Retail KPI 2025: essential indicators to monitor your sales, customers, and stores
In the retail sector, the strategic use of reliable KPIs is indispensable. These metrics, whether financial, logistical, omnichannel, or relational, offer a clear, quantitative perspective on real-world performance.
Data fueling KPIs must be centralized and analyzed in real time. Yet, POS, OMS, and CRM systems frequently operate in silos, obstructing consolidated insight. What, then, are the performance indicators for unified commerce in 2025, and how can you create a truly unified dashboard?
What is a retail KPI, and why is it strategic in 2025?
A KPI is a numeric measure that tracks the progress towards a business objective. In retail, valuable KPIs are actionable and aligned with clear goals such as profitability, commercial performance, operational efficiency, and customer experience quality. These indicators may be financial, operational, logistical, or relational.
Financial indicators reveal where a company is profitable and where it faces losses, helping anticipate which category, brand, or channel will yield profits in the future. A seamless retail network requires smooth operations. Logistical and operational KPIs offer an objective view of the value chain’s performance, assisting companies in preventing overstock and boosting in-store productivity.
Lastly, customer relationship KPIs assess how well a brand fosters long-term relationships.
Critical financial and commercial KPIs
Revenue and gross margin
Revenue stands as the crucial metric for gauging a company’s commercial success. In retail, this KPI should be monitored across channels (store, e-commerce, marketplace), product categories, and time periods to pinpoint sales trends.
Gross margin serves as a vital indicator of genuine profitability, showcasing whether sales growth is fostering sustainable value creation.
Key metrics to track:
– Overall revenue progress versus predefined sales targets.
– Gross margin across different categories and channels.
Areas to address:
– Revenue growth without margin improvement → reassess pricing strategy and discounts.
– Channel-specific margin discrepancies → streamline logistics and e-commerce and click-and-collect-related costs.
Average order value (AOV)
The average order value denotes the expenditure per customer per transaction, highlighting the potential to maximize each interaction. AOV should be monitored in both physical and digital realms and differentiated by customer segment (loyal, new, occasional), recognizing varied purchasing patterns.
Key metrics to track:
– Overall AOV per channel.
– AOV segmented by customer type.
Areas to address:
– Low AOV → implement upselling and bundling strategies, enhance in-store services.
– Significant channel disparity in AOV → refine the omnichannel journey.
Conversion rate in-store and online
Conversion rate represents the proportion of visitors (or prospects) who take action, such as making a purchase, subscribing to a newsletter, or enrolling in a loyalty program. This metric indicates the effectiveness of the customer journey and should be monitored by channel (store, e-commerce) and across the omnichannel landscape.
Key metrics to track:
– Overall and channel-specific conversion rates.
– Omnichannel conversion: Percentage of customers engaging across multiple channels before completing their transaction.
Areas to address:
– Low in-store conversion rate → improve visitor welcome, train sales staff, minimize checkout waiting through self-checkout systems.
– Low online conversion rate → smooth out the purchase process, expand payment options.
Shrinkage rate
The shrinkage rate measures the discrepancy between the theoretical inventory and the actual stock available. This critical metric signifies losses due to:
– Product damage;
– Internal or external theft;
– Administrative mistakes;
– Inventory discrepancies.
Key metrics to track:
– Overall shrinkage rate trends and by product category.
– High-risk periods (high traffic, sales promotions, holidays).
Areas to address:
– Increasing shrinkage rate → enhance point of sale security.
– Implement omnichannel traceability with unified commerce software for real-time anomaly detection.
Essential logistical and omnichannel KPIs
Stockout rate and product availability
The stockout rate indicates the percentage of items that are unavailable when customers intend to buy them, causing immediate sales loss and harming customer experience. Conversely, product availability measures a brand’s ability to ensure the presence of desired items at the right times.
Key metrics to track:
– Overall and category/channel-specific stockout rate.
– Product availability rate (OSA – On Shelf Availability).
Areas to address:
– Significant variability in availability between points of sale → centralize management and activate redistribution mechanisms like ship-from-store. Optimize availability with dynamic stock allocation.
– Frequent online stockouts → offer equivalent products or enable reservations on other channels (store, warehouse).
