Digital twins in recruitment are people who resemble the candidates who have already shown interest in similar roles. The ad platforms, Meta for instance, are the ones who find them: you give the platform an audience to start from, and the algorithm looks for people with similar characteristics.
The industry term for this is lookalike audiences. In recruitment it makes it possible to show the job ad to more relevant candidates than the ones who have already seen similar roles.
Frantz builds the audience. The channel algorithm finds the twins.
How it works
Measurement points on the job ads: Frantz registers how visitors behave on job ads, such as reading time, scrolling and intent to apply.
An audience of the interested: Visitors who have engaged with similar roles over the past 90 days become an audience of their own.
The channel finds the twins: That audience is used as the starting point at channels such as Meta, and their algorithm finds people who resemble it. That is the digital twin audience.
The ad reaches both: The job ad is shown both to the people who have shown interest and to their twins.
Why 90 days?
The audience is built from interest shown over the past 90 days. That gives a current picture of who is interested, and the channel finds the twins from what people are showing interest in now, not from old data.
Why it helps in recruitment
The group that has already seen similar roles is limited. The twins widen the reach with people who resemble them, including people who are not looking for work. That makes digital twins particularly useful for reaching passive candidates.
The starting point is what people have done, not an assumption about age, location or job title. That is the difference from traditional demographic targeting, which you can read more about in the guide to job advertising on social media.
What you should know
The algorithm belongs to the channel: Meta and the other channels decide how the twins are found. Frantz controls who is in the audience they start from.
The starting point decides the result: The better the audience reflects interest in that type of role, the better the twins match. That is why it is built from behavior on similar roles.
Consent: Marketing pixels from the ad platforms are only activated once a visitor has given explicit consent. Read more about consent in the FAQ.
Read more
Read more about data-driven recruitment, about data points and behavioral data, and about how the technology works.
Frequently asked questions
Digital twins in recruitment are people who resemble candidates who have shown interest in similar roles. Ad platforms such as Meta find them from an audience you give them, which means the job ad can be shown to more relevant candidates.
The algorithms of the ad platforms, Meta for instance, are the ones that find the twins. Frantz builds the audience they start from, made up of visitors who have engaged with similar job ads.
The audience is built from the past 90 days to get a current picture of who has shown interest. That way the channel finds twins from what people are showing interest in now, not from old data.
Yes, digital twins are the same thing that Meta and other ad platforms call lookalike audiences: an audience of people who resemble a group you already know.