Introducing Floopr: email feedback loop intelligence.
Meet Floopr
Built in Europe. Operated by mySMTP. Live today in early access.
Today we are opening the doors to Floopr, a new platform from the mySMTP team with one job: helping senders understand who is complaining, where reputation is changing, and why it matters.
Floopr monitors feedback loop (FBL) complaints, sending IPs and domains, blacklist listings and Google Postmaster signals in one place, so you can spot changes in your email deliverability and investigate the sources behind them. Instead of juggling provider portals, ARF emails and CSV exports, you get one normalized stream of events you can filter, attribute and act on.
real per-complaint ARF sources
Gmail: rates, not copies
providers that offer nothing back
same schema from every source
Six providers, six formats, no correlation
Complaint data exists. It just does not arrive in a usable shape.
Every mailbox provider reports differently, and blocklists report differently again. By the time you connect the dots by hand, throttling or foldering may already have started. Floopr's value is correlation and normalization, not another pile of raw reports.
6 providers, 6 formats, no correlation.
1 Collect every provider feed, one inbox
2 Normalize 6 formats into one schema
3 Attribute to your IP, domain, campaign
4 Alert only when it matters
+240% vs 7-day baseline · 4 providers agree
news.acme.io · 185.12.44.9 · aug-newsletter
Illustrative demo data.
Why Floopr
Feedback loop complaints and blacklist monitoring land in the same place, on the same assets, on the same timeline, instead of two tools that never talk to each other.
Floopr maps everything into one consistent model of identity, provider, category and timestamp.
A normalized Floopr Reputation Score summarises complaint health, blacklist status and provider trends, with the contributing signals always visible behind it.
Reports are grouped by IP, domain, provider and campaign, as far as the provider and your mail headers supply them, so you can see where to act.
A taste of the real dashboard
One of several dashboard views, filled with made-up data. Every number, domain and IP below is fictional.
Normalized from your complaint feed and blacklist monitoring. It is Floopr's own score, not a Gmail, Yahoo or Microsoft score, and no provider endorses or publishes it.
| Contributing signal | Reading | Weight |
|---|---|---|
| Complaint health24h rate across all monitored identities | 0.11% | 30% |
| Blacklist status185.24.10.4 on a public DNSBL | 1 listed | 25% |
| Yahoo / AOL complaint trendvs. the account's own 7-day baseline | +38% | 15% |
| Microsoft statusJMRP volume flat, SNDS colour green | Stable | 10% |
| Domain reputationnews.acme.io, no negative movement | Good | 10% |
| IP reputation185.24.10.4, complaints then listing | Degrading | 10% |
−0.03 vs previous
+184
+2
Provider signals and recent FBL events
| Provider | Events | Rate |
|---|---|---|
| Yahoo / AOL | 1,248 | 0.09% |
| Microsoft (SNDS) | 874 | 0.14% |
| Validity UFL | 312 | 0.21% |
| Signal Spam | 96 | 0.04% |
| Time | Source | Type |
|---|---|---|
| 09:42 | 185.24.10.4 · Yahoo | abuse |
| 09:31 | 185.24.10.9 · Validity | abuse |
| 09:12 | 185.24.11.2 · Microsoft | not-spam |
| 08:40 | 185.24.11.7 · Signal Spam | abuse |
From a single complaint to the action that protects your sending
Feedback loops and blacklist monitoring are placed on one timeline so the sequence is visible.
A recipient marks a message as spam. The provider's loop returns a per-complaint report tied to your sending identity.
Complaint volume for that IP, domain or source moves above its own baseline.
A listing on the same asset is placed on the same timeline as the complaint movement.
Throttling, foldering, rejections: shown where observable, the rest labelled unverified.
Pause a stream, isolate a customer, review a campaign, request delisting. One prioritised step instead of five open tabs.
Not "73 complaints": which IP, which customer, which campaign
A complaint count tells you something is wrong. Attribution tells you where to act.
