Made for Advertising (MFA) Sites: What They Are and How to Exclude Them
Made for advertising sites exist to sell ad impressions, not to serve readers. They can soak up a large share of an open-web budget while delivering little value. This guide explains how to recognise them, how exclusion and inclusion lists work, and where category and popularity data fit.
What made for advertising sites are
In plain terms, an MFA site is a website whose business model is the gap between what it pays for visitors and what it earns from showing them ads.
The content exists to hold the visitor long enough to load more ads. Reader value is secondary.
It is not about fraud alone
Traffic on MFA sites can be real people. The problem is the quality of the attention and the environment, not only bots.
It is a spectrum
Some sites are clearly built for arbitrage. Others are genuine publishers that drifted into heavy ad layouts. Screening needs judgement.
It became a mainstream topic
Industry studies from advertiser groups in recent years put MFA inventory on the agenda of most media buyers and procurement teams.
Signals that point to an MFA site
No single signal proves a site is MFA. Screening works by combining several of them. These are the patterns most often described in general terms across the industry.
High ad density
Many ad slots per screen, often more ad space than content above the fold.
Rapid ad refresh
Ad units that reload on a short timer while the visitor stays on the same page.
Slideshows and pagination
One short article split across many pages or slides, each with a fresh set of ads.
Clickbait headlines
Sensational lists and teasers that promise more than the content delivers.
Thin or recycled content
Generic articles, rewritten material and little original reporting or expertise.
Bought traffic
Most visitors arrive from paid placements on social or content recommendation widgets rather than from search, direct visits or loyal readers.
Short visits
Visitors leave after a few pages, which fits a model built on quick bursts of impressions.
Networks of lookalike sites
Many domains with the same template, layout and topics, often run by one operator.
Unwatched video units
Small autoplaying players placed where few people would notice them.
| Signal | Strength on its own | Why it is not proof |
|---|---|---|
| Ad density | Medium | Many honest publishers run several ad units to stay in business |
| Rapid refresh | Medium | Refresh can be legitimate on long-read or live pages if it follows platform rules |
| Bought traffic share | Strong | New publishers also buy traffic to grow; look at the share and the pattern |
| Slideshow pagination | Medium | Galleries are normal for some subjects, such as fashion or real estate |
| Lookalike site networks | Strong | Large media groups also share templates across real brands |
| Thin content | Weak alone | Hard to judge at scale without human review |
| Low organic popularity | Medium | Small niche sites can be valuable and loved by a few readers |
MFA site or ad-supported publisher?
Most of the open web is funded by ads, and that is healthy. The table contrasts typical traits so that screening hits the right targets and leaves good publishers alone.
| Trait | Typical MFA site | Typical ad-supported publisher |
|---|---|---|
| Reason to exist | Earning more from ads than traffic costs | Serving an audience that comes back |
| Where visitors come from | Mostly paid recommendation and social placements | Search, direct visits, newsletters, social sharing |
| Content | Generic, recycled, split across many pages | Original, with recognisable authors or expertise |
| Ad layout | Ads dominate the screen and refresh often | Ads sit next to content without crowding it |
| Subject focus | Broad mix of viral topics | A clear subject or community |
| Brand presence | Little identity beyond the domain name | A known name, contact details, editorial standards |
| Category profile | Many unrelated categories with no clear lead | One or a few ranked categories that fit together |
Why cheap MFA inventory looks good on paper
MFA supply often survives because it wins on the metrics that are easiest to report. Looking one level deeper shows the real picture.
| Metric | How MFA can flatter it | What to look at instead |
|---|---|---|
| Cost per thousand impressions | Low prices make the buy look efficient | Cost per real outcome, such as a sale, sign-up or qualified visit |
| Viewability | Ads can be technically in view while crowded by many others | Ad clutter on the page and time the ad stays on screen |
| Click-through rate | Dense layouts produce accidental clicks | What visitors do after the click and how long they stay |
| Reach | Many impressions across many small domains | Unique people reached on sites they chose to visit |
| Completion rate on video | Muted autoplay players complete without being watched | Player size, sound and placement on the page |
The safest test is simple: compare business outcomes per pound, euro or dollar for a campaign with and without MFA screening, over the same period and markets.
