How Kipling Uses Customer Service Metrics to Create Schedules That Drive Sales

The Problem 

In early 2024, Kipling’s North American retail team faced a common but complex issue: how to maintain premium customer service without over- or under-spending on labor, especially in lower-volume stores with unique demands. 

While Net Promoter Scores (NPS) remained high, scheduling decisions were still largely driven by traditional metrics like Sales Per Hour (SPH), which didn’t fully capture the nuances of store operations. 

Lack of visibility was the root problem. 

– Some stores were over-scheduled during quiet periods. 

– Others, particularly in remote or low-traffic areas, weren’t leveraging their full labor capacity. 

And while associates were completing critical tasks like inventory, floor sets, or off-site support, these non-selling hours were rarely tracked, making it difficult for store managers to advocate for the resources they truly needed. 

The Pivot 

Kipling’s leadership began asking better questions: 

– “Where are we seeing inefficiencies in how labor is allocated?” 

– “Are we scheduling to traffic — or out of habit?” 

– “Can we empower stores to self-manage their time more strategically, without compromising service?” 

Sales forecasts weren’t enough. The data was there but it wasn’t telling the full story. Shifting patterns like rising Monday foot traffic in certain regions and untracked task time made it clear: Kipling needed a new perspective on labor planning. 

The decision was made to adopt a more customer-centric metric: Traffic Per Labor Hour (TPLH). 

Schedule That Prioritizes Customer Service 

Unlike SPH, which focuses purely on revenue, TPLH zeroes in on customer engagement, the number of customers an associate can tend to each hour.  

It provides a precise view of how labor is being used relative to transaction flow throughout the day.  

Here’s what makes it powerful: 

– It spotlights service opportunity, not just sales performance. TPLH helps Kipling understand when and how often customers are interacting with associates, and whether the right staffing is in place to support those moments. 

– It reveals hidden inefficiencies. With TPLH, Kipling can identify where teams are overstaffed during low-traffic windows or under-resourced during high-volume bursts, especially on weekends. 

– It helps stores reclaim downtime. By identifying underutilized hours, teams can reassign non-selling tasks (like inventory or RFID projects) to quieter times, keeping the focus on customers during peak hours. 

It drives scheduling precision. TPLH data allows managers to build smarter, more targeted schedules that align with foot traffic trends, ensuring customers aren’t left waiting and associates aren’t standing idle. 

Still Early, But Already Working

Although Kipling only launched TPLH in January 2025, early results are already validating the shift: 

– Improved weekend scheduling across key locations. 

– Higher utilization of non-sell hours during low-traffic periods. 

– Cross-store visibility into what’s working and what isn’t. 

– A growing culture of data-informed decisions, where labor planning doesn’t compete with service. 

Want the Full Kipling Story? Hear It Live in NYC. 

Join us at the StoreForce Road Show in New York City, where Kipling’s leadership will walk you through their labor transformation, the questions they asked, the strategy they adopted, and how they’re building a culture of data-driven performance. 

Register Today! FREE for Retail leaders | Seats are limited.