What triggers an ESP to disable newsletter monetization for “irregularities” in email marketing?

Hi! When an ESP disables newsletter monetization for “irregularities,” it’s usually because their risk/fraud systems think either (a) your audience wasn’t acquired with clean consent, or (b) the monetization clicks/signups look incentivized, automated, or otherwise “not genuine” to advertisers—even if your sending itself looks mostly fine. Because ad networks and referral/boost marketplaces put the ESP on the hook financially, they tend to act fast and share very little detail.

Here are the most common triggers I see in email ops/compliance that lead to monetization being shut off (often without a precise explanation):

The most common “irregularities” that trip monetization flags

1) List acquisition that can’t be proven as true opt-in

Even if you believe it’s opt-in, monetization programs often require high-confidence consent.

• Subscribers imported without clear source/consent metadata (CSV imports, old lists, “my audience from X”)
• Co-registration (“enter your email to get a prize / download, and also receive partner newsletters”) unless it’s very explicitly disclosed
• “Opt-in” collected by a partner where the consent language is vague (or not newsletter-specific)
• Too many signups with no double opt-in confirmation (not required everywhere, but it’s a strong trust signal)
• Recycled/old lists (aged addresses can create spam-trap and complaint risk)

2) Low-quality or incentivized traffic sources

This is a huge one for monetization. ESPs and advertisers get burned by traffic that “converts” but isn’t real engagement.

• Paid social lead forms with broad targeting + low friction (these can generate accidental/bot signups)
• Incentivized signup (“sign up to enter giveaway,” “get paid to subscribe,” “subscribe for points”)
• Swap promos with other newsletters where the audience isn’t aligned (often causes complaint spikes)
• Affiliate traffic that you can’t fully vouch for (unknown sub-affiliates)

3) Bot activity and “too-perfect” patterns

Fraud tooling looks for patterns that humans don’t produce.

• Many subscribers from the same IP range / ASN / data center traffic
• Signups happening in bursts at odd hours with similar user agents
• Extremely fast click times (seconds after send) at scale
• Repeated clicks from the same device/IP across many accounts
• High volume of “link scanner” clicks isn’t usually punishable by itself, but if the pattern matches known click-fraud footprints, it can get monetization paused

4) Abnormal click behavior on ads/referrals specifically

You can have a healthy newsletter and still get monetization disabled if the ad/referral interactions look manipulated.

• Very high click-through rate concentrated on monetized links, especially from new subscribers
• Clicks with unusually low downstream quality (e.g., advertiser reports low quality, immediate bounces, or reversals)
• Encouraging/wording that feels like “click the ad to support me” can be okay on some platforms, but on others it’s treated as incentivizing ad clicks (a common policy line)

5) Deliverability and complaint signals that increase platform risk

Even without fraud, “risk to sender reputation” can get features restricted.

• Spam complaint spikes (especially shortly after list growth)
• High hard bounce rate (invalid addresses, typo domains, scraped/auto-filled addresses)
• Lots of unsubscribes relative to your normal baseline after a growth campaign
• Low engagement across the list (many inactive addresses) + scaling volume quickly

6) Content/category or compliance mismatch

Sometimes “irregularities” is a bucket used for policy issues too.

• Content that falls into restricted categories (varies by ESP/ad network)
• Missing/unclear identity info (physical mailing address requirements depend on region/program, but ESPs usually expect clear sender identity and one-click unsubscribe behavior)
• Misleading subject lines/from-names, or formatting that resembles affiliate blasts

---

The first metrics to review (in order) to pinpoint the likely trigger

If you only look at a few things, I’d start here:

1. Subscriber source breakdown (last 30–90 days)

• Where did each new subscriber come from (form, landing page, import, partner, paid lead form, referral/boost)?
• What changed right before monetization was disabled (new campaign, new partner, new ad channel, a big import)?

1. New subscriber quality (cohort analysis)
   Compare newest cohorts vs older subscribers:

• Hard bounces, spam complaints, unsubscribes per 1,000 sends
• Engagement (opens/clicks) over the first 1–3 emails after signup
  If the newest cohort behaves wildly differently, that’s often the smoking gun.

1. Monetization-link click patterns

• CTR on monetized links vs normal editorial links
• Click distribution: are clicks clustered in a narrow time window, geography, or a small set of IPs/devices?
• Are the same people clicking multiple ads repeatedly?

1. Bounce and complaint indicators

• Hard bounce rate trend (especially after any import or paid growth)
• Spam complaint rate trend (by campaign)
• Unsubscribe rate spikes (by campaign or by cohort)

1. Suppression/invalid patterns

• Role accounts (info@, admin@) and obvious typos
• Disposable email domains (if you track them)
• Repeated signups to the same address (could indicate automation)

If you find a single growth channel where subscribers have higher bounces/complaints and disproportionately high monetization clicks, that combination very often triggers “irregularities.”

---

The most practical way to request a review (when they won’t share details)

You’re right that many providers won’t disclose the exact rule or signal (it helps them prevent adversarial behavior). What does work is giving them a clean, structured “risk packet” that makes it easy to reinstate you.

Here’s what to send support/trust & safety (short, factual, and organized):

• Your acquisition methods (by channel)

  • “X% from on-site form, Y% from paid social lead ads, Z% from partner cross-promo,” etc.
  • Confirm: no purchased/scraped lists, no rented lists, no incentives for ad clicks, no paid-to-subscribe.

• Proof of consent & disclosure

  • Describe the exact signup flow and what users see (copy/paste the signup language)
  • Confirm whether you use double opt-in (and if not, offer to turn it on)
  • Confirm your unsubscribe process is one-click and honored promptly

• What changed right before the enforcement

  • Any import, new referral marketplace, giveaway, partner promotion, or paid campaign
  • If there was a spike, call it out yourself and explain why it happened

• Your self-audit findings

  • “No unusual complaint spikes” or “complaints spiked on cohort from X, we paused that source”
  • Any steps you’ve already taken: removed that cohort, added CAPTCHA, enabled double opt-in, tightened targeting, suppressed disengaged users, etc.

• A concrete remediation plan

  • “We will pause paid lead forms for 30 days”
  • “We will enable double opt-in for all new signups”
  • “We will remove subscribers acquired between [date range] from [source] and only mail confirmed engaged users”
  • “We will add bot protections (CAPTCHA/honeypot) and block suspicious IP ranges”

Escalation tactic that helps: ask them to route the case to their compliance/monetization risk team and ask which category it falls into (list acquisition, click fraud, advertiser quality, deliverability risk, restricted content). They may not share the exact metric, but they sometimes will confirm the category.

If they still won’t engage, your best leverage is demonstrating you’ve removed the likely risky source/cohort and tightened controls—because the decision is often “reinstate once the risk is demonstrably reduced,” not “argue about the signal.”

---

If you want, paste (no personal data) a high-level breakdown like: how many subscribers you added in the last 60 days, top 3 acquisition sources, whether you imported any list, and whether growth involved giveaways/lead forms/referral marketplaces. I can tell you which two or three areas are most likely to have triggered the enforcement and what to change first.