Context

EverydayCarry.com is the category-defining publication in everyday carry—the gear people actually use, every day. I founded it in 2009 as a product discovery platform and grew it to 380K monthly visitors and a 1M+ multi-channel audience. The site’s core function was always the same: help people find, evaluate, and buy the right gear.

Everything I built—the editorial voice, the community, the buying guides—existed to serve that.

The Problem

How do you build a product discovery engine that works when search traffic is volatile and attention has migrated to algorithmic feeds?

For years, the primary revenue model was straightforward: high-ranking SEO buying guides monetized through affiliate links. Readers searched for gear recommendations, found EverydayCarry, and clicked through to buy. It worked well—until it didn’t.

Two shifts hit at the same time. AI-generated content was flooding search results, and Google’s algorithm changes were increasing volatility in organic traffic. Meanwhile, audience attention was migrating to algorithmic feeds—TikTok, Instagram Reels, YouTube Shorts—where discovery happens through content, not queries.

The buying guide model wasn’t broken, but it was increasingly concentrated risk. I needed a product discovery channel that could reach people where they were actually spending time, and tie that discovery directly to measurable commerce.

The Insight

A real person’s curated carry is a product recommendation.

The answer was already in the community. EverydayCarry had always featured user submissions—photos of real people’s real carries. But I’d never treated UGC as a product discovery format. I’d treated it as a content supplement.

The reframe was this: a real person’s curated carry is a product recommendation. It’s arguably more credible than anything I could write in a buying guide, because it’s grounded in actual use. A software engineer’s daily carry tells you something about what a Flipper Zero is actually good for in a way a spec sheet never could.

The challenge wasn’t sourcing authentic content. It was building a system that could turn that authenticity into a repeatable, instrumented, commerce-driving engine.

The System

I designed the system around five workstreams: acquisition, curation, merchandising, distribution, and the feedback loop. Each one maps to a specific PMM function—and each one required decisions, not just execution.

1. Acquisition: Building the Intake Pipeline

I built a submission form pinned in the site navigation and linked as the primary CTA at the end of every piece of content. The form captured what mattered for product discovery: the submitter’s name, profession, location, and a detailed item list with specific makes and models. Submissions routed automatically into a Notion database, giving me a structured pipeline to work from.

The profession field was the key design choice here. It functions like a segmentation lever—it gives every submission an instant context frame (“This is what a network engineer carries”) that makes the product choices meaningful to a specific audience. That’s not a content decision. It’s a positioning decision.

2. Curation: The Editorial Gatekeeping Layer

This is where most of the product marketing judgment happened, and it’s almost invisible in the final output. The Notion board tracked submissions through stages—from intake through selection, formatting, scripting, recording, editing, and publish. At any given time, there were 99+ submissions waiting and only a handful moving through the pipeline. The selection rate was low, and deliberately so.

I selected submissions based on three criteria: photo quality (visual clarity for the format), product selection (interesting, diverse, story-worthy gear), and narrative strength (does this person’s carry tell a compelling story about how they live and work?). The curation was the product strategy layer—it determined what products got featured, to what audience, and in what context.

3. Merchandising: Turning Features into Conversion

Once a submission was selected, I editorialized it into a product discovery piece with real conversion architecture. Each item got a trackable affiliate link (tagged edcugc-20 in Amazon Associates, giving me clean attribution on every click). Then I selected a single “top pick”—one item from the carry that deserved a deeper spotlight—and built a dedicated product highlight around it with a buy button, current price, and a short editorial note on why it stood out.

The top pick selection was a merchandising call. It required understanding what would resonate with the audience, what had good conversion economics, and what told the right product story in context.

4. Distribution: Platform-Native Channel Strategy

A single submission became 10+ content outputs: a monetized site post, vertical shortform video for TikTok and Reels, a YouTube roundup segment, a podcast episode, and syndication to image-based platforms like Pinterest and Reddit. Each format was adapted to how that platform’s audience actually consumes content—not just repurposed.

The shortform script followed a tested structure: a hook built around the profession (“This is what a network engineer carries”), an item-by-item breakdown with my editorial opinions to drive engagement and product education, and an outro CTA that linked back to the submission form and the product links. The hook was a persona-based entry point. The body was product education. The outro closed the commerce loop and replenished the supply of future content.

5. Feedback Loop: Community as a Signal Source

Ending every piece of content with a clear CTA to submit your own carry did two things. It continuously replenished the top of the acquisition funnel—the system was self-sustaining. But it also generated signal. The comments and engagement on each piece told me which professions resonated, which product categories drove the most interest, and which story formats kept people watching.

That fed directly back into future curation and merchandising decisions. The community wasn’t just an audience. It was a source of voice-of-customer data.

Results

Launching the UGC system in August 2024 created a new product discovery and revenue lane that didn’t depend on search.

Over the following year, UGC affiliate revenue grew approximately 5× year over year (+398% on a rolling three-month basis, Aug ’24 to Aug ’25), tracked via the dedicated edcugc-20 affiliate tag. On TikTok, the UGC-style videos delivered 4.38M organic views across 16 videos in 2025 and grew the channel’s audience 27%—from 85K to 105K—ending a plateau that had persisted for over a year.

The format also drove discoverability through Google Discover, supplementing traditional search traffic in a way the buying guides alone couldn’t. And the system increased overall publishing output. UGC was free to source, submissions came in consistently, and the per-submission production cost was low relative to original content. That meant I could publish more frequently without increasing the team or the budget.

What I Learned

The biggest shift wasn’t tactical—it was conceptual. I stopped thinking about UGC as a content strategy and started thinking about it as a product discovery distribution strategy. The content (the videos, the posts, the syndication) was the vehicle. The actual product—the thing that created value for the audience and revenue for the business—was the product education and the purchase decision it enabled.

That reframe changed every decision downstream. It changed how I designed the submission form (profession as a segmentation field, not a curiosity). It changed how I curated (product story strength, not just visual appeal). It changed how I merchandised (top pick selection as a conversion call, not an afterthought). And it changed how I measured success—not by views or followers, but by whether the system was actually moving people toward purchase.

PMM Skills Demonstrated

• Product Discovery Architecture
  Built a five-stage system (acquisition → curation → merchandising → distribution → feedback) to convert community content into instrumented commerce.

• Audience Segmentation
  Used profession as a positioning lever, giving every submission instant context and making product recommendations relevant to specific buyer personas.

• Conversion Optimization
  Designed merchandising structure with trackable affiliate links, top pick spotlights, and buy buttons to move people from discovery to purchase.

• Cross-Channel Distribution
  Adapted single submissions into 10+ platform-native outputs (site, TikTok, Reels, YouTube, podcast, Pinterest, Reddit) to maximize discovery surface area.

Notes

Metrics tracked include UGC affiliate revenue (Amazon Associates, edcugc-20 tag) and TikTok audience/view data.
Customer acquisition cost and lifetime value were not measured in this system.