Turn Shopify order data into a causal model of what drives your e-commerce revenue, and who owns each lever.

Average order value (AOV) is the mean monetary value of each completed order. It captures the combined effect of pricing, bundling, upselling, and promotional strategies on basket size.

Cart abandonment rate is the percentage of shopping carts created that are not converted into completed orders. It measures friction and hesitation between add-to-cart and purchase completion.

Checkout conversion rate is the percentage of visitors who begin the checkout process and successfully complete a purchase. It isolates conversion performance at the critical final stage of the buying journey.

Customer acquisition cost (CAC) measures the total marketing and sales spend required to acquire a new customer. It encompasses ad spend, creative costs, agency fees, and any other direct acquisition expenses.

Customer lifetime value (LTV) estimates the total revenue a customer will generate over their entire relationship with your store. It combines average order value, purchase frequency, and customer lifespan into a single value figure.

Customer repeat rate is the percentage of customers who make more than one purchase within a defined period. It measures customer loyalty and the effectiveness of retention and re-engagement efforts.

Discount usage analysis measures the frequency, value, and impact of discount codes and automatic discounts applied to orders. It quantifies how promotions affect revenue, margins, and customer behaviour.

Fulfilment speed measures the average time between order placement and shipment. It captures warehouse efficiency, inventory availability, and operational capacity to meet customer delivery expectations.

Gross merchandise volume (GMV) is the total value of all merchandise sold through your Shopify store before deducting returns, discounts, and fees. It represents the top-line scale of your e-commerce operation.

Inventory turnover rate measures how many times inventory is sold and replaced within a period. Higher turnover indicates efficient inventory management and strong demand, while low turnover suggests overstocking or weak sales.

Marketing channel attribution assigns revenue credit to the marketing channels that influenced each purchase. It helps determine which channels, such as paid search, social, email, or organic, deliver the best return on investment.

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 or loyalty.

Order frequency measures the average number of orders placed by a customer within a defined period. It indicates purchasing cadence and is a key component of customer lifetime value calculations.

Orders per customer measures the cumulative average number of orders placed per customer across their entire relationship. Unlike order frequency which measures a period, this tracks lifetime purchase depth.

Product performance analysis evaluates each product on revenue, units sold, margin, return rate, and conversion rate. It identifies which products drive value and which underperform across multiple dimensions.

Product return rate is the percentage of sold units that are returned by customers. It reflects product quality, description accuracy, and how well customer expectations are met.

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.

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

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

Revenue per visitor (RPV) divides total revenue by the number of unique site visitors. It combines conversion rate and average order value into a single efficiency metric that reflects overall store performance.

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.

Shipping cost analysis measures total shipping expenditure and cost per order across carriers, destinations, and service levels. It reveals the true logistics cost of fulfilling customer orders.

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.

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.

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.

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 the effectiveness of your win-back automation.

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 and product quality perception.

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.

Checkout abandonment rate is the percentage of visitors who initiate the checkout process but leave before completing payment. Unlike cart abandonment, it focuses exclusively on drop-off after the buyer has committed to purchasing.

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

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.

Customer segmentation analysis divides your customer base into distinct groups based on purchasing behaviour, order value, frequency, recency, and product preferences. It enables targeted strategies for each segment rather than a one-size-fits-all approach.

Payment method distribution measures the share of transactions completed via each payment method, including credit cards, digital wallets, buy-now-pay-later, and alternative payment options. It reveals customer payment preferences and potential friction points.

Revenue growth rate measures the percentage change in revenue between comparable periods, typically month-over-month or year-over-year. It captures the overall trajectory of your business and whether growth is accelerating or decelerating.

Seasonal trend analysis examines recurring patterns in sales, traffic, and customer behaviour across different time periods such as weekly, monthly, and annually. It identifies predictable demand cycles that inform planning decisions.

Cohort Analysis groups your Shopify customers by the period of their first order, then tracks how each group behaves in the months that follow. Using Shopify order and customer data, it measures repeat purchase rates, retained customers and cumulative revenue for every cohort. This turns a single revenue figure into a view of how customer value develops after the first purchase.

Conversion Rate measures the percentage of Shopify store sessions that end in a completed order. It uses session counts from Shopify analytics alongside order records, so it reflects how effectively your storefront, product pages and checkout turn traffic into paying customers. Unlike a raw order count, it normalises for traffic volume, which makes performance comparable across days, channels and campaigns.

Cross Sell Analysis examines Shopify order line items to find which products are bought together in the same checkout. By reading each order is set of line items, it surfaces the pairs and groups of products that frequently co-occur, so the team can build bundles, recommendation blocks and post-purchase offers from real basket data. It turns raw Shopify order history into a ranked view of which products pull each other into the cart.

