03 Research & Strategy

Research & Strategy

Research is valuable when it helps the product make better decisions. This section includes competitive analysis, content-led growth research, and product thinking around onboarding and activation. Research is not about producing a beautiful deck — it is about answering what is worth doing, what should wait, and what to watch next.

Petch Competitive Analysis

Independent product research · Competitive strategy · Pet social category

Petch already looks quite complete: matching, maps, messaging, events, AI assistance, rewards, and subscription monetization are all in place. But its real problem is not missing features — it is product rhythm. Before users understand the value or build trust, the product asks for too much information, introduces incentives, and starts talking about monetization.

Core Diagnosis

Petch pursued completeness before it built trust.

The key question is not whether features are covered, but whether the right features appear at the right user moment.

Main Issues I Found

Product Path

Complete, But Not Clear

Petch has many feature layers, but after entering the product it is hard for users to quickly understand what to do next and which path is the core experience.

Onboarding

Input Before Value

The product collects too much information at an early stage, increasing the mental and operational burden of first use.

Monetization

Monetization Before Trust

Ads, subscriptions, and paid benefits appear too early. Users are asked to pay for value they have not yet felt.

Incentives

Gamification Mismatch

Points, rewards, and badges can turn relationship-building into task-completion, weakening the light, natural community experience.

Matching

Swipe Logic Assumptions

Pet social matching should consider distance, personality, play style, energy level, and offline feasibility — not just swipe speed.

Product Tone

Functional, But Cold

For a product that helps users build local, low-pressure relationships, whether it feels safe, natural, and unstressed matters as much as whether it works.

Pawly's Opportunity

Light

Reduce the operational and mental friction of first use as much as possible.

Smooth

Organize the experience around a natural core path: map discovery → event participation → offline meetup → repeat connection.

Warm

Make the product feel more like a trustworthy, friendly local community than a cold match or transaction.

Restrained

Validate core behavior and local network density before gradually introducing more complex features and monetization.

Read Full Competitive Analysis

A deeper PDF analysis covering product rhythm, onboarding burden, monetization timing, gamification mechanics, matching logic, product tone, and strategic implications for Pawly.

Pawly Content & Account Research

Pawly · Product Management Intern · Growth & Strategy

Content-led growth research · Creator pattern analysis · Account archetype strategy · Activation hypotheses · Brand positioning

I systematically reviewed the pet content ecosystem and representative accounts, then mapped different content formats to specific Pawly product goals: which content drives attention, which builds trust, which pushes profile completion, and which helps users understand the product.

Core Thesis

Pawly should not chase pet-content traffic alone.

The more important role of content is to gradually turn pet-parent emotional resonance into product understanding, trust, and actual usage.

Content Types I Focused On

Storytelling / Meme

Easier to gain exposure, create resonance, and be shared at low cost.

POV / Educational

Build professional trust through concrete, practical scenarios while explaining the problem Pawly solves.

UGC Prompts

Lower participation barriers, making it easier for users to contribute and gradually form sustainable community interaction.

Pet Personality

Drive profile completion and identity formation, bridging content browsing to product activation.

Strategic Insight

Storytelling content makes users see Pawly. POV and educational content help users understand and trust Pawly. Pet personality content further carries profile completion and identity, while UGC topics help the community build sustained participation.

Pawly's Content Strategy

Visibility

Start from real pet-parent emotions and daily friction to create content that resonates and is worth sharing.

Trust

Use specific scenarios to explain pet compatibility, whether meetups are safe, and how a low-pressure social moment can begin.

Activation

Use pet personality content to naturally guide users from browsing to profile completion, then toward identifying with a Pawly Type.

Community Loops

Turn small moments of pet-parent life into sustainable community content and interaction through low-barrier, UGC-friendly topic design.

Read Full Content Research

A deeper PDF appendix covering account archetypes, creator behavior, content-led growth strategy, activation hypotheses, and implications for Pawly brand and product positioning.

03 Data & Behavioral Research

Behavioral Analytics Capstone Poster Preview

Data & Behavioral Research

PM Lens

This project taught me that finishing a prediction is not the same as creating product value.

For AI products adjacent to mental health, the harder questions appear after a signal is detected: how to explain uncertainty in results, how much information to show, when intervention is appropriate, how to obtain genuine and sufficient informed consent, and how to avoid compressing a complex, vulnerable mental state into a cold score.

The product value lies not only in detecting risk, but in designing the boundary between signal, interpretation, user autonomy, and care.

Data & Product Research

Behavioral Analytics Capstone: Depression Risk Prediction

This study combines behavioral and survey data to analyze patterns related to depression, with focus on signal quality, interpretability, and the difference between two types of data:

Pilot data with a smaller sample but richer behavioral dimensions; and larger-scale population survey data that serves as a stable benchmark. It is included in the portfolio to show my analytical training, research judgment, and ability to translate data conclusions into product questions and product decisions.

What This Shows

— Analyzing and judging behavioral data
— Distinguishing valid signals from statistical noise
— Combining data science with product research
— Thinking about explainability, informed consent, and intervention boundaries in AI or health-related products

Open PDF

Academic capstone output.

All materials shown have been reviewed and limited to publicly shareable, non-confidential content, while preserving the original product reasoning, documentation structure, and decision logic as fully as possible.