Retail Insights

Why the Merchandise Planner Still Owns the Plan in the age of AI

AI is changing what merchandise planners do every day. It's not changing who owns the plan.

Retail Insights

What Separates Successful Retail Tech Implementations from Failed Ones

Most retail planning implementations fail for many reasons: how the project was scoped, who owned what, and how success was defined. Here's what the successful minority does differently.

Retail Insights

Wholesale Drives Revenue. Nobody's Planning for It.

Wholesale moves more inventory than most brands' and retailers DTC channels combined, but it consistently gets less planning rigor, less data infrastructure, and less organizational attention.

Retail Insights

Consumer Demand Is Fragmenting: Why The “Average Customer” Is Gone

Consumer demand is fragmenting across every major retail category. Here's what's shifting, why your historical data is the last to know, and what planning teams need to do differently.

Learning Series

Rebuilding Your Weekly Retail Recap in Claude Start to Finish

Most planning teams burn the first hour of every week building the same sales recap by hand. Here's a step-by-step workflow to get Claude to do it, analysis and dashboard included.

Retail Insights

48 Nations, One Buy: The World Cup and Sports Retail's Most Complex Buy

For sporting goods or licensed apparel retailers, the World Cup is the hardest buy of the year. Here's why broad loses and deep is a bet.

Learning Series

Setting Up a Claude Project for Your Retail Category — Template + Walkthrough

Most planners who try Claude start over every conversation. A project fixes that. Here's how to build one for your category with a free downloadable template and guided walkthrough.

Retail Insights

The AI Reckoning in Retail Planning: What Boards Are Demanding vs. What's Possible

Boards are mandating AI. Planning teams are scrambling to translate that into workflows. Here's an honest breakdown of what AI in retail planning actually does today, what's still vaporware, and the data quality prerequisite most conversations skip entirely.

Retail Insights

Why 95% of Retail AI Projects Fail, and What the 5% Do Differently

The reason most retail AI projects fail isn't the technology, it's the organizational work that never happens before it's deployed.