Illustrative demo data. Counts are complaints out of 73.
- Isolate the sending customer creating reputation risk before it reaches your shared pools.
- Hand your abuse desk evidence per account: complaint counts, timings, providers and listings on one record.
- Feed suppression and throttling decisions from the same normalized event your dashboard shows.
- Keep per-customer history so an account's pattern is visible, not just today's incident.
Slice complaint data the way your sending is structured
Exactly who your complaints come from, and who gives nothing back
Only providers that run a documented feedback loop produce per-complaint events. Every group is labelled so nothing looks like coverage it is not.
Public self-service programme (CFL), enrolled per DKIM signing domain.
JMRP returns complaint copies per IP. SNDS reputation and volume data is planned.
Orange, SFR and La Poste run no standalone self-service loop. Signal Spam is the single route to French consumer complaint data.
One commercial enrolment is the route to several mailbox groups that closed their own loops, including Comcast, La Poste, Libero / Virgilio and Seznam.
Point an existing loop at your Floopr email and it is parsed like a native source.
Daily complaint rates per domain. No per-message copies exist, so no recipient-level action is possible.
These providers return nothing directly to senders. Floopr names the blind spot instead of implying coverage.
Coverage map by market
The big three dominate globally, but the local remainder is where your blind spots live. The bar shows roughly how much of each market Floopr can observe today.
| Market | Big-3 share | Local mailboxes and gaps | Floopr visibility |
|---|---|---|---|
| 🇺🇸 United States | ~75–85% | Apple iCloud, regional ISPsApple iCloud returns nothing to senders | ~80% |
| 🇬🇧 United Kingdom | ~80% | BT/Sky (Yahoo-hosted), AppleApple and some ISP brands unmeasured | ~80% |
| 🇩🇪 Germany | ~45–55% | GMX + Web.de ~30–40%United Internet runs no feedback loop at all | ~50% |
| 🇫🇷 France | ~55–65% | Orange, SFR, Free, La PosteReported only via Signal Spam / Validity | ~65% |
| 🇩🇰 Nordics | ~80–90% | Telenor, Telia, Get (no FBL)Telco mailboxes have abuse desks, no loops | ~85% |
| 🇮🇹 Italy | ~65–75% | Libero, Virgilio, PECLibero/Virgilio only through Validity UFL | ~75% |
| 🇪🇸 Spain & LATAM | ~70–80% | Terra, UOL, LocawebTelefónica and Brazilian ISPs publish nothing | ~75% |
| 🇨🇿 Czechia | ~50–60% | Seznam (email.cz) ~30%+Complaints arrive only via Validity | ~60% |
| 🇯🇵 Japan & Korea | ~40–55% | Yahoo! Japan, Naver, DaumKorean mailboxes are whitelist-only, no feed | ~45% |
Share figures are public industry estimates of consumer mailbox mix and vary by audience, age group and B2B/B2C split. Treat them as planning guidance, not measurement. Provider support and access requirements differ: some loops require domain or IP verification, and source counts are indicative of programmes Floopr can ingest, not a guarantee of enrolment for every sender.
Complaint and reputation signals, deliberately not everything
Floopr's territory is complaint and sender reputation intelligence. The data layer can expand into adjacent sources, but it is not becoming a generic all-in-one deliverability toolbox. Everything is labelled by what exists today and what is planned or possible.
Per-complaint ARF reports from documented programmes, normalized into one event model.
Listing status for monitored IPs and domains, correlated with complaint movement.
Aggregate Gmail spam rates, authentication pass rates and delivery errors as an early-warning trend.
Per-IP complaint copies plus Microsoft's own volume and reputation colouring.
Alignment and unauthorised-use signals for the same sending identities.
Rejection and deferral patterns from your own MTA.
Configuration drift that can quietly degrade reputation.
Further provider and third-party sources as they become available to senders.
