Shopify Metric
Marketing
RFM Score = Recency Score (1-5) and Frequency Score (1-5) and Monetary Score (1-5), assigned by quintile rank across all customers
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.
Full guide: definition, formula, and benchmarksShopifyMarketingRFM Segmentation
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.
How to calculate rfm segmentation
Why rfm segmentation matters for Shopify users
Most Shopify stores treat their customer list as one undifferentiated audience, then wonder why broad email campaigns convert poorly. RFM Segmentation tells you which customers are worth a retention offer, which are drifting away and which have already lapsed, so spend goes where it actually moves revenue.
Because the segments update as new orders land, you can act on them. A champion segment justifies early access and loyalty perks, an at-risk segment justifies a win-back flow, and a one-time-buyer segment justifies a second-purchase nudge. This turns raw Shopify order data into a practical playbook for marketing and retention.
Understand and act on rfm segmentation with KPI Tree
Sync your Shopify customer and order data into your warehouse and compute RFM scores in KPI Tree, ranking customers into quintiles on recency, frequency and monetary value. Place the segmentation in a metric tree alongside average order value and your conversion metrics so you can see how each segment feeds repeat revenue.
Assign RACI ownership to your retention or lifecycle marketing lead in KPI Tree, with finance or analytics consulted on the scoring thresholds. Set a monthly review cadence to watch segment sizes shift, so a growing at-risk segment triggers a win-back campaign before those customers are lost for good.
Get started with your Shopify data
MCPPull metrics from Shopify directly through the Model Context Protocol.
Connect your existing warehouse where Shopify data already lands.
Our professional services team can build you turn-key AI foundations in a matter of weeks. Data warehouse on Snowflake/BigQuery, ELT with Fivetran, all modelled in dbt with a semantic layer.
Related Shopify metrics
Average Order Value
E-commerceMetric Definition
AOV = Total Revenue / Number of Orders
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 Conversion Rate
E-commerceMetric Definition
Cart Conversion Rate = (Completed Orders / Sessions with Add-to-Cart) × 100
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 Conversion Rate
E-commerceMetric Definition
Checkout Conversion Rate = (Completed Orders / Checkout Starts) × 100
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.
Abandoned Cart Recovery Rate
E-commerceMetric Definition
Abandoned Cart Recovery Rate = (Recovered Carts / Total Abandoned Carts) × 100
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.
Explore rfm segmentation across integrations
All Shopify metrics
Average Order ValueCart Abandonment RateCheckout Conversion RateCustomer Acquisition CostCustomer Lifetime ValueCustomer Repeat RateDiscount Usage AnalysisFulfilment SpeedGross Merchandise VolumeInventory TurnoverMarketing Channel AttributionNew vs Returning CustomersOrder FrequencyOrders Per CustomerProduct Performance AnalysisProduct Return RateProfit Margin by ProductRevenue by ChannelRevenue by GeographyRevenue Per VisitorSessions to Purchase RatioShipping Cost AnalysisStore Conversion RateTop Selling Products AnalysisTraffic Source PerformanceAbandoned Cart Recovery RateAverage Product RatingCart Conversion RateCheckout Abandonment RateCollection Performance AnalysisCustomer Cohort AnalysisCustomer Segmentation AnalysisPayment Method DistributionRevenue Growth RateSeasonal Trend AnalysisCohort AnalysisConversion RateCross Sell AnalysisCustomer Churn RateDiscount EffectivenessDraft Order Conversion RateFulfillment Time AnalysisGift Card Utilization RateInventory Turnover RateLocation Based Sales AnalysisPurchase Funnel AnalysisRefund RateRepeat Purchase RateRevenue Per CustomerStock Out FrequencyTransaction Success RateVariant Performance AnalysisEmpower your team to understand and act on Shopify data
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