Why is there a sudden click increase from Gmail addresses in SES campaigns, and could Google security checks be the cause?
Matthew Whittaker
Co-founder & CTO, Suped
Published 12 Aug 2025
Updated 26 May 2026
11 min read
Summarize with
A sudden click increase from Gmail addresses in Amazon SES campaigns can be caused by Google security checks, but the Gmail recipient domain alone does not prove it. The first split I make is simple: are the extra clicks coming from real Gmail users, Google-owned infrastructure, generic cloud IPs, security scanners, or a tracking/reporting artifact inside the campaign stack?
The practical answer is that Gmail can create non-human clicks when links are inspected for abuse, malware, unsafe redirects, or suspicious destination behavior. A 70% click increase still needs proof at the click-log level before treating it as Google activity. I would not call it campaign engagement until I have checked IPs, user agents, timing, clicked URLs, recipient patterns, and whether the same clicks triggered conversion or unsubscribe actions.
The most common pattern is a burst of clicks close to delivery time, often on many links in the same message, with no normal session behavior afterward. If the campaign uses a tracked redirect domain, a scanner can hit the redirect URL without the person reading the email. That inflates click-through rate, can falsely complete confirmed opt-in, and can create false unsubscribe events when the body contains one-click unsubscribe links.
The direct answer
Short answer
Yes, Google security checks can be the cause of a sudden click increase from Gmail addresses in SES campaigns. The stronger claim is narrower: the extra clicks are likely automated only when the click source, timing, and behavior match scanner activity. Gmail recipient addresses tell you who received the email, not who clicked the link.
- Google security checks: Look for Google-associated reverse DNS, cache-related hostnames, or Google-owned netblocks, paired with fast clicks after delivery.
- Non-human interaction: Clicks that happen without a browser session, cookie continuity, dwell time, form completion, or downstream page activity are not reliable engagement.
- SES factor: Amazon SES is usually the sending path, not the click source. Shared pool changes, IP reputation, and link domains still affect how receivers inspect mail.
- Reporting artifact: If the spike exists only in the ESP click dashboard and not in web analytics or conversions, the click-tracking layer is the first suspect.
The risk is acting on inflated clicks as if they are human intent. That leads to wrong subject-line conclusions, wrong segment scoring, and damaged confirmation flows. I treat sudden Gmail click spikes as an attribution problem first and a deliverability problem second.
Amazon SES console view with sending metrics used to compare delivery events and click activity.
I also separate Gmail addresses from Google IPs. If a report says clicks came from Gmail, that often means the recipient email address ended in gmail.com. It does not automatically mean the HTTP request came from Google. To prove Google involvement, you need the IP address that requested the tracking URL, reverse DNS, ASN ownership, request headers, and timing.
What Google checks can do
Gmail and Google browsing protection systems inspect URLs because links are one of the main abuse paths in email. The request can happen before the human opens the message, when a link is rendered, when a user hovers or clicks, or when a downstream system checks a redirect chain. The exact timing varies, so the investigation needs evidence rather than assumptions.
A scanner usually behaves differently from a person. It often requests the tracked URL quickly, follows redirects mechanically, skips images and scripts that a browser would load, hits multiple links in one message, and never returns with a normal web session. Some scanners fetch only the first redirect hop. Others continue through the final landing page.
Flowchart showing how an SES email can produce scanner clicks before a real human visit.
|
|
|
|---|---|---|
Timing | Seconds after delivery | Spread over minutes |
Links | Many links hit | One or two links |
Session | No page path | Normal browsing |
IP source | Data center | Consumer ISP |
Conversion | No intent event | Form or purchase |
Signals that separate automated checks from human clicks.
This is why raw click-through rate is fragile. If Gmail security checks touched a tracked redirect, the ESP records a click because the tracking server received a request. That record is technically true, but the marketing interpretation is false unless it is filtered or labeled.
Why SES is part of the diagnosis
SES does not make Gmail click links. SES sends the email, signs it if configured, tracks events if you built tracking around it, and gives receivers the envelope, headers, IP, and content they evaluate. SES still matters because sender identity, IP pool reputation, bounce patterns, complaint patterns, and link domain reputation affect how aggressively receivers inspect the message.If SES changed
- IP pool: A shared pool or dedicated IP change can alter receiver trust and scanning behavior.
- Identity: A different MAIL FROM domain, DKIM selector, or tracking domain can change how the message is evaluated.
- Reputation: A recent blocklist or blacklist issue can push receivers to inspect links more aggressively.
