tapers off.
2024-06-09 - Email Geeks
The practical answer
Email click rates inflate because security systems act like recipients in your tracking data. They request links, your ESP records those requests, and your report turns automated checks into apparent engagement. The solution is to change the reporting and automation logic, not to assume the audience suddenly became more engaged.
Use bot flags where available, add timing and link-count rules where they are not, compare provider groups separately, and rely on conversion-backed engagement for important decisions. Then keep DMARC, SPF, DKIM, DNS, and blocklist (blacklist) status clean so you are not debugging scanner behavior and authentication problems at the same time.