Who should care, and what each can do
Brands
Ask for domain-level reporting and set a clear policy on MFA supply in agency briefs and contracts.
Agencies
Run screening across all clients with shared lists, and report where spend actually landed.
DSPs
Offer MFA filtering as a default setting and let buyers apply their own allow and block lists.
SSPs and exchanges
Screen sellers at onboarding and review supply that grows fast without organic popularity.
Publishers
Show clear identity, original content and sensible ad layouts, so screening tools recognise quality.
Researchers
Study the size and structure of MFA supply using category and popularity data across markets.
Questions to ask your buying partners
- Which domains received our spend last month, and how much each?
- How do you define and screen MFA supply?
- How quickly are newly seen domains reviewed?
- Can we apply our own inclusion and exclusion lists on every platform?
- How are false positives handled for genuine publishers?
- What share of our impressions ran on domains with little organic popularity?
Exclusion lists and inclusion lists
There are two ways to keep spend off MFA sites. Most buyers end up using both: a block list as a safety net and an allow list for the campaigns that matter most.
Exclusion list (block list)
A list of domains you never want to buy. Everything else stays open.
- Keeps reach wide and easy to scale
- Needs constant updating, because new MFA domains appear all the time
- Good for always-on and performance campaigns
- Mistakes cost spend until the list catches up
Inclusion list (allow list)
A list of approved domains where ads may run. Nothing else is bought.
- Strong control over where every impression lands
- New MFA domains are excluded automatically
- Smaller reach unless the list is built carefully
- Good for brand campaigns and sensitive categories
| Question | Exclusion list | Inclusion list |
|---|---|---|
| Default for unknown sites | Allowed | Blocked |
| Typical size | Thousands of domains, growing | Hundreds to tens of thousands of approved domains |
| Maintenance | Add new bad domains quickly | Add good new domains and review approved ones |
| Risk of missing good sites | Low | Higher, unless the list is broad |
| Risk of buying MFA | Higher, during the gap before new domains are listed | Low |
Common mistakes when excluding MFA
Blocking whole subjects
Removing every entertainment or lifestyle site because MFA operators like those topics throws away a lot of genuine publishers.
Copying one list everywhere
A list built for one market or campaign rarely fits another. Local publishers and subjects differ by country.
Never revisiting blocks
Domains change hands and improve. A block from two years ago may now hide a good site.
Ignoring subdomains and variants
Operators rotate through similar domain names. Screen patterns and new domains, not only the exact names you saw.
Trusting price alone
Very cheap supply is a reason to look closer, not a signal of efficiency.
Keeping lists in one platform
If lists live only in one tool, spend leaks through the others. Keep a master list and push it everywhere.
Building a broad, relevant inclusion list is where categorized domain data does the most work. Instead of starting from nothing, you start from every popular domain in the subjects your campaign needs.
How category and popularity data help
Category and popularity data do not label a site as MFA by themselves. They give you context that makes MFA screening faster, fairer and easier to maintain.
| Data | How it helps with MFA | Example use |
|---|---|---|
| Ranked IAB categories | Real publishers usually have a clear lead subject. A scattered mix of viral topics with no lead is worth a closer look. | Flag domains whose top categories do not fit together |
| Popularity data | Sites with real organic audiences rank higher. Domains with heavy impression volume but low popularity deserve review. | Compare bid request volume per domain against popularity |
| Web filtering categories | Parked, for-sale and suspicious domains are labelled, which removes another source of waste. | Block Parked / For-Sale Domains and Malware / Phishing / Suspicious |
| New-domain updates | MFA operators often launch fresh domains. Daily labels of new domains, rechecked after a week and a month, close the gap. | Hold new domains out of campaigns until they have a stable profile |
| Inclusion list building | Pull all popular domains in your subjects, then remove flagged ones. The result is wide and clean. | A travel brand's allow list from Travel and Attractions domains |
| Country data | Lists can be built per market, so screening reflects local publishers. | Separate allow lists for each country in a campaign |
See also ad fraud prevention, brand safety for advertising and popularity and traffic insights for related uses of the same data.
