Lead quality

Every request will go through email, phone and duplicate checks before it can be passed on, then get a score that explains itself. Never creditworthiness.

Markmatix is in development. The features on this page are coming soon: we describe them as we are designing them.

Checks on P-20931

  • Emailaccepts mail
  • Domainno typo
  • Phonemobile, IT
  • Duplicatesnone in 30 days
  • Score82: consistent data, reliable source

verified

Example: how we are designing it, with made-up data.

A lead with a mistyped email or a dead phone number does not sell. If it does sell, it comes back as a chargeback. Markmatix is being designed around lead quality: every request will go through a set of checks and receive a score before it can be passed on. Sources that behave oddly will be quarantined automatically, before their leads reach a partner.

Lead verification: email and phone

Check What it will look at Where
Email Syntax, a domain that accepts mail, domain typos, disposable addresses In the core
Mailbox Whether the individual mailbox exists, via an external service Plugin
Phone International format and number type In the core
Live number Whether the number is active on the network Plugin
SMS OTP A code the person receives and types in Plugin

The core checks will tell you whether an address is well formed, whether its domain accepts mail and whether it is a disposable address. A typo in the domain will be corrected. Checking that the individual mailbox exists will go through an external service, as a plugin.

The live number check, often called an HLR lookup in the trade, and SMS one-time passcodes will be plugins you can switch on per industry. They are meant for partners who pay more for a verified phone number. Whether these plugins are included or paid for will be decided in the price list.

Scoring: rules first, then AI

The quality score will have two layers. The first will be fixed rules, in the core: consistency between fields, duplicates, the history of the source. The second will be an AI score that also says why, offered as a pay-as-you-go add-on with a monthly cap. The threshold for passing a lead on will be set per publisher and per partner.

The score will learn from outcomes. When a partner charges a lead back, that chargeback will count against the source and against the signals that came before it. Outcomes arrive through network postbacks, which we describe on the revenue and postbacks page.

Duplicates

Two requests will belong to the same contact if the normalised email matches, with domain typos corrected, or if the phone number matches. A new request in the same industry within a configurable window, 30 days by default, will be flagged as a duplicate. That way the same lead will not reach the same partner twice by mistake.

What the score will never look at

The AI score will assess how genuine the data is and how good it is. It will never assess creditworthiness or insurance risk. Under the AI Act, assessing people's creditworthiness, or risk for life and health insurance, is a high-risk use (Regulation (EU) 2024/1689, Annex III, point 5(b) and (c)). Fraud detection, on the other hand, sits outside the high-risk category.

That is why income, debts and health will not be among the AI score's signals, even when those fields are on the form. The rule will apply to loan leads and insurance leads alike.

Then there is automated decision-making (Article 22 of Regulation (EU) 2016/679). Routing and scoring will not produce legal effects on the person. Their logic will still be described in the privacy notice, and the person will be able to ask for human review.

Fake leads and source quarantine

Markmatix will look for anomalies source by source: sudden spikes, the same IP address or device, forms filled in too fast, emails in a sequence. When it finds them, it will quarantine that source's requests and send an alert on Telegram. A person will then decide whether to release or discard them. Advanced AI fraud detection will be a pay-as-you-go add-on. Fraud alerts will stay on whatever your settings: see the Telegram and AI page.

From lead quality to sale

A verified request will enter the rules cascade described on the lead distribution page. A quarantined request will wait for a person's decision. The score will stay on the request together with its status, partner and financial events, so you will always be able to reconstruct why a lead left or stopped.

If you would like to run these checks on your own leads when that becomes possible, join the waitlist.

Updated 3 November 2026

Common questions

What makes a good quality lead?

Real, consistent data from a person who actually asked for the service and agreed to be passed to that partner. In Markmatix a lead will qualify after the email, phone and duplicate checks, with a score above the threshold set for that partner.

How do you spot fake leads?

Mostly from the behaviour of the source rather than the single lead: spikes, the same IP address or device, forms filled in too quickly, emails in a sequence. Markmatix will quarantine that source's requests and send an alert on Telegram. A person will decide whether to release or discard them.

What is an HLR lookup, and will Markmatix have one?

It is a check that a mobile number is active on the network. In Markmatix it will be a plugin, alongside SMS one-time passcodes, switched on per industry when a partner pays more for a verified number. The core will check international format and number type.

Will the lead score assess creditworthiness?

No. The AI score will look only at how genuine and how good the data is. Income, debts and health will not be among its signals, because assessing creditworthiness or life and health insurance risk is high-risk under the AI Act.

Is lead scoring an automated decision under Article 22 of the GDPR?

Routing and scoring will not produce legal effects on the person. The logic will be described in the privacy notice and the person will be able to ask for human review. As with the whole project, the final assessment belongs to a lawyer, on the actual case.

Save me a seat:

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