Centile
what is a Centile ( percentile) in data analysis?
Un percentile ( percentile(in English) is a statistical indicator which allows divide a dataset into 100 equal partsEach percentile corresponds to a threshold below which a given percentage of values lies.
For example, the 30th percentile indicates that 30% of observations are less than or equal to this value.
The 50th percentile corresponds to the median.
1. Application in data marketing
In an environment oriented data-drivenPercentiles allow us to perform a very fine and granular segmentation customers, products, or behaviors. Here's how they are used in the digital marketing and martechs :
1.1. Behavioral segmentation
Percentiles allow customers to be categorized into 100 ordered groups according to:
- Their purchase frequency,
- Their average basket size,
- Their loyalty score,
- Their engagement (open rates, clicks…),
- Their customer lifetime (CLTV).
💡 Example: Customers above the 95th percentile of customer value are considered "ultra-premium" or ambassadors.
1.2. Detection of extremes and weak signals
Percentiles also allow us to identify:
- The high potential customers (e.g., above the 90th percentile)
- The customers at risk of churn (e.g., below the 10th percentile of interaction)
- The underperforming products in a wallet.
2. Integration into Martech analytics tools and platforms
Numerous platforms CRM, CDP or BI allow the calculation and use of percentiles:
- In google analytics 4Percentiles can be used to compare load times or performance by segment.
- In one CDP Like Salesforce or Scal-e, you can build dynamic segments based on CLTV or scoring percentiles.
- In report, Instrument ou LookerPercentiles are integrated to generate personalized visualizations or drive automated marketing recommendations (NBO/NBA).
3. Advantages and limitations
✅ Advantages:
- Very precise : better granularity than quartiles, quintiles or deciles.
- Powerful for customization : each group can receive specific treatment.
- Robust : does not depend on the average, therefore more stable in the presence of extreme values.
⚠️ Limits:
- More complex reading than other types of quantiles.
- Requires a sufficient volume of data to be statistically significant.
- May be unstable on cohorts that are too small or segmented too finely.
4. A simple example
Let us assume a basis of 10,000 customers ranked by annual purchase value.
A customer located at 80th percentile has a higher purchase value than 80% of other customers.
This allows the marketing team to:
- To assign him a VIP treatment (exclusive offers, invitations to events)
- To integrate it into a premium loyalty campaign,
- To monitor him in a premium performance dashboard.
Conclusion
Le percentile is a measure subtle, powerful and strategic in the universe of data marketing. It allows to segment the customer base accurately,direct automated actionsand of prioritize marketing efforts depending on the relative value.
In a data-driven world, where hyper-personalization is a major performance driver, percentiles become Essential references for optimizing campaigns, journeys and decisions.
See also the definitions of: quantiles, quartiles, quintiles, deciles.
Synonyms:
percentile
