Create Customer Group - Smart RFIM Grouping

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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:

 

1. Customer Group - Smart RFIM introduction 

There are 9 Smart RFIM customer grouping filter conditions:

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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.

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2. "High/ Mid/ Low" options for Purchase Behavior filter condition

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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

 

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