Stock accuracy
Stock accuracy gauges the disparity between the theoretical inventory recorded in company systems and the actual physical inventory available, ensuring data reliability.
Calculation formula: Stock accuracy = (Items where theoretical stock equals physical stock ÷ Audited items) × 100.
With the advent of RFID systems, brands can now attain accuracy rates near 95–98%, up from 60–70% with conventional inventories.
Key metrics to track:
– Overall stock accuracy rate and store-specific performance.
– Frequency of discrepancies identified during inventories.
Areas to address:
– Accuracy below 90% → enhance cycle count frequency.
– Persistent discrepancies despite checks → consider RFID deployment for automated point of sale and warehouse management.
On-Time In-Full (OTIF)
On-Time In-Full (OTIF) measures the percentage of orders delivered on schedule and in precise quantities, indicating logistical performance and service quality.
Calculation formula: OTIF = (Number of on-time and in-full orders / Total orders) × 100.
Key metrics to track:
– Overall OTIF by channel.
– Discrepancy types: delays versus partial deliveries.
Areas to address:
– Drop in “On-Time” rate → refine logistics planning, reassess supplier lead times, predict seasonal peaks.
– Low “In-Full” rate → diagnose issues like picking errors or stockouts.
Specific KPIs for click-and-collect
The click-and-collect rate quantifies the percentage of orders placed online and collected in-store.
Click-and-Collect rate = (C&C Orders ÷ Total Orders) × 100.
Pickup uplift assesses the extra value created during in-store collection, where customers add to their initial purchase with additional items.
Calculation formula: Pickup uplift = (Additional revenue generated during pickup / Initial C&C order revenue) × 100.
Key metrics to track:
– Overall C&C rate relative to total online orders.
– Average additional revenue generated during pickup (uplift).
Areas to address:
– Low C&C rate → enhance service visibility online, reduce preparation times, provide flexible pickup slots.
– Low uplift → train store teams for upselling, promote special offers at pickup points.
Ship-from-store lead time
Ship-from-store lead time evaluates the average interval between order approval by a customer and actual dispatch when prepared straight from a store, reflecting network responsiveness.
Calculation formula: Ship-from-store lead time = Shipment date − order date (average).
Key metrics to track:
– Overall average ship-from-store lead time.
– Comparison by store/region to pinpoint bottlenecks.
Areas to address:
– Excessively long lead time → reassess store organization.
– Significant discrepancies between stores → standardize practices and enhance team training.
Return and reconditioning rate
The return rate measures the ratio of returned products to total sales, influencing both profitability and customer satisfaction in retail.
Return rate = (Number of returned items / Total items sold) × 100.
The reconditioning rate assesses the percentage of returned items that can be resold or restocked following quality checks.
Reconditioning rate = (Returned items restocked / Total returned items) × 100.
A high reconditioning rate indicates effective reverse logistics management and minimizes losses.
Key metrics to track:
– Overall return rate and per product category.
– Percentage of restocked versus destroyed items.
Areas to address:
– High return rate → enhance product descriptions, streamline in-store fitting processes.
– Low reconditioning rate → bolster quality control and expand second-hand sales channels.
Top customer experience & loyalty KPIs
Net Promoter Score (NPS)
The Net Promoter Score measures how likely a customer is to recommend a brand to others, indicating potential satisfaction and loyalty.
Question asked to the customer: “On a scale of 0 to 10, how likely are you to recommend our company to a friend or colleague?”
Response segmentation:
– Promoters (9–10): loyal customers and potential brand advocates.
– Passives (7–8): satisfied but neutral, unlikely to recommend.
– Detractors (0–6): dissatisfied customers, risking harm to the brand’s reputation.
NPS = % Promoters – % Detractors.
Key metrics to track:
– Overall NPS trends and channel-specific performance.
– Correlation with loyalty metrics (CLV, repurchase rate).
Areas to address:
– High detractor rate → pinpoint issues and execute corrective measures.
– Predominance of passive customers → enhance brand differentiation.
Customer Satisfaction Score (CSAT)
Customer Satisfaction Score (CSAT) measures customer satisfaction with a specific product, service, or interaction, aiding in pinpointing essential improvement areas.
