How Kipling Boosted Visit Value by 200 Basis Points

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.

Even with strong Net Promoter Scores (NPS), Kipling’s North American stores faced a challenge familiar to many specialty retailers: labor wasn’t always aligned with sales opportunity.

– Selling hours overloaded on weekdays, underutilized on weekends.

– Non-selling tasks cutting into peak customer-facing time.

– Inconsistencies between stores on how labor was used and why.

At the same time, associates completed critical tasks like inventory, floor sets, or off-site support. However, those non-selling hours were rarely tracked. As a result, store managers struggled to advocate for the resources they truly needed.

The Turning Point

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?”

– “Why are all my selling hours on a Tuesday when I need them on weekends?”

Leaders quickly realized the issue wasn’t just labor itself. It was how they were thinking about labor. Legacy planning models, like Sales Per Hour (SPH), didn’t tell the full story. Meanwhile, changing customer patterns, such as rising foot traffic on Mondays in certain markets, were going unnoticed. Therefore, they needed to shift from reactive firefighting to proactive, data-led planning.

That shift started with adopting Traffic per Labor Hour (TPLH) as the primary metric.

What is Traffic per Labor Hour?

Traffic per Labor Hour (TPLH) is a key retail productivity metric that measures customer traffic relative to labor hours worked. In short, it helps retailers decide how many employees should be scheduled during a shift to maintain service quality and labor efficiency.

How to Calculate TPLH

Here’s the formula:

Example: If a store sees 100 customers during a shift with 20 labor hours scheduled, its TPLH is 5. This means that, on average, 5 customers were supported per labor hour. By using TPLH, Kipling aligned staffing levels with customer traffic, optimizing both service quality and labor costs.

Why It Matters

TPLH focuses on service opportunity, not just sales performance. It helped Kipling understand when customers interacted with associates and whether the right staffing supported those moments.

Additionally, it revealed hidden inefficiencies. With TPLH, Kipling spotted overstaffing during low-traffic periods and under-resourcing during busy times, especially on weekends.

Furthermore, TPLH helped stores reclaim downtime. By shifting non-selling tasks (like inventory or RFID projects) to slower hours, teams maximized their customer focus during peak periods.

Finally, it improved scheduling precision. TPLH data allowed managers to build smarter schedules aligned with real customer traffic, reducing wait times for shoppers and idle moments for staff.

Get The Foundation Right First, Then Optimize

Before making major scheduling changes, Kipling focused on visibility first. They made sure every optimization had purpose, not just optics.

“You have to lay the foundation before you can optimize,” said Kara Flood, Head of Stores. “If you’re only reacting, you’re always behind. But when you’re proactive with the right data upfront, you can shift before problems start.”

With StoreForce, Kipling achieved measurable results:

– Measure Visit Value by day and segment, revealing where and when stores were missing opportunities, including a 200 basis point improvement by focusing labor during peak hours.

– A $1M annualized revenue opportunity by identifying their peak weekend hours.

– Expose Traffic per Labor Hour (TPLH) inconsistencies across stores, providing clear benchmarks for managers to target.

– Equip store managers with the Reforecasting Tool to add or reduce hours based on real-time trends.

A Cultural Shift: Ownership, Confidence, Growth

Kipling’s success was about more than data. It was about changing the conversation around labor. Store managers no longer viewed schedules as fixed; instead, they saw them as business strategies.

“It’s not about cutting hours,” Kara explained. “It’s about making every hour count.”

This shift happened across the organization:

– Finance gained trust in store-level decisions.

– District Managers became coaches and partners, not just reviewers.

– Associates saw firsthand how better planning led to better customer experiences.

As a result, Kipling created a ripple effect: stronger store performance, empowered leadership, and a company-wide expectation that labor planning drives growth, not just coverage.

As one leader summed it up, “When everyone’s using the same data, the right decisions feel obvious.”

What’s Next?

With this foundation firmly in place, Kipling is moving forward with confidence in the way their teams think about labor altogether.

The next phase of their journey is already underway:

– Expanding Super User programs to strengthen leadership capability across all stores.

– Continuing to benchmark Visit Value and TPLH to guide smarter hiring and staffing models.

– Leveraging StoreForce to fine-tune labor coverage by the hour, by store, and by segment.

Now, labor planning isn’t just about filling shifts. It’s about building a smarter, more profitable, service-driven business.

If you’re ready to stop guessing and start leading with refined data, we can help.

Read the full breakdown of how TPLH works and how it can help you build smarter schedules that drive results.