SHOPLINE's "Customer Group" feature allows you to use various filters to segment your audience accurately. You can also export relevant reports on specific customer groups to formulate the best marketing strategies and promotional activities for them.
In this article, you will learn the Smart RFIM filter conditions for the customer groups:
- Customer group - Smart RFIM introduction
- "High/ Mid/ Low" options for Purchase Behavior filter condition
1. Customer Group - Smart RFIM introduction
There are 9 Smart RFIM customer grouping filter conditions:
1. Customer segment filters
Smart RFIM divides customers into 9 distinct segment types, with no overlap between segments. The table below provides definitions for each segment type.
| Name | Repurchase Cycle | Number of Purchases |
Total Spend |
| Core Top Shopper |
Recently purchased OR Ready-to-repurchase |
Top Shoppers | Total spend > Top 10% |
| Inactive Top Shopper | Ready-to-repurchase with/without interaction | Top Shoppers | Total spend > Top 10% |
| Active Shopper | Recently purchased | Repeated Shoppers | Total spend ≤ Top 10% |
| Ready-to-Repurchase Shopper |
Ready-to-repurchase OR Lapsed with interaction |
Repeated Shoppers | Total spend ≤ Top 10% |
| Sleeping Shopper | Lapsed without interaction | Repeated Shoppers | Total spend ≤ Top 10% |
| New Shopper | Recently purchased | One-time Shoppers | Total spend ≤ Top 10% |
| Potential Shopper |
Ready-to-repurchase OR Lapsed with interaction |
One-time Shoppers | Total spend ≤ Top 10% |
| Lost Shopper | Lapsed without interaction | One-time Shoppers | Total spend ≤ Top 10% |
| Engaged Customer | Interacted within 3 times of the store's repurchase cycle | Browsers | No Purchases |
*Remarks:
- "Repurchase Cycle" is based on the purchase records of all repeat shoppers in the store over the past 2 years, the system calculates the median number of days between purchases to determine the store's repurchase cycle. This also serves as the benchmark for predicting customer repurchase behavior. For more information, please refer to: The X-axis of the heatmap.
- "Number of purchases" is categorized based on the number of purchases and the total spend. For more information, please refer to: The Y-axis of the heatmap.
- With the feature update, the "Loyal Customers" segment list will no longer be updated. Instead, you can set your own filters using "Number of Order > N" and "Money Spent = High".
2. Smart RFIM segment chart
The Smart RFIM segment chart is presented as a heatmap, showing the proportion and changes of each segment to help you track customer performance. For more information, please refer to: Customer: Segment Analysis | Shoplytics.
2. "High/ Mid/ Low" options for Purchase Behavior filter condition
| Name | Definition | Update frequency |
|
"High/ Mid/ Low" smart options for Money Spent |
Divide the spent amount of store customers into quartiles
|
Daily |
| "High/ Mid/ Low" smart options for AOV |
Divide the AOV amount of store customers into quartiles
|
Daily |
Read more
- Create Customer Group
- Customer Group Management
- Create Customer Group - General Filter
- Customer Group Analytics
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