Ecommerce & Marketplace Metrics

Listing conversion rate measures the percentage of product listing views that result in a completed purchase. It is the core marketplace efficiency metric that reveals how effectively individual listings turn browsing interest into buying action.

New buyer growth rate measures the rate at which a marketplace acquires new buyers over a given period. It is the demand-side growth engine that determines whether the marketplace can sustain increasing transaction volume and attract more sellers.

New seller growth rate measures the rate at which a marketplace onboards new sellers over a given period. It is the supply-side growth engine that determines catalogue breadth, product selection, and the marketplace's ability to satisfy buyer demand.

Percentage of active listings measures the proportion of all listings on a marketplace that are currently live, in stock, and available for purchase. It is a catalogue health metric that directly affects buyer experience, search quality, and marketplace credibility.

Percentage of active sellers measures the proportion of registered sellers on a marketplace who currently have at least one live listing. It is the supply-side engagement metric that reveals whether the marketplace is retaining its sellers as active participants or accumulating dormant accounts.

Percentage of engaged buyers measures the proportion of registered buyers who regularly interact with the marketplace through actions such as searching, browsing, adding to wishlists, or purchasing. It reveals the depth of demand-side engagement beyond simple registration counts.

Percentage of satisfied transactions measures the proportion of completed marketplace transactions that receive a positive rating or no complaint from the buyer. It is the trust metric that determines whether buyers will return and whether sellers maintain their reputation.

Purchase frequency measures how often customers make a purchase within a given time period. It is a core loyalty metric that directly determines customer lifetime value and reveals how deeply a product or marketplace has been integrated into a customer's buying habits.

Repeat customer rate measures the percentage of customers who return to make more than one purchase. It is the clearest signal of whether a business is building genuine customer loyalty or relying entirely on one-time transactions to generate revenue.

Revenue by traffic source measures the total revenue attributed to each acquisition channel, such as organic search, paid advertising, email, direct, social media, and referrals. It answers the most fundamental marketing question: which channels are actually generating revenue, not just traffic?

Time to purchase measures the average duration between a customer's first interaction with a platform and their completed purchase. It quantifies the length of the buying decision cycle and reveals how much friction, hesitation, or consideration exists between initial interest and transaction.

Checkout conversion rate measures the percentage of users who begin the checkout process and successfully complete their purchase. It isolates the final stage of the buying funnel, from the moment a shopper initiates checkout to the order confirmation page. This metric is critical for e-commerce businesses because the checkout is where purchase intent is highest, and any friction at this stage directly destroys revenue that was nearly captured.

Product return rate measures the percentage of purchased products that are returned by customers after delivery. It is a critical e-commerce and retail metric because returns directly erode gross margin through reverse logistics costs, restocking expenses, and lost inventory value. For many online retailers, the return rate is the single largest threat to profitability, particularly in categories like fashion where return rates routinely exceed 30%.

Revenue per visitor (RPV) measures the total revenue generated divided by the number of unique visitors to a website or app over a given period. It combines the effects of conversion rate and average order value into a single number that represents how effectively the business monetises its traffic. RPV is one of the most useful e-commerce metrics because it captures both "how many visitors buy" and "how much they spend" in a single, comparable figure.

Customer repeat rate measures the percentage of customers who return to make more than one purchase within a defined period. It is the simplest and most direct indicator of whether your product, pricing, and post-purchase experience are strong enough to earn a second transaction.

Order frequency measures the average number of orders a customer places within a defined time period. It captures how deeply your store has been woven into a customer's purchasing habits and is one of the three core levers of customer lifetime value alongside average order value and customer lifespan.

Fulfilment speed measures the average elapsed time from when a customer places an order to when they receive it. It is one of the most visible indicators of operational excellence and directly influences customer satisfaction, repeat purchasing, and competitive positioning.

