Turn data into performance

If the data doesn’t change behavior, it’s just reporting.

tRS helps apparel retailers connect commercial outcomes with the behaviors that drive them — so every store and every team member knows what to work on next.

Illustrative pilot

65 → 82

One apparel retailer · 15 stores · 10 weeks Overall Store Score moved from 65 to 82 in the pilot. Full context and supporting results are shown below.

The challenge

You already have the data. So why isn’t performance higher?

Sales, conversion, ATV, UPT, labor, capture and task data are usually available. The harder question is what each store should change next.

The opportunity

Make performance visible at the level where it can actually change.

Store Score works at both levels: the store as a whole and the individual people whose behaviors drive the result.

Store performance

Store Score creates a weighted view of execution that shows each store what matters, where points are being lost, and what to focus on next.

Individual performance

Within the same Store Score model, leaders can drill down to individual performance to see who is driving results, who is improving, and where coaching will help.

Real results

Higher performance. Stronger teams.

One apparel retailer. Ten weeks.

The Overall Store Score is a weighted 100-point view of store execution, combining the measures most closely tied to performance — typically conversion, ATV/UPT, upsell, customer capture, labor deployment and task execution.

Overall Store Score

65 → 82 10 weeks after the program started

+15%

Sales

Illustrative chain-level improvement

+20%

Average Transaction Value

At one improved store

+12%

Units Per Transaction

Behavior visible in the basket

+25%

Add-on Sales

Example improvement in upsell behavior

Why behavior changes

Measurement becomes useful
when people can see cause and effect.

Specific

Know exactly what to improve.

Controllable

Focus on behavior people can influence.

Visible

See whether the change is working.

Fair

Use objective measures for coaching.

Motivating

Create ownership and healthy competition.

Repeatable

Reinforce progress until it becomes a habit.

Most performance data helps managers manage people.

What if its more powerful use is helping people manage themselves? When teams can see their own numbers and see those numbers changing, measurement becomes motivation.

Case study at a glance

What changed?

In a 10-week test using Store Score in a sample of 15 stores, these were the results.

Overall Store Score 65 → 82 Weighted 100-point view of store execution

Chain sales ~15% Increase across the store network

Surprises Good stores improved too Opportunity was not limited to underperformers

Coaching More visible Training gaps surfaced at store and individual level

Example: one store under a new manager

60s → 90sStore Score

~40%Sales vs. prior year

~20%ATV improvement

↑Upsell & customer capture

The point is not just that the numbers moved. The business could see which behaviors were changing the result.

Sustaining the change

Measurement first creates the change.
Later it helps protect it.

Behaviors can become habits and team norms — but solved problems can also return. Ongoing measurement helps spot regression before it becomes normal again.

Measure

Focus

Improve

Reinforce

Normalize

Teach

Monitor

Continuous Improvement

Early Stage

Visible metrics create focus, encourage behavior change, and show whether the change is working.

Later Stage

Repeated behaviors become habits and team norms. Measurement remains valuable as an early-warning system when solved issues start to return.

A practical operating loop: measure, focus, improve, reinforce, normalize, teach and monitor.

Built for apparel

We understand your business.

Our focus is narrow by design. We work specifically in apparel and related specialty retail, so the measures and coaching logic reflect how stores actually operate.

Apparel specialists

Not generic BI.

Connect your data

Bring together the commercial and operational picture.

Designed for store teams

Simple enough to use, powerful enough to coach from.

Measurable results

See the difference in performance and behavior.

A different way to manage store performance

What would happen if more of your stores executed like your best ones?

The first step is understanding where the controllable execution gap actually sits.