If Gmail changed
- Inspection: Gmail can fetch links or redirect chains as part of unsafe URL checks.
- Classification: A reputation shift can move mail into heavier scanning without causing visible spam placement.
- Caching: Some requests can resolve through Google-related cache infrastructure rather than a consumer browser.
A useful clue is whether the spike affects only SES campaigns or every campaign to Gmail across your other sending systems. SES-only points toward a sender, IP, identity, tracking, or campaign-content change. Gmail-only across multiple senders points toward receiver-side scanning or a Gmail classification shift.
Authentication also belongs in the diagnosis. If SPF, DKIM, or DMARC domain matching is inconsistent, Gmail has less reason to trust the message, especially when the link domain is different from the visible brand. Suped's DMARC monitoring helps connect authentication results with sending sources, so you can see whether SES is passing cleanly before spending time on click filtering.
How to prove the source
The fastest way to resolve this is to export raw click events and group them by recipient domain, source IP, user agent, link URL, timestamp, and campaign. Aggregated dashboards hide the difference between one person clicking once and one scanner clicking every link in a template.
Fields to export from click logstext
campaign_id recipient_email recipient_domain message_id clicked_url final_url click_timestamp source_ip reverse_dns asn user_agent http_method redirect_status landing_page_session_id conversion_event
Start by checking the first 15 minutes after delivery. Security systems usually act close to receipt. Real click curves usually have a softer tail, especially for newsletters, promotions, and lifecycle campaigns. Then check whether the spike hit only Gmail addresses or also Google Workspace domains that use Gmail infrastructure.
- Group by IP: Find whether a small set of IPs created a large share of clicks.
- Resolve ownership: Check ASN and reverse DNS for Google, consumer ISPs, corporate gateways, and cloud hosts.
- Compare links: Identify whether scanners clicked all links, privacy-policy links, unsubscribe links, or only primary calls to action.
- Compare analytics: Match ESP clicks against web sessions, UTM visits, form starts, purchases, and server-side events.
- Check authentication: Confirm SPF, DKIM, DMARC, and visible From domain matching for the SES stream.
Email tester
Send a real email to this address. Suped opens the report when the test is ready.
?/43tests passed
Preparing test address...
Send a real copy of the campaign through the same SES identity and inspect the result with the email tester. That gives you a controlled view of authentication, headers, content warnings, and deliverability signals without relying only on campaign metrics.
If your logs contain an IP that resolves to a Google cache hostname, treat it as a strong automated-click signal, then check whether it loaded the same URL pattern repeatedly. If the IP is a normal residential ISP and the session has page views, time on page, and a conversion, count it as human unless other evidence contradicts it.
The confirmed opt-in and unsubscribe problem
The most expensive version of this issue is not inflated reporting. It is when automated clicks change user state. Confirmed opt-in, passwordless login, preference changes, and body unsubscribe links should not complete on a single GET request from a tracked email link.
Do not let a scanner complete intent
A link click can prove that a URL was fetched. It does not prove that the subscriber intended to confirm, unsubscribe, approve a login, or change a preference. Use a confirmation page, a POST action, or another explicit human step for state-changing flows.
Fragile flow
- GET action: A single link fetch confirms a signup or unsubscribe.
- Tracked body link: The same redirect layer used for marketing clicks changes account state.
- No session check: The app cannot separate a bot fetch from a person.
Safer flow
- Landing page: The click opens a page that asks the person to confirm the action.
- POST action: The state change happens after a button press, not on link fetch.
- Bot filter: Known scanner behavior is excluded from conversion and lifecycle triggers.
Header-based one-click unsubscribe is different from putting a one-click unsubscribe link in the body. The header mechanism is designed for mailbox providers. A body link that immediately unsubscribes on GET is easy for automated scanners to trigger. Keep body unsubscribe links compliant and clear, but require a confirmation page before final state change when scanner clicks are a known problem.
What to check in authentication and reputation
When a Gmail click spike appears at the same time as reputation trouble, I check both the email authentication path and the reputation of the sending and link infrastructure. A recent blocklist (blacklist) issue, a new SES pool, or a new redirect domain can change the receiver's risk calculation even when the campaign copy stayed the same.
Click spike triage bands
Use the spike size to decide how quickly to move from reporting review to infrastructure investigation.
Normal variation
0-15%
Compare against recent Gmail-only campaigns first.
Review needed
16-40%
Check timing, links clicked, and web analytics.
Likely automation
41-70%
Export raw logs and filter scanner patterns before reporting.
Critical anomaly
70%+
Audit sender identity, link domains, and reputation immediately.
