Feature

AI Lead Enrichment

Enrichment is only useful if it becomes action. Suprflo runs waterfall enrichment from 50+ data sources, fills missing fields, dedupes records, and scores every lead 1–10 against your ICP — then routes those ranked leads straight into sequences and campaigns.

Waterfall enrichment

Run each record through a defined source order until required fields are filled — no single provider has full coverage.

Deduping + normalization

One truth per contact and account. Clean fields, consistent formatting, fewer orphan records and duplicates.

ICP scoring 1–10

Rank leads automatically so sequencing targets the right segment first — not whoever happened to be in a CSV export.

Built into the motion

Enrichment isn’t a side project. It’s stage one of a pipeline that continues into sequences, inbox, and attribution.

Why enrichment is never the end

Most teams enrich to “make the list nicer,” then export into a sequencing tool and lose context immediately. The result is predictable: the wrong accounts get contacted, messaging is generic, and nobody can trace pipeline back to what actually happened.

Suprflo treats enrichment as a foundation. The same enriched record powers scoring, targeting, sequences, LinkedIn steps, inbox routing, and attribution — so your GTM system behaves like a system.

How it works in Suprflo

  1. 1.A record enters the pipeline (CSV, CRM sync, Clay/Apollo export).
  2. 2.Waterfall enrichment fills missing fields across sources.
  3. 3.Deduping and normalization create one clean record.
  4. 4.ICP scoring ranks the record 1–10.
  5. 5.Ranked records route into campaigns — without leaving the system.

Lead enrichment — common questions

Can we keep Clay or Apollo and still use Suprflo enrichment?

Yes. Suprflo is integration-first. If you’re already enriching in Clay or sourcing in Apollo, you can bring that data into Suprflo and make it stage one of a pipeline that continues into sequences, inbox, and attribution.

Why score leads 1–10 instead of a simple yes/no?

Because targeting is rarely binary. A ranked score lets you run tighter sequences on 8–10s, test messaging on 6–7s, and avoid burning low-fit segments — while still learning what converts.

What happens when enrichment data changes?

That’s the point of an engineered system: the record stays live. When a field updates, campaigns and routing can use the updated truth without manual re-exports.

Turn better data into better pipeline.

See enrichment feeding sequences, inbox, and attribution — one motion, one system.

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