From Chaos to Clarity: Turning Retail Data into Real Results
Executive summary
Retailers generate more data than ever, but too often it goes unused or misunderstood. Collecting numbers is meaningless without a plan to act on them. Here’s the core message: break down silos, focus on NPS and loyalty, and equip store teams to turn data into measurable business results.
Turning Retail Data into Real Results
Retail has never lacked data. POS systems, traffic counters, online behavior, inventory levels, and customer profiles. Every store and channel generates more of it each day. The problem isn’t collecting information. The problem is doing something with it.
“Data is like garbage. You better know what you are going to do with it before you collect it.” Without a clear plan, retailers risk drowning in numbers that remain siloed, inaccessible, or misunderstood. It raises a tough question for every executive: Are your decisions truly data-driven—or are they still based on instinct and guesswork?
The risks of ignoring data
The risks of ignoring data are real. Stock imbalances, generic marketing, preventable errors, and poor planning are all common when information is stuck in silos. In fact, up to 90% of collected data in retail goes unused, leaving teams to fall back on gut decisions or depend entirely on analysts and IT.
Additional barriers include:
– Lack of data literacy: Staff don’t understand or trust outputs.
– Overcomplicated tech: Tools are purchased but never fully integrated.
The consequences are costly:
– Operational inefficiencies and resource misallocation.
– Wasted marketing spend on generic campaigns.
– Slow reactions to market trends.
– Eroded customer trust, preventable churn, and broken omnichannel journeys.
In today’s landscape, guesswork isn’t just expensive—it’s preventable.
Why NPS and loyalty matter more than ever
If there are two metrics retail executives should anchor to, they are the Net Promoter Score (NPS) and customer loyalty. These aren’t just subtle outputs—they are direct signals of brand trust and long-term revenue potential.
According to the 2025 Global Satisfaction & Loyalty Report from XM Institute:
– 70% of consumers are likely to recommend a brand after positive interactions (NPS).
– 69% of consumers are extremely likely to repurchase after good experiences (loyalty).
– The Trust Index correlates with NPS at 0.7, the strongest among loyalty behaviors.
The chain is clear: Brand Appreciation → Higher NPS → Greater Loyalty → Increased Sales.
It raises important questions for every retailer: Does your company collect NPS data? Do you have a loyalty program? And if so, are you using those insights to improve performance—or are they sitting unused?
Proof in numbers
Take PVH, the global fashion group behind brands like Tommy Hilfiger and Calvin Klein. What started as a StoreForce journey with 40 Dutch stores in 2014 has since scaled to 520 stores worldwide. Today, PVH runs 150 scheduled reports, has more than 1,800 users logging in every three months, and supports a workforce of 8,000 employees through its retail systems.
The PVH operations team uses structured data to shape scheduling, payroll, dashboards, and performance tracking across multiple countries. The result? A cohesive strategy that ties customer loyalty and store execution together. This proves that data, when centralized and analyzed, drives measurable performance gains.
It’s not just PVH. Other specialty retailers have demonstrated the same patterns:
– Asics leveraged loyalty data to reinforce repeat purchases.
– Laura and Dynamite improved customer retention by aligning data-driven decisions with in-store execution.
– Fabletics highlighted the risks of chasing vanity metrics—discount-driven loyalty signups that boosted membership counts but eroded long-term performance.
The difference is simple. When loyalty is treated as a transaction, performance suffers. When it’s treated as a fee earned through consistent brand appreciation, performance accelerates.
Stop hoarding data
Too many retailers still sit on valuable data without a plan to use it. Naipal’s challenge to the industry was blunt: stop hoarding. Collecting numbers without strategy is wasted effort.
The path forward can be broken into four steps:
1. Collect and analyze
Bring data from across the business into one view. Break down silos between POS, traffic, inventory, and customer systems. Look for trends instead of snapshots.
2. Strategize
Translate analysis into a plan. If NPS is lagging, what’s the store-level action? If loyalty is slipping, what changes are needed in customer engagement or store operations?
3. Teach and win
Data is useless if store teams aren’t empowered to act on it. Training frontline staff to understand metrics and their role in improving them creates alignment across the business.
4. Repeat
Continuous measurement keeps the strategy relevant. Retail is dynamic—data strategy should be too.
From insight to action
The core lesson from “Chaos to Clarity” is that success comes from execution, not collection. Specialty retailers don’t win by gathering the most numbers—they win by using the right ones.
Naipal used a simple scenario to illustrate this point: A district manager reviews a report showing 1,100 online transactions linked to the endless aisle. The immediate questions should be: When do these transactions spike—weekends, weekdays, or certain times of day? If your NPS is low, do you know why? If omnichannel sales are high, what’s driving the performance? Without those answers, the raw data isn’t actionable.
The takeaway for executives
For retail leaders, the priority is clear: build a data strategy that breaks down silos, puts NPS and loyalty at the center, and gives store teams the tools to act. Done well, this turns information into impact—and ensures the business isn’t just tracking numbers but turning them into real results.