For authentication, verify that the visible From domain has DKIM or SPF domain matching, the SES MAIL FROM domain is configured correctly, and DMARC reporting shows expected pass rates for Gmail. Use a domain health check to catch obvious SPF, DKIM, and DMARC problems before digging into HTTP logs.
Example DMARC record for monitoringdns
Host: _dmarc.example.com Type: TXT Value: "v=DMARC1; p=none; rua=mailto:dmarc@example.com; fo=1"
That example starts in monitoring mode. It will not fix bot clicks by itself, but it gives you the data needed to see whether SES is authenticated cleanly. Once legitimate senders pass with matching domains, move toward quarantine or reject with staged rollout. Suped is useful here because it turns raw DMARC aggregate reports into source-level issues, shows steps to fix failures, and keeps SPF, DKIM, DMARC, blocklist monitoring, hosted SPF, and MTA-STS management in one place.
Issues page showing top issues, verified sources, unverified sources, and authentication pass rates
For reputation, inspect sending IPs, link domains, and domains used in redirects. A blocklist or blacklist hit does not automatically explain a click spike, but it can explain why a receiver started checking messages more aggressively. Suped's blocklist monitoring helps keep that reputation context beside authentication data, which is easier than treating these as separate incidents.
How to adjust reporting without hiding the problem
Do not delete suspicious clicks from history. Label them. A good reporting pipeline keeps raw clicks, creates a filtered human-click metric, and exposes the filter reason. That keeps your campaign reporting honest while preserving evidence for future incident reviews.
- Keep raw clicks: Store every tracking request with IP, user agent, timestamp, URL, and recipient metadata.
- Create a human-click metric: Exclude known scanner patterns, instant multi-link fetches, and requests with no web session.
- Use conversion weighting: Treat page sessions, form starts, purchases, and replies as stronger signals than a redirect hit.
- Alert on drift: Trigger review when Gmail filtered clicks diverge from raw Gmail clicks beyond your normal range.
If your reporting cannot access raw click IPs, add server-side logging on your tracking redirect or landing pages. UTM-only analytics can undercount scanner traffic because some scanners stop at the redirect, while ESP click tracking can overcount it because the redirect itself is the measured event.
A clean operating model
Report raw clicks for audit, filtered clicks for engagement, conversions for intent, and authentication health for sender trust. When those four numbers are separated, a Gmail scanner spike stops distorting campaign decisions.
If you recently saw bot-like activity outside Gmail too, compare this incident with other mailbox patterns. Click inflation has a few recurring causes, and a broader write-up on bot click activity can help separate receiver scanning from analytics bugs and campaign setup mistakes.
Views from the trenches
Best practices
Separate Gmail recipient metrics from click-source IP ownership before changing reporting.
Keep raw clicks and filtered human clicks so campaign reporting remains auditable.
Require explicit confirmation for signup, unsubscribe, and preference-changing links.
Common pitfalls
Treating a Gmail address as proof that Google infrastructure made the click is unreliable.
Letting a tracked email GET request complete confirmed opt-in creates false signups.
Ignoring recent blocklist or blacklist events can hide why scanning became heavier.
Expert tips
Check reverse DNS and ASN for spike IPs before deciding whether clicks are human.
Compare ESP clicks with web sessions to separate redirect hits from real visits.
Review SES identity, MAIL FROM, DKIM selector, and link domain changes together.
Marketer from Email Geeks says a large SES click increase should be split by recipient ISP before assuming the campaign suddenly improved.
2024-08-16 - Email Geeks
Marketer from Email Geeks says Gmail-address clicks require raw IP review because recipient domain and click source are separate facts.
2024-08-16 - Email Geeks
What I would do next
I would treat a 70% Gmail click increase in SES as suspicious until proven human. The working answer is that Google security checks can cause it, especially when the clicks arrive quickly, cluster around a few IPs, hit many links, and fail to produce normal web sessions. The proof is in raw click logs, not in a top-line Gmail segment.
The immediate fix is operational: export the logs, label likely scanner activity, protect state-changing links, and compare filtered clicks against conversions. The parallel fix is deliverability hygiene: confirm SES authentication, check sender and link reputation, and monitor blocklist or blacklist changes that can trigger heavier inspection.
Suped fits the authentication and reputation side of that workflow. It is not a replacement for click-log analysis, but for most teams Suped's product is the best overall fit when they need DMARC, SPF, DKIM, hosted SPF, hosted MTA-STS, and blocklist signals beside the incidents that affect campaign interpretation. That unified view stops each spike being treated as an isolated mystery.
