Driving Modern Store Performance

Retail has changed

The pandemic has blown apart the traditional store P&L. With labor costs surging and store traffic being funneled towards ecommerce, retailers need to re-think their store operation–but the stakes are high. Customers are slowly experimenting with returning to stores and retailers have one chance to get it right.

Many retailers are still managing performance off paper reports and scheduling staff using Excel. This might have worked a few years ago, but between a labor shortage and increasingly discerning customers, retailers no longer have room for inefficiencies, errors, and wasted opportunities.

Planning matters more than ever

It’s not about more data–store managers already spend hours pouring over reports but most are unable to consistently find and act upon the right insights.

Rather than relying on each regional, district or store manager to interpret their numbers, Tulip uses AI-driven insights into how to optimize performance. It lets users answer questions like “which stores are falling behind on basket size goals?” in just a few clicks.

So does scheduling

Labor hours are one of the biggest costs for stores. Retailers need to ask how they can get their most knowledgeable and seasoned employees to spend more time on the floor. Scheduling in retail is plagued with oversights and inefficiencies that bog down retail performances and lead to worker burnout. In fact, 57% of retailers still manually set their employee’s schedules on a weekly basis—despite the significant time it takes and drawbacks in performance optimization.

 
AI is a game changer when it comes to staff scheduling. It can go beyond plugging people into shifts and instead looks at the resources available and their impact on historical performance to chart the right path forward. AI can see trends in performance invisible to human eyes and create optimized schedules with the shifts, people, and skills needed to maximize sales and operational efficiency. The other big benefit to AI is that it’s ready for volatility and makes re-organizing schedules to account for predicted and last-minute staff shortages almost instant.

The result

Each number shows Tulip’s impact on one retailer’s business

6h
How much time retail store managers reported saving each week on managing and actioning reports

2%
Chainwide increase in same-store sales when a 1000-store specialty apparel retailer traded manual reporting for AI-based retail diagnostics

50%
How much time retail store managers report saving on managing staff schedules when they switch from manual to automated scheduling.

10%
Increase in sales at a single store after the manager used AI-backed automated scheduling to create performance-driven staff schedules.