[EX-2698] Document experiment protocols

hugo/config/_default/menus/main.en.yaml

@@ -10122,26 +10122,31 @@ menu:
       parent: pa_experiments_metrics
       identifier: pa_experiments_metric_sync
       weight: 1
+    - name: Standardize Experiments with Protocols
+      url: experiments/protocols
+      parent: pa_experiments
+      identifier: pa_experiments_protocols
+      weight: 2
     - name: Plan and Launch Experiments
       url: experiments/plan_and_launch_experiments
       parent: pa_experiments
       identifier: pa_experiments_plan
-      weight: 2
+      weight: 3
     - name: Read Experiment Results
       url: experiments/reading_results
       parent: pa_experiments
       identifier: pa_experiments_results
-      weight: 3
+      weight: 4
     - name: Experiment Diagnostics
       url: experiments/diagnostics
       parent: pa_experiments
       identifier: pa_experiments_diagnostics
-      weight: 4
+      weight: 5
     - name: Concepts
       url: experiments/concepts/
       parent: pa_experiments
       identifier: pa_experiments_concepts
-      weight: 5
+      weight: 6
     - name: Subject Types
       url: experiments/concepts/subject_types
       parent: pa_experiments_concepts
@@ -10166,7 +10171,7 @@ menu:
       url: experiments/statistics/
       parent: pa_experiments
       identifier: pa_experiments_statistics
-      weight: 6
+      weight: 7
     - name: Analysis Methods
       url: experiments/statistics/analysis_methods
       parent: pa_experiments_statistics
@@ -10196,7 +10201,7 @@ menu:
       url: experiments/metric_property_breakouts
       parent: pa_experiments
       identifier: pa_experiments_metric_property_breakouts
-      weight: 6
+      weight: 8
     - name: Troubleshooting
       url: experiments/troubleshooting
       parent: pa_experiments

hugo/content/en/experiments/_index.md

@@ -34,6 +34,7 @@ To get started, select a link from the table below. Otherwise, read on to learn
 | [Create a warehouse-native metric][14] | Define Metric SQL Models and experiment metrics from warehouse data |
 | [Create a metric from Product Analytics or Real User Monitoring data][15] | Build experiment metrics from client-side RUM and Product Analytics events |
 | [Launch an experiment using Datadog Feature Flags][16] | Plan your hypothesis, configure randomization with Feature Flags, and start your experiment |
+| [Standardize experiments with protocols][21] | Define reusable defaults for metrics, randomization, duration, and statistical analysis |
 | [Analyze an experiment that's already been randomized][17] | Define exposure data in your warehouse when randomization runs outside Datadog Feature Flags |
 | [Understand experiment diagnostics][20] | Interpret automated checks for exposures, metrics, randomization, and analysis health |
 
@@ -98,3 +99,4 @@ Datadog applies statistical analysis to compare variants and estimate lift. When
 [18]: /experiments/concepts/subject_types/
 [19]: /experiments/statistics/global_lift
 [20]: /experiments/diagnostics/
+[21]: /experiments/protocols/