Calculation formula: CSAT = (Satisfied/very satisfied responses ÷ Total responses) × 100.
Note: CSAT measures immediate satisfaction but does not guarantee long-term loyalty. For a complete picture, combine CSAT with NPS and CLV.
Key metrics to track:
– Overall CSAT and by interaction type.
– Survey response rate to assess representativity.
Areas to address:
– Drops in CSAT after specific steps → reassess logistical processes and enhance customer communication.
– Low response rate → simplify surveys and time their delivery effectively.
Customer Effort Score (CES)
The Customer Effort Score (CES) quantifies the effort customers perceive when executing actions such as placing an order or contacting customer service. Lower effort signals a smoother experience.
Calculation formula: CES = Average score given by customers (1–7 scale).
Key metrics to track:
– Overall CES score and by interaction type.
– Compare CES with NPS and CSAT to uncover discrepancies.
Areas to address:
– High CES for specific steps → simplify the process.
– Significant gap between channels → harmonize the experience across physical and digital platforms.
Repurchase rate & purchase frequency
Repurchase rate designates the proportion of customers who make a second purchase after their original order.
Calculation formula: Repurchase rate = (Customers with ≥ 2 purchases / Total customers) × 100.
Purchase frequency gauges the average number of transactions per customer over a specified period (monthly, quarterly, annually).
Purchase frequency = Total transactions / Total customers
Key metrics to track:
– Overall repurchase rate and by customer segment.
– Average purchase frequency by channel.
Areas to address:
– Stagnant repurchase rate → reignite dormant customers with targeted campaigns.
– Low purchase frequency → increase touchpoints and improve personalization.
Customer Lifetime Value (CLV)
Customer Lifetime Value (CLV) calculates the total revenue generated by a customer over their entire relationship with the brand, guiding investment in customer acquisition and retention.
Calculation formula: CLV ≈ AOV × Frequency × Duration (or margin model × retention).
Key metrics to track:
– Average CLV by customer segment.
– CLV / CAC ratio to assess acquisition campaign profitability.
Areas to address:
– Low CLV → improve repurchase rate, average order value, and customer relationship duration.
– Channel-specific CLV variations → realign marketing budgets to favor the most profitable channels.
Churn rate and CAC payback
Churn rate tracks the proportion of customers lost during a specific period (e.g., customers who haven’t repurchased within the past 12 months).
Calculation formula: Churn rate = (Lost customers during the period / Active customers at the beginning of the period) × 100.
CAC payback measures the time needed to recoup the customer acquisition cost (CAC) via the margin generated by that customer (or cohort).
Calculation formula: CAC payback = CAC ÷ monthly gross margin generated by the cohort.
Example: If CAC is €100 and the monthly gross margin generated by a customer is €20, the payback period is 5 months.
Key metrics to track:
– Overall churn rate and by customer segment.
– Average CAC payback and by acquisition channel.
Areas to address:
– High churn rate → enhance loyalty initiatives.
– CAC payback exceeding 12 months → refine acquisition strategies.
Customer service KPIs
First Contact Resolution (FCR) measures the percentage of requests addressed successfully during the initial contact with the customer.
FCR = (Requests resolved at first contact / Total requests) × 100.
Average Handling Time (AHT) calculates the average time to resolve a request (conversation + post-processing).
AHT = (Total interaction time + post-processing) / Total requests.
The queue abandonment rate measures the percentage of customers who exit the queue before receiving a response.
Queue abandonment rate = (Customers who left the queue / Total customers in the queue) × 100.
Key metrics to track:
– Overall FCR and by channel.
– Queue abandonment rate by time slot and channel.
Areas to address:
– Low FCR → improve training, enrich the knowledge base, deploy AI to assist responses.
– High AHT → streamline processes and automate repetitive tasks.
Setting up a unified retail dashboard
The importance of centralized data
A unified dashboard enables performance analysis with centralized data from various systems (POS, OMS, CRM). Unified retail data offers decision-makers a comprehensive view of the customer journey and performance, ensuring:
– Responsiveness: through real-time analysis;
– Continuous optimization of offers and journeys;
– Personalization of in-store experience: by connecting CRM, OMS, and POS, the brand can enhance interaction relevance.
