Description
This template offers the following list of models, each with its own unique perspective, to help you make informed decisions based on Shopify dataset.
Model |
Description |
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Each record represents an order in Shopify.
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Each record represents a customer in Shopify.
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rpt__shopify__customer_cohorts
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Each record represents a customer’s performance in a calendar month.
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rpt__shopify__customer_rfm_scd
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Each record represents a customer in Shopify.
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fct__shopify__fulfillment
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Each record represents a fulfilment joined with orders. |
rpt__shopify__fulfillment_order
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Each record represents a fulfilment joined with orders along with leap time. |
fct__shopify__product_basket
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Each record represents an order in Shopify, with list of purchased products with products attributes.
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Each record represents a product in Shopify.
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fct__shopify__transactions
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Each record represents a transaction_id.
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fct__shopify__demand_forecasting
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Each record represents a actual and forecasted demand of each SKU.
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rpt__shopify__demand_forecasting_evaluation
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Each record represents a monthly r-square.
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rpt__shopify__inventory_alert
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This report table contains info about daily inventory level, quantity sold and reorder quantity of each SKU.
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fct__shopify__order_lines
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Each record represents a line item of an order in Shopify.
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Lead Analytics Engineer at Joon Solutions Global
Data Analyst | Business Intelligence | BI Consultant
Latest posts by Na Nguyen Thi
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Usage
This template offers a range of dimensions and metrics that allow you to monitor and analyze:
1. Customer Segmentation through RFM model
RFM model shows the you the number of customers and their detailed information in each RFM in the current month. Based on this report you can easily plan a Marketing strategy customized to each customer group:
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Champions (R=4,5 | MF=4,5) are your best customers, who bought most recently, most often, and are heavy spenders. Reward these customers. They can become early adopters for new products and will help promote your brand.
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Loyal customers (R=3 | MF=4,5) are those who made a purchase recently. They are regular patrons and also likely to spend more than other customer segments. They are your second best friend, just after the champions. Maintain and enhance the relationship with this segment through loyalty programs, personalized communication and excellent customer service.
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Promising (R=4,5 | MF=2,3) are your recent customers with average frequency and who spent a good amount. Offer membership or loyalty programs or recommend related products to upsell them and help them become your Loyalists or Champions.
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New Customers (R=4,5 | MF=1) are your customers who recently bought your products but are still very careful with their purchase. Start building relationships with these customers by providing onboarding support and special offers to increase their visits.
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Hibernating (R=1,2 | MF=3,4) are your customers who purchased often and spent big amounts, but haven’t purchased recently. Send them personalized reactivation campaigns to reconnect, and offer renewals and helpful products to encourage another purchase.
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Can’t Lose Them (R=1,2 | MF=5) are customers who used to visit and purchase quite often, but haven’t been visiting recently. Bring them back with relevant promotions, and run surveys to find out what went wrong and avoid losing them to a competitor.
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Needs attention (R=3 | MF=3) are those used to shop frequently with a significant amount on their purchases but their engagement has recently dropped off. They were once valuable but be at risk of churning. Re-engage them by reminders, outreach programs and personalized offers to keep them with us.
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About to sleep (R=3 | MF=1,2) are those on the verge of becoming inactive and have a history of low to moderate monetary value. This segment is a good target for reactivation campaigns, but of lower priority compared to other potentially churned segments.
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Lost (R=1,2 | MF=1,2) are customers who haven’t bought your products for quite a time and didn’t usually spend much money either. Consider them as lost customers and do not waste resources in bringing them back because the revenue generated from these customers may not worth the try.
2. Demand Forecasting & Inventory Alert
Please find detailed blog: HERE
3. Others:
- Transaction Management: payment method, refund, fraud detection
- Fulfilment Management: late delivery, route analysis
Lead Analytics Engineer at Joon Solutions Global
Data Analyst | Business Intelligence | BI Consultant
Latest posts by Na Nguyen Thi
(see all)