A screening workflow you can run
This workflow suits an agency, a DSP or an in-house trading team. It uses data you can hold inside your own systems, so no bid has to wait for an outside call.
Export the domains you bought or were offered last month.
Join categories, popularity and filtering labels to each domain.
Flag domains with weak popularity, scattered subjects or risky labels.
Check flagged domains by hand, starting with the biggest spenders.
Add confirmed MFA domains to the block list, good ones to the allow list.
Run monthly, and weekly for new domains.
| Check | Rule of thumb | Action |
|---|---|---|
| Spend versus popularity | High spend on a domain with little organic popularity | Review first |
| Category coherence | Top categories unrelated to each other | Review |
| Domain age | Very new domain carrying large volume | Hold until rechecked |
| Filtering labels | Parked, suspicious or adult labels | Block |
| Relevance to brief | No category overlap with the campaign | Remove from that campaign |
Spot check any domain with the domain category checker before adding it to a list.
Keeping MFA lists current
MFA lists age quickly. Operators replace domains, and genuine sites change hands or improve. A steady data rhythm keeps lists honest.
About 300,000 newly registered domains are categorized every day.
Each new domain is checked again, because many add content after launch.
A further recheck confirms the stable profile of the site.
All other domains are refreshed so categories and popularity stay current.
Be fair to publishers
- Keep a record of why each domain was blocked
- Re-review blocked domains on a schedule
- Offer a route for publishers to ask for a review
- Avoid blocking on one weak signal
Be strict with spend
- Review the biggest-spending flagged domains first
- Hold brand-new domains out of brand campaigns
- Use inclusion lists for sensitive campaigns
- Share lists across all buying platforms
MFA terms in brief
Arbitrage
Buying visitors cheaply on one channel and earning more by showing them ads. It is the core of the MFA model.
Ad clutter
The share of the screen taken by ads compared with content. High clutter reduces the attention each ad gets.
Supply path
The chain of sellers between a publisher and a buyer. Short, clear paths make it easier to see where spend goes.
Frequently asked questions about MFA sites
What does MFA stand for in advertising?
Made for advertising. It describes websites built mainly to sell ad impressions, usually by buying cheap traffic and showing many ads per visit.
Are MFA sites illegal or fraudulent?
Not necessarily. Many break no law and show ads to real people. The concern is value: attention on these sites is usually poor and the environment adds little to a brand.
Can I buy a ready-made list of MFA sites?
Lists from any source go stale quickly. We do not publish a public MFA list, but we can supply the category, popularity and new-domain data that screening relies on. Talk to us about MFA screening data.
Is an inclusion list better than an exclusion list?
For brand campaigns, often yes, because new MFA domains are kept out by default. For broad performance campaigns, a strong exclusion list plus regular screening keeps reach higher.
How does contextual targeting relate to MFA?
Contextual plans built from relevant, popular domains naturally avoid much MFA supply. Read contextual vs behavioral targeting for the planning side.
Which IAB categories do MFA sites fall into?
They often cover broad viral subjects such as Pop Culture, Entertainment or Healthy Living, but so do many genuine sites. Category alone is never enough; see the IAB categories list for what each branch covers.
Do MFA sites affect publishers too?
Yes. Money spent on MFA supply is money not spent on genuine publishers. Clear screening helps quality sites win back budget.
Can popularity data alone find MFA sites?
No. It is one strong input, especially when compared with how much ad volume a domain sells. Combine it with category coherence, filtering labels and human review.
Should new domains be blocked by default?
For brand campaigns, holding new domains back until they have been rechecked is sensible. For broad campaigns, monitor them closely instead of blocking all of them.
Where should MFA screening run in my stack?
As early as possible. Screening domain lists before a campaign launches is cheaper than cleaning up afterwards. Holding the data in your own systems lets every bid use it without waiting for an outside lookup, and keeps your lists the same across every platform you buy on.
How often should MFA lists be reviewed?
Monthly for the full list and weekly for newly seen domains is a good rhythm for most buyers. Review the highest-spending flagged domains first, because that is where a decision changes the most money.
Talk to us about MFA screening data
Category, popularity and web filtering labels for 120 million domains, with daily updates for new domains, delivered as files for your own systems. Tell us how you screen supply today and we will suggest the right data.
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