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Closed Loop Enrich

Who reads E29b matrix click-through mvkufalm (synthetic)

The 100 most engaged (highest open rate per send) · 7 contacts · open preview (recorded results) · 23 Oct 2026

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Readers profiled

7

5 matched to a person

Decision makers

80%

owners, C-level, VPs, directors · of 5

Companies

7

7 on a business address

Open rate per send

35.7%

average across the sample

Seniority

of 5 readers where it is known

  • Owner / founder20% (1)
  • VP40% (2)
  • Director20% (1)
  • Manager20% (1)

Job function

of 5 readers where it is known

  • Marketing60% (3)
  • Executive20% (1)
  • Other20% (1)

Industries

No industry found in this sample yet.

Company size

No company size found in this sample yet.

Countries

of 5 readers where it is known

  • Germany20% (1)
  • Singapore20% (1)
  • Sweden20% (1)
  • United Kingdom20% (1)
  • United States20% (1)

Fit grade

of 7 readers where it is known

  • Grade A42.9% (3)
  • Grade C28.6% (2)
  • Grade D28.6% (2)

Engagement × fit

Fit is the AI grade (A or B is high fit). Engagement is the open rate per send: 15% or more is engaged — never “opened at least once”. Counts are the sample's; “Open in Contacts” and “Save as segment” cover every graded contact of the list.

Engaged · opens ≥ 15% of sendsCold · under 15%High fit
A · B

High fit, engaged

3 · 43%

Sell or upsell: they match your ICP and read you.

Open in Contacts

High fit, cold

0 · 0%

Re-engage: they match your ICP but stopped opening.

Low fit
C · D

Low fit, engaged

2 · 29%

Loyal readers outside your ICP: keep them, do not pitch.

Low fit, cold

2 · 29%

Lowest priority: candidates for a list clean-up.

Where readers work

7 companies across 7 readers · top 7, with how many readers each. People are never named.

  • Copperleaf · 1
  • Fernbrook Labs · 1
  • Kestrel AI · 1
  • Northwind Analytics · 1
  • northwind-analytics.example · 1
  • Tidewater Capital · 1
  • unknown-co.example · 1

Made with Closed Loop Enrich · aggregates of a 7-reader sample; no reader is named.