LYLynn YangGrowth Marketing Portfolio
Acquisition System · Case 01

AI-Assisted PR & Media Acquisition Workflow

Scaling qualified media outreach without sacrificing relevance, personalization, or human control.
Translated a manually validated PR outreach process into an AI-assisted workflow covering media discovery, qualification, contact research, pitch drafting, quality scoring, approval, sending, and tracking.
92–96%
Less Active Handling Time
Reduced daily hands-on research and drafting time through automated processing and human review.
18.9% / 14.7%
Positive Response Rate
AI-assisted workflow compared with the previous manual baseline.
9.4% / 7.6%
Confirmed Collaboration Rate
Confirmed media collaborations compared with the previous process.
01 · The Scaling Problem

Increase processing capacity without lowering media relevance

The bottleneck was not simply writing emails. Each target still required evidence-based qualification, usable contact research, a credible product angle, and quality control before outreach.

System principle

AI accelerated repetitive research, classification, drafting, and scoring. Targeting standards and final approval remained human-controlled.

02 · Workflow Overview

Turn a manually validated PR process into a connected operating system

The original workflow visual shows how discovery, qualification, contact research, drafting, email scoring, approval, sending, and tracking connect within one system.

AI-assisted PR media outreach workflow
Workflow overview · click to enlarge
03 · Decision & Quality Control

Define both who enters the outreach queue and what is ready to send

Target qualification and email approval were handled through separate standards rather than treating every discovered outlet or generated draft as send-ready.

Media evaluation model
Media qualification framework covering hard filters, weighted criteria, priority tiers, and next-action rules.
04 · Operational Output & Media Outcomes

Connect structured output with real replies and published coverage

The media queue, positive response, and coverage examples are presented together as evidence of how the system moved from qualification to external outcomes.

Media value was not defined by reach alone. Different outlets qualified for different reasons: broader publications supported visibility and third-party credibility, while relevant review outlets supported deeper product testing and repeat coverage.

Operational output

Actionable Media Queue

The workflow converted research into a structured output containing relevance evidence, contact status, qualification score, priority tier, recommended pitch direction, and next action.

Qualification EvidencePriority TierNext Action
Qualified media output table
External validation

Selected Positive Response

A representative reply showing that qualified outreach progressed into a real media opportunity. The example is used as outcome evidence rather than as proof of every outreach result.

Qualified OutreachPositive ReplyNext-Step Opportunity
Selected positive media response
Different qualification value

High-Reach National Publication

Selected for broad consumer visibility and relevant lifestyle and product-review coverage. This type of outlet supported wider brand reach and third-party credibility beyond the core home-brewing audience.

Broad Consumer ReachBrand VisibilityThird-Party Credibility
High-reach publication coverage example
Different qualification value

Relevant Review Outlet with Repeat Coverage

Selected for strong technology and hardware review fit, detailed product-testing format, and continued coverage potential. The brewer review was followed by a second review focused on a new ingredient kit.

Strong Product FitIn-Depth ReviewRepeat Coverage Potential
First Impulse Gamer review
Brewer review example
Second Impulse Gamer review
Follow-up ingredient kit review example

What This Workflow Established

The project established a reusable PR acquisition system that converted media qualification, pitch matching, quality review, and tracking into structured operating rules. AI increased processing capacity and reduced repetitive handling, while human control remained responsible for targeting standards, final approval, strategic exceptions, and active media relationships.