Revise Percentage Options

Author: adams85

website/docs/targeting/feature-flag-evaluation.mdx

@@ -17,9 +17,9 @@ The feature flag's value is determined by:
 The feature flag's value always comes from exactly one rule, following this algorithm:
 
 1. **Evaluation of Targeting Rules:** If Targeting Rules are present, the SDK evaluates them one by one, from top to bottom. It checks if all the conditions in the rule's IF part are met (i.e. all the conditions evaluate to true).
-   - If the conditions are met, the THEN part determines the value to return. Note: If the THEN part contains Percentage Options but the [Percentage Evaluation Attribute](../percentage-options#percentage-evaluation-attribute) is missing, the SDK will skip the Targeting Rule and continue with the next rule - even though the Targeting Rule's conditions are met!
+   - If the conditions are met, the THEN part determines the value to return. However, if the THEN part contains Percentage Options but the [Percentage Evaluation Attribute](../percentage-options#percentage-evaluation-attribute) is missing from the User Object, the SDK will skip the Targeting Rule and continue with the next rule - even though the Targeting Rule's conditions are met!
    - If the conditions aren't met, the SDK moves to the next Targeting Rule, or to step 2 (below) if there are no more Targeting Rules.
-2. **Evaluation of Percentage Options:** If a *Percentage Options* rule exists, the SDK executes the [Evaluation of Percentage Options](#evaluation-of-percentage-options) algorithm to determine which Percentage Option applies to the user and returns the value associated with that option. If the necessary user attribute is missing, the SDK skips to step 3 (below).
+2. **Evaluation of Percentage Options:** If a *Percentage Options* rule exists, the SDK executes the [Evaluation of Percentage Options](#evaluation-of-percentage-options) algorithm to determine which Percentage Option applies to the user and returns the value associated with that option. If the [Percentage Evaluation Attribute](../percentage-options#percentage-evaluation-attribute) is missing from the User Object, the SDK skips to step 3 (below).
 3. **Returning simple value:** At this stage, the only remaining "rule" is the simple value specified at the end of the feature flag, which the SDK then returns.
 
 In the event of an unexpected error during evaluation, the SDK returns the [default value](../targeting-overview#default-value) passed to the `GetValue` function.
@@ -54,7 +54,7 @@ The evaluation process stops if the referenced segment is missing, and the SDK w
 
 ## Evaluation of Percentage Options
 
-[Percentage Options](../percentage-options) are designed to be consistent and sticky across all SDKs, which means that users with the same attributes fall in the same group and get the same feature flag value across the supported platforms as long as the percentage values are the same.
+[Percentage Options](../percentage-options) are designed to be *consistent* and *sticky* across all SDKs, which means that users with the same attributes fall in the same group and get the same feature flag value across the supported platforms as long as the percentage distribution is the same.
 
 The SDK looks up the [Percentage Evaluation Attribute](../percentage-options#percentage-evaluation-attribute) in the [User Object](../user-object), then:
 - The SDK creates a hash from the combination of the specific feature flag's key and the Percentage Evaluation Attribute's value.
@@ -69,7 +69,7 @@ By hashing the combination of the feature flag's key and the user attribute, we
 The evaluation process is entirely implemented within the SDKs, meaning your users' sensitive data never leaves your system. The data flow is one-way – from ConfigCat CDN servers to your SDKs – and ConfigCat does not receive or store any attributes of the [User Object](../user-object) passed to the SDKs. This design prioritizes the privacy and security of user data.
 :::
 
-### Example Scenarios for Percentage Options
+### Example scenarios for Percentage Options
 
 Imagine you have two users, Jane and Joe, and you're experimenting with two different feature flags (**isTwitterSharingEnabled** and **isFacebookSharingEnabled**) that use percentage-based targeting. In these scenarios, we see how Percentage Options allow for a controlled and gradual rollout of features, ensuring a smooth transition for users like Jane and Joe.