deletes and redirects (#2443)

statsig-io · Dec 26, 2024 · 88ab981 · 88ab981
1 parent 3d440bb
commit 88ab981
Show file tree

Hide file tree

Showing 9 changed files with 19 additions and 146 deletions.
diff --git a/docs/experiments-plus/experimentation/best-practices.md b/docs/experiments-plus/experimentation/best-practices.md
diff --git a/docs/experiments-plus/experimentation/choosing-randomization-unit.md b/docs/experiments-plus/experimentation/choosing-randomization-unit.md
diff --git a/docs/experiments-plus/experimentation/common-terms.md b/docs/experiments-plus/experimentation/common-terms.md
diff --git a/docs/experiments-plus/experimentation/scenarios.md b/docs/experiments-plus/experimentation/scenarios.md
diff --git a/docs/experiments-plus/experimentation/why-experiment.md b/docs/experiments-plus/experimentation/why-experiment.md
diff --git a/docs/integrations/data-connectors/segment.mdx b/docs/integrations/data-connectors/segment.mdx
@@ -93,7 +93,7 @@ If you are unable to connect to Segment via OAuth, you can still manually connec
     ![](https://user-images.githubusercontent.com/1315028/150830169-17564060-816b-4c5c-ade9-10bf6274265a.png)
 
 ## Working with Users
-Statsig will join incoming user identifiers to whichever [unit of randomization](/experiments-plus/experimentation/choosing-randomization-unit) you choose. This allows you to be flexible with your experimentation and enables testing on known (userID) and unknown (anonymousID) traffic as well as any custom identifiers your team may have (deviceID, companyID, vehicleID, etc).
+Statsig will join incoming user identifiers to whichever [unit of randomization](/experiments-plus#choosing-the-right-randomization-unit) you choose. This allows you to be flexible with your experimentation and enables testing on known (userID) and unknown (anonymousID) traffic as well as any custom identifiers your team may have (deviceID, companyID, vehicleID, etc).
 
 ### User IDs and Custom IDs
 

diff --git a/docs/metrics/different-id.md b/docs/metrics/different-id.md
@@ -10,7 +10,7 @@ There are two common scenarios where the experiment assignment unit differs from
 
 1. Measuring session-level metrics for a user-level experiment. Ratio metrics are commonly used to solve this (this doc).
 2. Measuring logged-in metrics (eg. revenue) on a logged-out experiment. There are two solutions:
-   a. Running the experiment at the [device-level](/experiments-plus/experimentation/choosing-randomization-unit#other-stable-identifiers), with device-level metrics collected even after the user is logged-in.
+   a. Running the experiment at the [device-level](/guides/first-device-level-experiment), with device-level metrics collected even after the user is logged-in.
    b. Using [ID resolution](/statsig-warehouse-native/features/id-resolution).
 
 We will explain how to set up the first scenario with Warehouse Native in this doc.

diff --git a/docs/statsig-warehouse-native/guides/running_a_poc.mdx b/docs/statsig-warehouse-native/guides/running_a_poc.mdx
@@ -27,7 +27,7 @@ Keep these high level steps in mind as you begin your planning your Warehouse Na
        - This approach can yield results for analysis in as little as **30 minutes,** assuming data is readily available for ingestion
      - If your team plans on utilizing the **Assign and Analyze** experimentation option, you’ll want to identify **where** the experiment will run. Typically **web based** experiments are easier to evaluate, however Statsig has SDK support for server and mobile SDKs as well.
        - **Note**: It’s important the implementing team understands how the SDKs operate prior to executing a proof of concept. Our [client](/client/introduction) and [server](/server/introduction) docs can help orient your team!
-       - A typical evaluation takes **2-4 weeks** to account for experiment design, implementation, time to bake, and analysis. To ensure a successful POC, [have a well scoped plan](/guides/running-a-poc#phase-0-scope--prepare-your-poc) and ensure the right teams are included to assist along the way.
+       - A typical evaluation takes **2-4 weeks** to account for experiment design, implementation, time to bake, and analysis. To ensure a successful POC, [have a well scoped plan](/guides/running-a-poc#2-phase-0-scope--prepare-your-poc) and ensure the right teams are included to assist along the way.
    - Read [experimentation best practices](https://statsig.com/blog/product-experimentation-best-practices) to get an idea of how to best succeed.
 
 1. **Connect the Warehouse** - In order to query data and operate within your warehouse, you’ll need to allocate resources and connect to Statsig. You may choose to utilize an existing prod database or create a separate cluster specifically for experimentation (if you don’t already have one).

diff --git a/docusaurus.config.ts b/docusaurus.config.ts
@@ -144,6 +144,22 @@ const config: Config = {
       "@docusaurus/plugin-client-redirects",
       {
         redirects: [
+          {
+            from: "/experiments-plus/experimentation/why-experiment",
+            to: "/experiments-plus#why-experiment",
+          },
+          {
+            from: "/experiments-plus/experimentation/scenarios",
+            to: "/experiments-plus#scenarios-for-experimentation",
+          },
+          {
+            from: "/experiments-plus/experimentation/common-terms",
+            to: "/experiments-plus#key-concepts-in-experimentation",
+          },
+          {
+            from: "/experiments-plus/experimentation/choosing-randomization-unit",
+            to: "/experiments-plus#choosing-the-right-randomization-unit",
+          },
           {
             from: "/js-migration",
             to: "/client/javascript-sdk/migrating-from-statsig-js",