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Listing summary

  • Identify your top revenue-driving clients Retail
  • Free

Analytics status

  • Available

Business benefit

This analysis is designed to help you substantially increase :
▪ total turnover
▪ AOV (Average Order Value)
▪ items per basket
▪ client acquisition and retention

Data inputs (mandatory)

We'll be using historical sales data containing the following information :
▪ InvoiceNo : ID of the actual purchase
▪ StockCode : SKU number (or SKU ID)
▪ Description : written description of the item/SKU
▪ Quantity : number of the same SKU being sold to the same client (if applicable, otherwise it will be "1")
▪ InvoiceDate : actual purchase date
▪ UnitPrice ; SKU/Item unit price
▪ CustomerID : ID number of the client
▪ Country : Country where the purchase has been made

Data Output

▪ Output is the list of all your customers along with their status (High/Medium/Low value)

Technical description

This model uses the RFM methodology (Recency, Frequency and Money). It does correlate recency (last time your purchased from observation date), frequency (number of purchases over the last 12 months) and Money (average basket value) to identify the high-value customers.

Limitations

Clients must have purchased at least once in the last 12 months from observation date.

Description

Tired of sending campaigns, mails and calls to the same customers with no results? Identify your high potential clients by using this analysis and focus on your most revenue driving customers.

Quick and simple tool to be used to identify the necessary clienteling actions to work on for the most revenue-driving customers but also for the inactive clients/least revenue driving to retain them.