Customer Churn Rate measures the share of Shopify customers who were active in one period but did not place another order in the following period. Using the customer and order data in your Shopify store, it tells you how many buyers have lapsed rather than returning to purchase again. It is the inverse of customer retention and a direct read on how well your store holds onto its existing base.

Discount Effectiveness measures how much net revenue your Shopify discount codes and automatic discounts generate relative to the discount value given away. Shopify records the applied discount amount, the code used, and the resulting order total on every checkout, so you can compare what a promotion brought in against what it cost in reduced margin. A high score means a discount drove orders that would not otherwise have closed, rather than simply cutting the price on sales you would have won anyway.

Draft Order Conversion Rate measures the proportion of Shopify draft orders that are completed and paid within a defined period. In Shopify, draft orders are manually created carts for wholesale buyers, phone orders, or custom quotes, and each one carries a status that moves from open to completed once payment is captured or an invoice is settled. The metric tells you what share of these manually built orders actually turn into revenue.

Fulfilment Time Analysis measures the elapsed time between when a Shopify order is placed and when it is marked as fulfilled, using the order created_at and fulfillment created_at timestamps. It can be broken down by location, fulfilment service, product, or shipping method so you can see where delays build up. The metric is usually expressed as an average or a percentile, since a small number of very slow orders can hide behind a healthy mean.

Gift Card Utilisation Rate measures the proportion of total gift card value issued in your Shopify store that has been redeemed at checkout. It uses the gift card balance and redemption data Shopify records for every card sold or issued, comparing the value spent against the value originally loaded. A high rate means gift cards are converting into orders, while a low rate signals balances sitting idle in customer wallets.

Inventory Turnover Rate measures how many times your Shopify stock is sold and replaced over a defined period, calculated from Shopify order line items and inventory level snapshots. It reveals how efficiently capital tied up in stock converts into sales, product by product or across the whole catalogue. A high rate signals brisk sell-through, while a low rate points to overstocked or slow-moving SKUs.

Location Based Sales Analysis breaks down Shopify order revenue by geography, using the shipping or billing address on each order to group sales by country, region, state, or city. It reveals which locations drive the most revenue, how order value differs across markets, and where demand is concentrated or thin. In Shopify, this draws on order, line item, and address data rather than a single store-level total.

Purchase Funnel Analysis maps the proportion of Shopify shoppers who progress through each stage of the buying journey, from store session to product view, add to cart, checkout started and completed order. It uses Shopify session, cart and order data to expose the conversion rate at every step rather than only the final order rate. The analysis turns a single headline conversion number into a stage by stage view of where shoppers stall.

Refund Rate measures the proportion of your Shopify sales that gets returned to customers as refunds within a given period. It draws on the refund records attached to Shopify orders, so it captures both full order refunds and partial line-item adjustments. Tracked as a percentage of gross sales, it shows how much of your revenue does not stick.

Repeat Purchase Rate measures the proportion of your Shopify customers who have placed more than one order over a defined period. It is derived from the customer and order records in your Shopify store, counting each customer once and checking whether their lifetime order count is greater than one. A higher rate signals that your store retains buyers rather than relying entirely on first-time purchases.

Revenue Per Customer measures the average total revenue your Shopify store generates from each unique customer over a chosen period. It is built from Shopify order data grouped by customer record, summing the value of every order a shopper has placed and dividing by the number of distinct customers. Unlike average order value, which looks at single transactions, this metric captures the full spend of each customer across repeat purchases.

RFM Segmentation groups your Shopify customers using three behaviours drawn from order history: recency (how recently they last purchased), frequency (how many orders they have placed) and monetary value (how much they have spent in total). Each customer is scored on each dimension and placed into a segment such as champions, loyal customers, at-risk or lost. In Shopify, these scores come straight from the customer and order objects, so the segmentation reflects real transaction data rather than survey responses or guesses.

Stock Out Frequency measures how often products in your Shopify catalogue reach zero available inventory across a defined period. Using Shopify inventory level and variant data, it counts the number of distinct stock out events, where a sellable variant drops to zero available units, against the size of your active catalogue. It tells you how frequently customers land on an out of stock product rather than a buyable one.

Transaction Success Rate measures the proportion of payment attempts in Shopify that complete successfully, against every attempt that was initiated at checkout. In Shopify terms, it compares successful transactions recorded against orders with the failed, voided, or error transactions captured by Shopify Payments and any third party gateway. It isolates payment reliability from earlier funnel drop off, so a fall here points to gateway or processing problems rather than browsing behaviour.

Variant Performance Analysis measures how each Shopify product variant, defined by options such as size, colour, or material, contributes to sales relative to its siblings and to the catalogue as a whole. In Shopify, every variant carries its own SKU, price, inventory level, and order line items, so the data lets you rank variants by revenue, units sold, and sell-through rather than judging a product only at the parent level. It surfaces which specific options carry a product and which sit dormant tying up stock.