Customer value insights
Spaaza brings together each customer's purchase history, profile, and preferences across all of your channels into a single view of the customer. From that view, Spaaza derives a set of value and engagement insights — calculated values added to each customer's profile based on their own past behaviour and the behaviour of other customers.
This page describes the standard customer value insights and what each one means.
Recency, Frequency and Monetary (RFM)
Spaaza uses the well-established RFM method to summarise customer value. Each customer is given a Recency, a Frequency, and a Monetary score, each from 0 to 5.
Recency
A score from 0 to 5 based on when the customer's last purchase occurred.
| Last purchase time frame | Score |
|---|---|
| In the last month | 5 |
| Between 1 and 3 months | 4 |
| Between 3 and 5 months | 3 |
| Between 5 and 8 months | 2 |
| Between 8 and 24 months | 1 |
| No purchases, or more than 24 months ago | 0 |
Frequency
A score from 0 to 5 based on the average number of purchases per year, measured over the period between the customer's first and most recent purchase.
| Number of purchases in a year | Score |
|---|---|
| 9 and above | 5 |
| Between 5 and 8 times | 4 |
| Between 3 and 4 times | 3 |
| 2 times | 2 |
| 1 time | 1 |
| No purchases | 0 |
Monetary
A score from 0 to 5 based on how much the customer spends on average compared with other customers who shop with your business. Customers are split statistically into five equal quintiles across the whole customer population: the top-spending quintile scores 5, the next scores 4, and so on.
Combined RFM score
The Recency, Frequency and Monetary scores are combined into a single RFM value that can be used to define customer value. For example:
- Customer A — Recency 4, Frequency 2, Monetary 1 → RFM score 421
- Customer B — Recency 1, Frequency 3, Monetary 5 → RFM score 135
Because RFM places more weight on recency and frequency, Customer A is considered more valuable than Customer B, even though Customer B has the higher Monetary score.
Other value and engagement insights
- Brands purchased — when Spaaza receives a product feed that includes brand data, the list of brands a customer has bought in the past is added to their profile.
- Stores — the name of each physical store the customer has made a purchase in.
- Average spend value — the average value of all the customer's transactions.
- Days since last purchase — the number of days since the customer's most recent purchase.
- Number of purchases — the total number of purchases the customer has made.
- Offline shopper — true if the customer has made a purchase in a physical store, otherwise false.
- Online shopper — true if the customer has made a purchase in the webshop, otherwise false.
Can these insights be tailored for your business?
Spaaza applies a standard set of algorithms, built on our experience and industry best practice, to derive these insights. The RFM scores currently use a set of default values — for example, the recency and frequency bands shown above — that work well across a broad range of businesses.
These defaults are a starting point rather than a fixed rule. If the standard bands do not reflect how customers shop in your industry, Spaaza can tailor the RFM calculation to suit it. To have RFM tuned for your business, contact Spaaza.
Getting additional insights
If you need an insight that is not currently available, there are typically three options — in each case, contact Spaaza to discuss:
- The insight may already be on Spaaza's product roadmap, or it can be added to it.
- A data analyst can often derive the insight from existing data in Spaaza.
- Spaaza can create a custom report that includes the insight.
Where to find this in Console
Customer value insights are written onto the customer record, so they appear anywhere customer data is surfaced in Spaaza Console:
- As criteria when filtering and building Customer segments — for example, finding customers who have not purchased in more than 200 days. Segments can then be targeted by certain campaigns, such as giving double points on a given weekend.
- On a specific customer's profile page, useful for support staff dealing with an individual customer.
- In customer exports (CSV), so the data can be analysed further or imported into another system.
- Through Spaaza's API, which gives third-party systems access to the customer profile and export functionality.
Enabling customer value insights
Customer value insights are not available by default. They are switched on for your business by Spaaza, so to enable them, contact Spaaza.