Personalization
Making a message specific to its recipient. In 2026 the word covers two opposite things: merge-variable insertion (template personalization) and research-based writing (actual personalization).
A useful personalized message connects a verified fact with a relevant question or offer. Name substitution and generic praise do not do that on their own. Preview both research-based copy and rendered variables for accuracy before authorizing outreach.
In practice
Tie one verified observation to a relevant question, then preview the individual message before it enters outreach.
What to check
Avoid fabricated familiarity, invented results, or references to private inferred behavior. Correct merge fields alone do not make the offer relevant.
Use it in LinkedBoost
- write_column_values
Store researched member values and evidence using write_column_values.
- update_lead_messages
Revise an enrolled person's unsent copy without changing everyone's sequence.
Related terms
- AI slop
- Low-effort AI-generated content and outreach: template mail with a first-name merge, generic flattery, obviously machine-written notes. LinkedIn now lets users flag it with a dedicated report option.
- Merge variables
- Placeholders like {firstName} and {company} that a sequencer fills per recipient. The technology behind 'Hi {firstName}, I saw {company} is growing!': and behind most of what gets reported as slop.