Overview
Bass Pro Shops manages a large catalog of private-label and third-party products. I designed an AI-assisted product onboarding experience that helps merchandising teams validate product information, generate customer-ready content, review listings, and publish products through a structured workflow.
Powering Product Onboarding at Enterprise Scale
Bass Pro Shops manages a diverse product catalog that includes both private-label and third-party merchandise. Before a product can be published, merchandising teams need to validate product information, enrich missing details, create customer-facing content, and ensure every listing meets publishing standards.
As the catalog continues to grow, maintaining speed, consistency, and accuracy becomes increasingly challenging. The opportunity was to redesign this operational workflow into a unified AI-assisted experience.
Business Goals
Streamline the product onboarding workflow.
Reduce repetitive manual effort across merchandising tasks.
Improve consistency in product listings.
Accelerate publishing readiness without compromising quality.
Keep human review central to every publishing decision.
Product Scope
The platform serves as an operational workspace where merchandising teams prepare products for publication by combining product data, AI assistance, and structured review into a single workflow.
Product Data Ecosystem
SFTP
ERP
PIM
WMS
Catalog
Legal
AI Product Onboarding
Basspro.com
Preparing Products Was More Complex Than Publishing Them
Publishing a product wasn't a single action. It involved validating information, reviewing assets, creating customer-facing content, resolving missing data, and preparing listings for approval across multiple operational steps.
As product volume increased, these activities became repetitive and difficult to manage efficiently, creating an opportunity to redesign the workflow instead of optimizing individual tasks.
Existing Workflow
SFTP
ERP
PIM
Catalog
Legal
Validate Data
Create Content
Review
Publish
Fragmented Product Data
Product information originated from multiple enterprise systems, requiring users to consolidate and verify information before moving forward.
Repetitive Operational Tasks
Teams repeatedly validated product attributes, reviewed assets, generated content, and followed up on missing information for every listing.
Inconsistent Publishing Readiness
Missing details or incomplete product information often delayed the publishing process and required additional review cycles.
Business Goals
The objective wasn't simply to redesign an internal tool. It was to create a scalable product onboarding workflow that reduced operational effort while maintaining the quality and consistency required for enterprise merchandising.
Designing Human + AI Collaboration
AI wasn't introduced to automate the entire workflow. Instead, it was applied where repetitive, pattern-based tasks could be accelerated while keeping business-critical decisions under human control.
The goal was to reduce manual effort without removing accountability from the merchandising team.
AI Detect missing or inconsistent information
Verify recommendations
AI Generate titles, descriptions, and SEO content
Review and refine
Identify potential quality issues
Approve final assets
Draft contextual follow-up emails
Review and send
Support publishing readiness
Approve and publish
Design Principle
Automate repetitive tasks.
Preserve human judgment.
AI Handles
Validation
Content
Recommendations
Quality Checks
Human Handles
Review
Approval
Publishing
A Guided Workflow for AI-Assisted Product Onboarding
Instead of treating product publishing as a collection of disconnected tasks, I redesigned the experience into a structured workflow that guides merchandising teams from product data to publication.
Each stage has a clear objective, while AI supports repetitive tasks such as validation, content generation, and product review. Users remain in control throughout the entire process, ensuring every listing is reviewed before it goes live.
Product Data
Data Gathering
Content Generation
Preview & Edit
Publish
Basspro.com
Building a Trusted Product Foundation
Every successful product listing starts with complete and reliable product information. The Data Gathering stage brings information from multiple enterprise systems into a single workspace, allowing merchandising teams to validate product details, identify missing information, review assets, and resolve issues before moving to content creation.
By establishing a trusted product foundation early, the rest of the workflow becomes faster, more consistent, and easier to review.
"Good AI starts with good data."
What AI Does
Product readiness progress
AI missing information detection
Image validation
AI-generated email assistance
Enterprise data sources
Key Capabilities
Consolidate product information from multiple enterprise systems
Detect missing product attributes with AI
Validate product images and supporting assets
Generate contextual vendor communication for missing information
Track product readiness before progressing to the next stage
Turning Product Data into Customer-Ready Content
Once product information is validated, the workflow shifts from data preparation to content creation.
Using validated product attributes, AI generates product titles, descriptions, feature highlights, and SEO metadata, giving merchandising teams a strong starting point instead of a blank page. Every suggestion remains editable, allowing users to refine content before moving to the final review stage.
"AI creates the first draft. People create the final product experience."
What AI Does
AI-generated product title
Product description editor
SEO metadata generation
AI Assistant for content refinement
Editable AI suggestions
Key Capabilities
Generate product titles and descriptions
Create SEO-friendly metadata
Produce feature highlights from product attributes
Refine content through contextual AI assistance
Edit and regenerate content before approval
From AI Suggestions to Publish-Ready Listings
The final stage brings together validated product data, AI-generated content, and merchandising expertise into one review experience.
Before publishing, users can review every recommendation, refine product content, verify assets, and ensure the listing meets business and merchandising standards.
Once approved, the product is ready to be published with confidence.
"Publishing isn't the beginning of quality. It's the result of it."
Human in the Loop
Product preview
Editable AI content
Final validation
Publish confirmation
Key Capabilities
Review AI-generated content before publishing
Edit product information and merchandising copy
Verify images and product assets
Preview the final customer-facing listing
Publish approved products through a guided workflow
Delivering a Smarter Product Onboarding Experience
The redesigned workflow transformed product onboarding from a collection of disconnected operational tasks into a structured AI-assisted experience. Rather than replacing human expertise, the platform reduced repetitive work and helped merchandising teams prepare products with greater consistency and confidence.
Business Outcomes
Unified fragmented product onboarding into a single operational workflow
Reduced repetitive merchandising tasks through contextual AI assistance
Standardized the journey from product data to publication
Improved publishing readiness through staged validation and review
Product Outcomes
AI integrated directly into the workflow instead of becoming a separate tool
Clear four-stage workflow reduced context switching across operational tasks
Human approval remained central to every business-critical decision
Built on top of existing enterprise systems without disrupting existing processes
My Contributions
End-to-end product experience design
Workflow architecture
AI interaction design
Information architecture
Enterprise UI design
Design system adaptation
Developer handoff and implementation support
The best AI experiences don't replace expertise. They amplify it.
This project reinforced that successful AI products aren't defined by how much they automate, but by how well they support human decision-making.
Working on an enterprise workflow taught me to think beyond individual screens and focus on how information, people, and systems come together to complete a business process. Every design decision, from structuring the workflow into four stages to embedding AI contextually, was driven by the goal of reducing operational complexity without sacrificing user control.