Glossary · Platforms & business
Lead routing
Also called: lead assignment, lead distribution, round-robin routing
Lead routing is the process of automatically assigning each new lead to the right salesperson, team or nurture track based on rules such as territory, company size, product interest, score or round-robin rotation.
Routing decides two things that drive conversion: who follows up and how fast. A great lead that sits unassigned for a day is worth less than an average one called within minutes.
Common routing models
| Model | Rule | Watch out for |
|---|---|---|
| Territory | Region or country → rep | Uneven territories, overlapping accounts |
| Segment | Company size or industry → team | Bad firmographic data |
| Round-robin | Next rep in rotation | Ignores skill, capacity and time off |
| Score-based | High score → sales, low → nurture | Score drift, and scores nobody can explain |
| Account-based | Existing account owner wins | Needs reliable account matching |
Real setups layer them: existing account owner first, then segment, then round-robin within the team.
Where AI helps, and where it doesn't
AI is useful for reading messy form answers into a score with a stated reason, or tagging product interest. It shouldn't silently decide who gets ignored: keep the score visible, let reps flag bad calls, and review a sample each week.
The basics that matter more than the model
Deduplicate before routing (a returning lead belongs to its existing owner), have a fallback owner for anything no rule matches, and alert on unassigned leads.
In Fluxo Flow
The Router node sends a run down the first route whose conditions match, with a default route for everything else, so rule order is your priority order. A typical lead workflow scores the lead with an AI step, routes on the score, creates or updates the HubSpot contact (matched on email) and alerts the owner in Slack. The AI lead qualification template is a ready-made version.
Read next
Related terms
- Human in the loop (HITL)Human in the loop (HITL) is a design in which an automated process pauses at chosen points for a person to review, correct, approve or reject its output before it continues.
- Structured outputStructured output is a model response in a predefined, machine-readable format, typically a JSON object matching a schema, so the next steps of a workflow can use the fields directly instead of parsing prose.
- WorkflowA workflow is a repeatable sequence of steps, started by a trigger, that turns an input (a form, an invoice, a new deal) into an outcome, with defined rules for each decision along the way.
- LLMAn LLM, or large language model, is a neural network trained on large amounts of text that generates text by repeatedly predicting the next token, which lets it summarize, classify, extract and draft.
- JSON schemaJSON Schema is a standard vocabulary for describing what a JSON document must look like (which fields are required, their types, formats, allowed values and ranges) so data can be validated automatically.