Create Customer Group - Smart RFIM Grouping

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 High: Cumulative spent amount is higher than the first quartile (top 25%) Mid: Cumulative spent amount is between the third and first quartile Low: Cumulative spent amount is lower than the third quartile (lower 25%)	Daily
"High/ Mid/ Low" smart options for AOV	Divide the AOV amount of store customers into quartiles High: AOV is higher than the first quartile (top 25%) Mid: AOV is between the third and first quartile Low: AOV is lower than the third quartile (lower 25%)	Daily

 

Read more

• Create Customer Group
• Customer Group Management
• Create Customer Group - General Filter

• Customer Group Analytics