Influencer Marketing · Campaign Optimization

Optimizing Influencer Matrix for Higher Engagement

From aspirational professionals to relatable micro-influencers — a data-driven pivot that doubled engagement

Project Length

Q3–Q4 2025

6 months

Client

Duet

Influencer Marketing

My Role

Marketing Consultant

Freelance · Strategy & Campaign

Engagement Type

Freelance Consulting

Strategy & Execution Support

00

Background

Duet is a Hong Kong–based social app ("Meet People You Resonate With") expanding into the US market. The team had traction in Asia but no playbook for US influencer marketing — unfamiliar with creator pricing, audience behavior, and what content formats actually convert.

I joined as a freelance marketing consultant to research the landscape, build a budget-aligned influencer strategy, and help execute a campaign that could validate Duet's US growth model.

Overview

Duet's original influencer play — polished content from high-end professionals — looked great but didn't convert. I pivoted the strategy to micro-influencers and student KOCs, cutting CPE by 40% while more than doubling engagement.

Goal: Find the right creator mix for Duet's US launch — higher engagement, lower CAC, within budget.

01

Discover

The Original Plan

Duet launched with "High-End Professionals" — polished creators with aspirational lifestyles. The bet: premium content quality would drive downloads.

It Didn't Work

In the US market, users see social apps as peers, not status symbols. The aspirational content created an invisible wall — viewers watched but never felt "this is for me." CPE stayed high, engagement stayed flat.

Baseline Performance (High-End Influencers)
Engagement Rate
2.8%
CPE (Cost per Engagement)
High
Low Engagement

Likes and comments per view below industry benchmarks despite high production quality.

No Product-Market Fit in Content

Aspirational content didn't match Duet's core value proposition — genuine connection over status.

02

Define

The Pivot

I dug into competitor campaigns, KOC pricing tiers, and comment sentiment across similar social apps. The signal was consistent: for social-discovery products, relatable creators outperform aspirational ones on every engagement metric.

The Aha Moment

While analyzing a competitor's campus campaign, I noticed student-created "day in my life" posts had 3–4× the comment rate of polished brand spots — and the top comment was always "What app is this?" That's when I knew KOCs were the channel.

Why students? Product-market fit. Duet's matching algorithm is built around shared interests — a use case that maps perfectly to campus social life. Students aren't just cheaper creators; they're the actual target user, which makes their content inherently authentic.

From this research I built a selection framework I call the "ARC Model":

Authenticity

Does the creator's content feel genuine? Would you believe they actually use the product?

Relatability

Does the audience see themselves in this creator's life — dorms, study groups, daily routines?

Community

Does the creator spark conversation? High reply rates signal a real community, not just passive followers.

High-End Professionals

Aspirational · High CPE · Low engagement

Student KOCs & Micro-Influencers

Relatable · Low CPE · 2.5× engagement

Influencer Content

Real creator content from micro-influencers and student KOCs — swipe to explore

03

Develop

Campaign Execution

Applied the ARC Model to recruit, brief, and launch a new creator cohort — then tracked performance to optimize spend in real time.

ARC-Based Selection

Scored every creator candidate on Authenticity, Relatability, and Community engagement — replacing the old "follower count + production quality" filter.

Creator Recruitment

Recruited 12+ student and micro-influencer KOCs across US campuses, briefed on "day in my life" formats that naturally integrate Duet.

  • Phased Budget: Started small, validated CPE, then scaled spend on top performers
  • Content Guardrails: Provided loose briefs (dorm life, study routines, friend hangouts) — not scripts — to preserve authenticity
  • Performance Tracking: Monitored CPE, comment sentiment, and install-intent signals weekly to reallocate budget
04

Deliver

Results

2.5×
Engagement Rate
vs. baseline
↓ 40%
CPE
Cost per Engagement
12+
Creators
recruited & launched
Lower
Implied CAC
via higher install-intent
Before vs. After
Engagement Rate
Before
2.8%
After
7.0%
CPE (lower = better)
Before
High
After
↓ 40%
Validated Persona

Student KOC content 2.5× engagement rate vs. high-end professionals. Comments shifted from passive to "What app is this?"

Budget Efficiency

40% lower CPE means more engagements per dollar — and higher install-intent signals that indirectly reduce CAC.

Reusable Framework

The ARC Model and phased-budget playbook are now Duet's standard for all future influencer campaigns.

Install-Intent Lift

Comment sentiment analysis showed a clear increase in download inquiries and "link in bio" clicks.

"Libin's strategy gave us a clear, budget-friendly path into the US market. The ARC framework turned a scattered influencer approach into a repeatable system — and the engagement numbers proved it."

— Duet Marketing Team

Impact

Delivered a validated influencer growth model for Duet's US expansion: the ARC selection framework, a phased-budget playbook, and proof that authenticity outperforms aspiration for social-discovery products. The model is now Duet's standard for all influencer campaigns going forward.