How do scammers decide which specific people to contact?

Scam outreach is rarely random at the individual level, even when it appears to be. Mass operations like robocalling or spam email do send messages to enormous lists, but even those lists are curated — sorted by country, age range, income indicators, and past response rates. A person who once responded to a sweepstakes call is more valuable than one who never has, so response history is tracked and sold.

Social media has made targeting dramatically more precise. Public profiles contain names, rough ages, employers, family structures, life events like marriages, bereavements, moves, and retirements, and sometimes explicit financial references like paying off a mortgage. All of this data helps a scammer construct a personalised approach. Someone who just posted about a bereavement and settling an estate is a valuable target for investment fraud. Someone who posted that they are excited to start a new job abroad is a target for rental fraud.

Data brokers aggregate these signals at scale. Companies that legally compile consumer profiles for marketing can sell information that, when used by a scammer, becomes targeting intelligence. Even if each individual data source is legitimate, the combination can create a profile precise enough to underpin a convincing fraud.

Scammers also use platform algorithms without knowing it. When a fake profile engages with content about loneliness, investment, or relationship advice, the platform's algorithm may show that profile to people who also engage with those topics — inadvertently surfacing vulnerable targets. This is not a deliberate exploitation of algorithms but an emergent effect of how recommendation systems work.