Shipping cost analysis measures shipping expenditure as a percentage of order value. It quantifies how much of each sale is consumed by the cost of getting the product to the customer and is a critical input to e-commerce profitability, pricing strategy, and free-shipping threshold decisions.

Discount usage analysis measures the percentage of orders that include a discount code or promotional offer. It reveals how dependent your revenue is on price reductions and whether your promotional strategy is driving incremental sales or simply subsidising purchases that would have happened at full price.

Marketing channel attribution assigns revenue credit to the marketing channels that influenced each purchase. It determines which channels drive profitable customers and guides budget allocation across paid, organic, social, email, and referral sources.

New vs returning customers measures the proportion of orders and revenue coming from first-time buyers versus repeat purchasers. It reveals whether growth is driven by acquisition, loyalty, or a sustainable balance of both.

Orders per customer measures the cumulative average number of orders placed per customer across their entire relationship with your store. It captures how deeply customers engage with your brand over time and is a core component of customer lifetime value.

Product performance analysis evaluates each product across revenue, units sold, margin, return rate, and conversion rate. It identifies which products drive value and which underperform, enabling data-driven merchandising, pricing, and inventory decisions.

Profit margin by product measures the percentage of revenue retained as profit after deducting cost of goods sold for each product. It reveals which products generate healthy margins and which are margin-dilutive, guiding pricing, promotion, and catalogue decisions.

Revenue by channel segments total sales by the distribution channel through which they occur, including online store, point of sale, social commerce, marketplaces, and wholesale. It reveals channel contribution, concentration risk, and diversification opportunities.

Revenue by geography breaks down sales by customer location, including country, region, or city. It reveals market penetration, identifies expansion opportunities, and highlights geographic concentration risk.

Sessions to purchase ratio measures how many site sessions are needed, on average, before a visitor makes a purchase. It captures the consideration cycle length and browsing behaviour of your customers, revealing how much nurturing is required to convert interest into revenue.

Store conversion rate is the percentage of unique visitors who complete at least one purchase. It is the broadest measure of how effectively your store converts browsing traffic into paying customers and one of the highest-leverage metrics for e-commerce growth.

Top selling products analysis ranks products by revenue, units sold, or order count to identify the items that drive the most business value. It highlights heroes, rising stars, and declining performers so merchandising teams can act before trends shift.

Traffic source performance evaluates each traffic source on volume, conversion rate, revenue contribution, and customer quality. It compares organic, paid, social, email, direct, and referral channels holistically to reveal which sources deliver valuable visitors.

Abandoned cart recovery rate is the percentage of abandoned carts that are subsequently converted into completed orders through recovery efforts such as email sequences, SMS reminders, or retargeting campaigns. It quantifies how effectively your win-back automation recaptures lost revenue.

Average product rating is the mean star rating across all customer reviews for a given product or your entire catalogue. It serves as a proxy for customer satisfaction, product quality perception, and directly influences conversion rate and search ranking.

Cart conversion rate is the percentage of visitors who add items to their cart and subsequently complete a purchase. It isolates the effectiveness of the post-browse, pre-checkout stage of the buying journey and reveals how much high-intent traffic is lost before checkout.

Checkout abandonment rate is the percentage of visitors who initiate the checkout process but leave before completing payment. It focuses exclusively on drop-off after the buyer has committed to purchasing, representing the highest-intent lost revenue in the funnel.

Collection performance analysis evaluates each product collection on revenue contribution, conversion rate, average order value, and traffic volume. It reveals which product groupings resonate with customers and which underperform, guiding site structure and merchandising decisions.

Customer cohort analysis groups customers by their acquisition period and tracks their purchasing behaviour over subsequent time intervals. It reveals how retention, order frequency, and revenue evolve for each cohort as they mature, exposing trends that aggregate metrics hide.

Seasonal trend analysis examines recurring patterns in sales, traffic, and customer behaviour across different time periods. It identifies predictable demand cycles that inform inventory planning, marketing timing, staffing, and budget allocation.