A transactional sender at 100,000 emails a day
Illustrative scenario. "Northbound Pay", a fictional European payments platform, sends receipts, password resets and account alerts from a small set of dedicated IPs. When those messages stop reaching the inbox, support tickets follow within hours.
transactional emails
vs. 0.04% baseline
from first alert
to baseline reputation
Floopr flags 0.41% complaints on 185.24.x.18, a single IP carrying the password-reset and receipt streams. Yahoo's loop and Validity's (carrying Comcast) account for 78% of the reports.
Normalized events group by List-Id: one re-engagement campaign was accidentally routed through the transactional pool, mixing marketing volume into a trusted IP.
The campaign moves back to the marketing pool and complainers are suppressed automatically through the Floopr webhook into the sending platform.
Complaint rate back to 0.04%. Inbox placement on the transactional pool returns to pre-incident levels before any provider-side throttling took hold.
Why the metric matters
At 100,000 messages a day, a 0.4% complaint rate is roughly 400 explicit "this is spam" signals every 24 hours. Mailbox providers act on that ratio long before a sender notices revenue impact: first with folder placement, then with rate limiting.
- One shared IP mixes marketing risk into transactional trust.
- Without per-identity attribution, the fix is guesswork for days.
- Suppression must reach the sending system automatically, not by CSV.
Fictional scenario with illustrative figures. Not a customer reference.
Keeping transactional and marketing mail on their own IPs is the first line of defence. See mySMTP dedicated IP server options.
Dashboard + API + Webhooks
Floopr is built to be consumed, not just looked at. The same intelligence that renders in the portal is designed to flow into suppression systems, abuse workflows, MTA dashboards and customer-facing dashboards.
Complaint trends, blacklist status, correlation timeline, attribution and event logs for the assets you monitor.
Normalized complaint events, rollups and monitored-asset data with scoped keys.
HMAC-signed push events the moment a complaint lands, with delivery logs, replay and automatic retries.
FBL data only works when it reaches your sending system
Filter by identity, provider, date range or campaign. Cursor paging for backfills.
Signed events with retries and replay for missed deliveries.
Recurring CSV or JSON drops to object storage or SFTP.
Ask investigations in plain language with scoped, read-only access.
One event schema, every channel
received_attimestamp
providerenum
complaint_typeenum
sending_ipinet
sending_domainstring
return_pathstring
campaign_refstring
message_idstring
recipient_hashstring
Recipient data is minimised: Floopr never asks you to send mail through it, and never returns more identifying data than an investigation needs.
Who it's for
Monitor complaint signals across many sending customers and isolate risky accounts.
Keep notifications and shared sending domains healthy as your user base grows.
Detect when receipts, alerts or lifecycle mail start attracting complaints.
One evidence-backed view for investigations and provider conversations.
How Floopr fits with mySMTP
Floopr is a service of mySMTP, built on the same European, deliverability-first mindset as our email delivery infrastructure and our free deliverability toolbox. Use the toolbox to get SPF, DKIM and DMARC right; use Floopr to see what recipients and blocklists say about your sending afterwards.
An email feedback loop and blacklist monitoring platform from mySMTP that normalizes complaint reports and attributes them to sending IPs, domains and campaigns.
A programme where a mailbox provider sends you a per-complaint report, usually in ARF format, each time a recipient marks your message as spam.
No. Yahoo/AOL, Microsoft, Signal Spam and Validity run documented loops. Gmail publishes aggregate rates only, and several providers offer nothing to senders.
Floopr shows the sequence and timings of complaints and listings on the same asset, and does not claim causation unless it is proven.
Yes. Create a scoped key in the dashboard and call the events endpoint; webhooks are HMAC-signed with delivery logs, replay and retries.
Yes. The Free Test covers up to 300 monitored IPs or domains for 30 days, no card needed.
No. It is monitoring only.
See your complaint signals in one place
Floopr is opening early access to senders and deliverability teams who want a clearer view of feedback loop data.