Work / Campaign Operations
Case Study 01
A research-led outbound workflow for senior financial audiences
Deal-news research feeds custom email sequences. Cadence execution, deliverability review, and engagement QA close the loop. The result is outbound that senior audiences actually open, and a measurable case for where research effort pays off.
Context
Outbound campaigns targeting senior investment-banking and private-equity audiences across three markets. Generic outreach underperforms with these audiences, so the campaign needed personalization that was genuine but still scalable.
What I built
A research-to-message pipeline. For each target firm, I monitor recent transactions, press, and public activity on a rolling 60-day window, then write a four-step email sequence anchored to their actual deals. Each step takes a different angle: deal congratulations, founder-transition perspective, buyer education, then process value.
- A structured working file tracks research status across 52 firms, so effort is never duplicated and no firm receives a guessed-at message.
- 18 firms with usable recent news received full custom sequences: 72+ emails referencing real acquirers, deal structures, and industry nuance rather than merge fields.
- I ran the full campaign operation around the messaging: list preparation, cadence setup and scheduling, deliverability review, and weekly reporting.
"Congratulations on advising ████████ on its acquisition by ██████████. Helping a deeply technical, founder-led business like the one built by ████ ████████ transition to an institutional platform is incredible work…"
Evidence
Three cadences ran at different personalization depths. Engagement varied by list quality, personalization depth, and offer placement:
| Cadence | Delivered | Open | Click |
|---|---|---|---|
| Deep: per-firm sequences | ~530 | 63% | 21% |
| Medium: segmented, custom intros | ~430 | 34% | 3% |
| Light: broad list | ~560 | 19% | 5% |
Open rate showed the clearest lift from research-led personalization. Click rate was reviewed separately, because CTA placement, asset relevance, and automated link scanning can distort raw engagement. Open rate is treated as a directional signal given privacy-related tracking limitations. Follow-up lists were built only after click-pattern QA (send-to-click timing and multi-link bursts).
Outcome
Sales received a prioritized, QA'd follow-up list instead of a raw click export, so follow-up time went to genuine interest. The personalization-depth comparison gave leadership a measurable basis for deciding where research effort is worth it.