Essential tools
Integrated dashboards within POS, OMS, and CRM systems enable monitoring and analyzing operational indicators. They provide immediate and contextualized insights for real-time network performance management.
Business Intelligence (BI) enhances analytical capabilities, consolidating multi-source data and allowing market trend analysis.
Additionally, real-time reporting ensures maximum responsiveness with continuously updated data.
Building your retail KPI dashboard in 10 steps
- Define objectives (growth, profitability, loyalty, performance).
- Select essential KPIs (8–12 indicators per objective).
- Identify data sources: mobile POS (mPOS) and store systems (POS), omnichannel orders (OMS), customers (CRM), e-commerce (online).
- Centralize data flows.
- Ensure data reliability.
- Choose appropriate analysis tools.
- Define responsibilities: assign each indicator to a responsible person.
- Build role-specific views: executive (strategic vision), manager (operational management), sales associate (field objectives).
- Set up alerts and thresholds.
- Continuously adjust based on feedback.
Benchmarks and best practices for 2025
Decathlon uses retail KPIs to enhance operational performance and in-store customer experience. By integrating technologies like RFID for inventory tracking, the brand significantly improved efficiency.
At Intersport, real-time data has become a cornerstone for performance management and customer experience optimization. Utilizing Orisha Commerce’s unified commerce platform, the teams benefit from a comprehensive and central view of the entire network. The software manages points of sale and enables revenue analysis by brand and collection over previous years.
Meanwhile, the SMCP group (Sandro, Maje, Claudie Pierlot) has adopted unified commerce as a strategic lever to enhance its high-end shopping experience and support international growth.
Finally, Leroy Merlin has leveraged Ship-from-Store as a strategic tool to accelerate delivery times and streamline its omnichannel organization. Relying on Orisha Commerce’s platform, the brand centralizes inventories and orchestrates shipments directly from its stores.
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Observed benchmarks in 2025:
– Average stockout rate: 6–8% in specialized distribution.
– CSAT: Brands with a good CSAT score range between 75–85%.
– OTIF: Benchmarking around 85–90% (source McKinsey).
Key best practices:
– Combine financial and relational indicators to manage profitability and loyalty.
– Implement a data governance strategy.
– Use BI and real-time reporting to adjust strategies.
– Communicate results to build consumer trust.
FAQ– Retail KPI and Customer Experience
Which KPIs should be tracked to measure customer experience in retail?
In 2025, the key retail customer experience KPIs are revenue by channel, Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), Customer Effort Score (CES), repurchase rate, and Customer Lifetime Value (CLV). These indicators evaluate satisfaction, loyalty, and profitability both in-store and online.
What is the difference between NPS, CSAT, and CES?
NPS measures the likelihood of recommendation (promoters – detractors). CSAT assesses immediate satisfaction after a transaction. CES gauges the effort exerted by the customer to obtain a service. Used together, these three KPIs provide a comprehensive view of the customer experience quality.
What omnichannel KPIs should be tracked for click-and-collect and ship-from-store?
Key omnichannel sales KPIs in 2025 include click-and-collect order rate, uplift at store pickup, average preparation time (ship-from-store lead time), return rate, and inventory accuracy (stock accuracy). They help optimize logistical efficiency and customer satisfaction.
How to link customer experience KPIs to profitability?
The link is made through Customer Lifetime Value (CLV), repurchase rate, and CAC payback. For example, improving NPS and CSAT increases retention, thus CLV. Conversely, a high CES can result in customer loss and reduce overall profitability.
What tools are used to ensure and track retail KPIs?
In 2025, ensuring retail indicator reliability involves data centralization in unified systems (POS, OMS, CRM). Omnichannel dashboards and Business Intelligence solutions facilitate real-time analysis and visualization of financial, logistical, and customer indicators, enabling faster action.
In 2025, steering by KPIs is essential to balance economic performance with omnichannel customer loyalty. The goal isn’t to multiply indicators but to create a unified dashboard based on centralized and reliable data (POS, OMS, CRM).
The brands that gain an edge are those that can turn their KPIs into measurable actions: reducing stockouts, optimizing margins, and improving customer satisfaction in real-time.
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