Where Your ROI Leaks: Blacklists and Traffic Noise That Eat Into Profit

A campaign can look promising: high CTR, cheap clicks, a steady flow of leads. But after processing, some of those leads get flagged as “blacklist,” approval rates drop — and ROI drops with them.

When rejections like this keep happening, it’s easy to conclude that the whole GEO or audience quality is the problem. We analyzed 33,181 leads with the “blacklist” status and found that the real picture is different: the bulk of these leads is created not by a huge audience, but by a relatively small pool of numbers that submit orders again and again.

What the “blacklist” status means

There are many reasons for rejection during processing: the customer doesn’t like the price, the order was placed under someone else’s name, the buyer changed their mind or can’t be reached.

Blacklist is a separate category. It includes numbers that have already shown suspicious activity, repeatedly created low-quality leads, or were flagged for other reasons.

We decided to check how large this group really is — and whether it actually reflects the quality of the entire market.

There are few problem numbers, but they are very active

Facebook’s audience in Europe aged 35 to 65 is around 180 million people. The total pool of contacts on the blacklist is roughly 330,000 numbers.

That’s about 0.18% of the available audience.

The share itself is small. But individual numbers submit leads so frequently that they create the impression of a mass problem. It is the high activity of a small group — not the number of unique people — that noticeably skews the statistics.

10% of numbers generate more than 42% of leads

The analysis showed a high concentration of repeat activity:

• the top 10% most active numbers generated 42.4% of all leads in the sample;

• one single number appeared in the database 209 times;

• 41.2% of unique phone numbers submitted two or more leads;

• repeat numbers accounted for 76% of the entire dataset studied.

In other words, a large share of rejections is not tied to new users. The same contacts come back again and again, land in different campaigns, and inflate the total volume of blacklisted leads.

This makes the problem look far bigger than it actually is at the level of unique audience.

One number can appear across different partners and different offers

Repeat activity is not limited to a single campaign.

Almost 88% of leads from repeat numbers came from phones that appeared on different offers. In one case, a single number showed up under 18 different User IDs and across 27 offers.

This explains why several partners can run into the same contacts at once: the number keeps submitting leads on different pages, products, and in different ad campaigns.

As a result, everyone sees only a small slice of the activity — but together these repeats add up to a significant volume of rejections.

Some repeat leads appear almost immediately

Another important indicator is the speed of repeats.

20% of repeat blacklist leads were submitted within the first 24 hours. The shortest recorded interval between two leads from the same number was 19 seconds.

That kind of frequency hardly resembles normal buyer behavior. It may point to automated form submissions, deliberate creation of low-quality leads, or other kinds of suspicious activity.

Should you drop the entire GEO because of blacklists?

A high share of blacklisted leads doesn’t mean the country’s whole audience is low-quality.

In some GEOs — including Slovakia, Greece, and the Czech Republic — the concentration of repeat numbers can be higher. But that doesn’t mean there is no solvent audience in these countries.

Before shutting down a direction, break down the rejection reasons and look at:

• what share is specifically blacklist;

• how many of those leads come from repeat numbers;

• how often they appear across different offers;

• what share of overall statistics the most active contacts generate.

This kind of breakdown gives a far more accurate picture than the overall rejection percentage.

Why filtering beats shutting everything down

The data shows the problem is concentrated in a small segment. That means it’s more effective to filter out specific numbers and suspicious activity than to cut off access to the entire audience.

Filtering helps you:

• stop counting repeat leads from known contacts;

• assess the real quality of traffic more accurately;

• avoid mixing blacklist with other rejection reasons;

• make campaign decisions based on cleaner statistics.

Other rejections require separate work: a customer can sometimes be won back with a conversation or a different offer. Blacklisted leads are a different case — they’re often tied to repeat or suspicious activity.

Conclusion

Blacklist can noticeably affect approval rates and ROI, but the scale of the problem is easy to overestimate.

The analysis of 33,181 leads showed that most of the volume is created by repeat contacts: a small group of numbers submits leads dozens or hundreds of times, appearing across different offers and with different partners.

So a high blacklist percentage doesn’t necessarily mean the whole GEO is low-quality. First, separate repeat activity from new leads, assess the concentration of problem numbers — and only then make a decision on the campaign.

Precise filtering is more useful here than abandoning an entire market: it removes repeat contacts and lets you keep working with the main part of the audience.

If you want to break down the stats from your own campaign and understand what exactly is eating into your approval rate — bring your numbers to a manager for review.