Case Study 02 / ABM Programs

Why a 20-person send beat a 147-person broadcast

When the same mooring-software product email went to two audiences a day apart, the 20 people who had opted into mooring-software updates opened it at 60% and clicked at 10%; the 147-person general community pool opened at 29.1% and clicked at 5.2%. People who had raised their hand engaged at twice the rate. That is the case for building segments on intent and role, not list size.

Client
Maritime compliance software company
Industry
Maritime software and compliance (B2B)
Service
ABM Programs + LinkedIn Content
Timeline
July – August 2026

Founder track record: this work was led by Clarafold's founder before founding Clarafold, while working as marketing manager at a maritime compliance software company. The client's name is withheld until it approves publication; every figure comes from its own systems. Clarafold client engagements are added as they complete.

open rate, opted-in segment (20)
60%
open rate, broad pool (147)
29.1%
click rate for the intent segment
2×
open rate on the LinkedIn-to-email bridge (93)
57.3%

01 · Client

Maritime compliance software company

Maritime compliance software and services company. Its mooring management software is Class-approved. Name withheld until the client approves publication.

The challenge

The company's mooring management software is a specialist product: its real buyers are marine managers, superintendents and DPAs responsible for mooring compliance under OCIMF MEG4 and SOLAS. The default instinct was to send every product message to the whole list. With a few hundred contacts in total, each send to the wrong people spent attention the company could not easily earn back.

02 · System

What existed before.

  • One list, segmented mostly by tags inferred from email prefixes
  • Product emails broadcast to everyone, regardless of role or expressed interest
  • LinkedIn engagement and email lived in separate worlds

03 · Intervention

What was built and run.

01

Built segments on signals people had actually given

An opt-in mooring-updates subscriber segment; a job-title segment for marine managers and DPAs; a separate segment for people who had engaged with the founders on LinkedIn.

02

Sent the same email to two audiences

One send to the 20 people who had opted into mooring-software updates, one the following day to the 147-person community pool. Same subject line, same content.

03

Bridged LinkedIn engagement into email

People who engaged with the founders' LinkedIn content received a short, personal 'let's stay connected' email, tagged by source so the bridge could be measured on its own.

04

Split the call to action, not the audience

Where clients and prospects shared a list, they received the same content with different CTAs: a lead magnet for prospects, an account-expansion conversation for existing clients.

Tools used: MailchimpLinkedInPython

04 · Outcome

What changed.

Opted-in segment (20 recipients): 60% open rate, 10% click rate. Community pool (147): 29.1% open, 5.2% click. The intent segment engaged at roughly twice the rate on both measures.

The LinkedIn-to-email bridge opened at 57.3% (93 recipients, 7.3% click) and 39.1% (27 recipients, 13% click): well above the list's 42.2% average open rate for the larger send.

A job-title view of the list showed how small the true buying audience was: 26 contacts held marine manager or DPA titles, 56 including superintendents. For the first time, mooring-software planning could start from a few dozen named people instead of the whole list.

05 · Lessons

What we would tell you.

  • A small list of the right people outperforms a big list of everyone. For a specialist product, the size of the segment matters far less than whether the people in it have a reason to care.
  • Segment on signals people give you, not ones you infer. An opt-in, a job title or a LinkedIn interaction all beat a tag guessed from an email prefix.
  • Read small samples honestly. Twenty recipients is a small base, so the lesson is the direction, which is consistent with the other targeted sends in the same period, rather than the exact percentage.

Put It To Work

ServiceABM ProgramsServiceLinkedIn Content

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