Orderful's GS1 Label Creator: A Vibe Coded Lead Gen Engine — Akram — Product Designer

Orderful's GS1 Label Creator: A Vibe Coded Lead Gen Engine

Growth DesignAI Development
Orderful's GS1 Label Creator

In July 2025, leveraging the rise of AI assisted development vibe coding, we identified an opportunity to transform Orderful's internal GS1 Label API into a public growth engine. Recognizing high SEO demand for GS1 compliance tools, I designed, developed, and shipped a standalone app.

The GS1 Label Creator has since evolved into a lead generation engine by solving a complex logistics pain for suppliers. The label app has generated over $50k in pipeline and closed a $20k deal within 90 days all while bypassing traditional development cycles.

Visit Live App ↗

Role
  • - Product Designer
  • - Developer
Timeline
July 2025Ideation & Alpha
August 2025Full Launch

The Challenge

The complexity and custom requirements of GS1 128 (UCC 128) labels leave suppliers vulnerable to steep chargebacks from major retailers for even minor barcode errors. The existing landscape was dominated by clunky, paid software, so to capture this high intent traffic, I needed to disrupt the space with a low friction solution, offering immediate, accurate compliance to suppliers while serving as a growth engine for Orderful.

What difference did we make?

Generated over

$0k

in Pipeline
Closed a

$0k

deal within 90 days
Generated

0+

labels since launch

Some context

A little bit about Orderful

Orderful is a cloud based Electronic Data Interchange (EDI) platform that enables companies to exchange complex business documents (like Purchase Orders and Invoices) with their trading partners in real time. By abstracting away the complexity of traditional EDI, Orderful ensures data compliance and accuracy, allowing suppliers and retailers to seamlessly manage their commerce operations and scale their businesses without costly manual intervention.

UCC 128 / SSCC 18 Labels

GS1 Compliant UCC 128 (or SSCC 18) labels are essential logistical identifiers used globally by suppliers to communicate shipment contents to their retail partners (such as Walmart and Amazon). Retailers rely on the machine readable SSCC 18 barcode on these labels to quickly scan and process incoming inventory at their distribution centers. Each retailer has their own unique requirements and layouts for their label. If the label is non compliant or the barcode is inaccurate, the retailer rejects the shipment or issues expensive chargebacks, making label accuracy a high stakes, mandatory requirement for every supplier.


SSCC-18 Barcode Requirements ↗

The Build

  1. Rapid prototyping with AI

    I kicked things off using Cursor to rapidly scaffold a Next.js serverless application, exploring whether "vibe coding" could handle the complexity of logistics workflows. I prompted AI to interpret GS1’s technical standards and build a SSCC-18 barcode generator. The AI not only parsed the requirements but also surfaced an NPM package for compliant barcode rendering, proving the AI-assisted approach could be built upon.

  2. Turning Documentation into Backend Logic

    For the label templates, I needed to support strict schemas for over 150 retailers. Rather than coding each field manually, I leveraged an existing spreadsheet used for API integrations by our implementation team.

    View the spreadsheet ↗

    I fed this spreadsheet into the prompt, which allowed me to programmatically generate the form requirements and field validation for every retailer. This turned a static document into a dynamic backend logic layer in minutes rather than weeks.

  3. Seamless API Integration

    With the frontend generator ready, I used Cursor to scan Orderful's public API documentation. The AI agent mapped the frontend inputs to our API endpoints with near perfect accuracy. This allowed us to move from a "dummy" generator to a live, functional tool that could generate unlimited real labels via our production API.

  4. Adapting to supplier workflows

    Demoing the single-label POC surfaced a big supplier need: batch generation. High-volume suppliers needed to produce sequential sets, not just one label. I returned to the code, prompting to utilize our API's batch capabilities. I modified the generator to accept bulk ranges eliminating a high-friction blocker task for suppliers.

  5. Programmatic SEO for retailer searches

    Marketing identified that users weren't searching for "GS1 Generators" generically, they were searching for "Walmart Shipping Label" or "Costco Barcode." early on. To capture this traffic, I wrote a script to iterate through our retailer templates and generate static, SEO optimized landing pages for every specific retailer (e.g., /labels/walmart, /labels/target). This created hundreds of backlinks for search traffic.

Design Details

Matching Orderful's Brand

I created a prompt that resulted in a simplified "bento box" layout that our marketing team used for our external branding. This modern, modular structure visually aligned the generator with Orderful's main marketing website, ensuring a cohesive brand experience.

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Reducing repetitive data entry

Repeating the same data slows everyone down so the app persists key information intelligently. Company Prefix and Extension Digit are cached across the app, Ship From address is cached globally, and Ship To address is cached for each label, anticipating repeat shipments.

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The app also automatically increments the serial reference in SSCC 18 barcodes for batches, so suppliers don't need to manually update the serial number with each new label, reducing the risk of errors when generating multiple labels in a batch or when starting a new batch.

The Growth Engine

Email Data Collection

I implemented a one time email collection modal that triggers just before the first successful label generation. This feeds directly into HubSpot, tagging the supplier as a Marketing Lead.

Contextual Upsells

I added a little upgrade prompt to "Book a Demo" specifically when suppliers were filling out manual fields that Orderful's core product would automate. This is a subtle way to upsell the core product to suppliers who are already using the generator.

Usage Limits

We set a generous 10 label limit per generation, prompting high volume suppliers to contact sales for an enterprise solution.

The Growth Engine

Soft Launch

We shipped with zero paid spend, relying solely on social posts (LinkedIn/Twitter) from the company and the team. The utility of the tool drove immediate organic traction, resulting in 1,000+ labels generated in the first month.

Paid Acceleration

In month two, we layered in Google Ads. Because the landing pages were highly specific (e.g., "Home Depot Label"), quality scores were high. We immediately began seeing direct attribution to sales conversations and closed deals.

What difference did we make?

Generated over

$0k

in Pipeline
Closed a

$0k

deal within 90 days
Generated

0+

labels since launch

Summary

The Vibe Coding Paradigm

This project served as a successful case study for a new way of working. By acting as the architect while AI handled the implementation details, I condensed a project that typically takes weeks of engineering resources into a few days of focused "vibe coding." It proved that I can build powerful, compliant, and revenue generating tooling outside the scope of the traditional product roadmap.

This success also kicked off a conversation with the engineering team about the future of product development. We are now actively exploring the use of AI to generate entire MVPs for new products, moving the methodology from external tools into the core product line.

The conversation has fundamentally shifted from "How can I build this?" to "How fast can I ship it?"