Clients
The Clients model contains comprehensive customer data and purchasing behaviour for RFM (Recency, Frequency, Monetary) analysis and customer segmentation. Data Octopus retrieves all data from the beginning of the shop’s existence.
Requirements
E-commerce engine: IdoSell.
Integrations with additional e-commerce engines will appear in Q2 and Q3 2025. This statement comes from the documentation dated 23 July 2025.
Data anonymised in Data Octopus
| Field name | Description |
|---|---|
| Hashed Client Email | Anonymised email address |
| Hashed Client Phone | Anonymised phone number |
| Hashed Client First Name | Anonymised first name |
| Hashed Client Last Name | Anonymised last name |
Address data
| Field name | Description |
|---|---|
| Client Delivery Address Zip Code | Postal code |
| Client Delivery Address Country Code | Country code |
Order metrics
| Field name | Description |
|---|---|
| Days Since First Order | Number of days since the first order |
| Days Since Last Order | Number of days since the last order |
| Order Count | Number of unique orders |
| Unique Item Count | Number of unique purchased products |
Financial metrics
| Field name | Description |
|---|---|
| Min Product Net Price | Net price of the cheapest product purchased |
| Max Product Net Price | Net price of the most expensive product purchased |
| Total Net Revenue | Total net value of all purchases |
| Has Invoice | Flag indicating whether an invoice was issued (true/false) |
RFM metrics and segmentation
| Field name | Description |
|---|---|
| Recency Score | Segment indicating the time since the last purchase |
| Frequency Score | Purchase frequency rating on the RFM scale |
| Monetary Score | Purchase value segment |
| Customer Segment | Customer segment determined by Data Octopus through RFM analysis |
Purchase preference metrics
| Field name | Description |
|---|---|
| Quantity Of Purchased Brands | Number of unique brands purchased |
| Purchased Brands | List of all purchased brand names |
| Quantity Of Purchased Categories | Number of unique categories purchased |
| Purchased Categories | List of all purchased categories |
RFM – customer segments
The Clients model uses RFM analysis to categorise customers automatically according to their value and purchasing behaviour.
Use cases
The data in the Clients model is primarily used to:
- Perform RFM analysis and customer segmentation based on recency, frequency and monetary (purchase value)
- Analyse purchase preferences by brand and product category
- Build audiences who purchased specific brands or product categories for use in advertising (e.g. overselling)
- Design high-value customer retention strategies
Segments prepared using the Clients model can be used as audience lists or similar audience lists in advertising systems such as Google Ads, Meta Ads or Programmatic. This enables precise campaign targeting to:
- High-value customers with frequent purchases (e.g. Champions)
- Customers making regular, frequent purchases
- Customers who have recently made a purchase (New Customers)
- Customers showing interest in specific categories or brands
- Activating customer segments such as Slipping Champions – valuable customers who have not made a purchase for an extended period
The Clients model enables effective advertising directly to selected customer groups or the creation of similar audiences based on them in advertising systems, improving the effectiveness of marketing activities.
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