From 6de72f1d2943f9d23330f81b15c40cf4f3c4b4bf Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Mon, 21 Oct 2024 21:19:31 -0400 Subject: [PATCH 01/22] updating a/b testing doc: v2 --- .../use-cases/a-b-testing.md | 121 ++++++++++++------ website/docs/reference/api/unleash/sidebar.js | 1 + ...rial-building-blocks-strategy-variants.png | Bin 0 -> 230420 bytes website/static/img/use-case-abvbandit.png | Bin 0 -> 24942 bytes .../static/img/use-case-add-new-strategy.png | Bin 0 -> 361934 bytes .../img/use-case-create-experiment-flag.png | Bin 0 -> 386128 bytes .../static/img/use-case-gradual-rollout.png | Bin 0 -> 462879 bytes website/static/img/use-case-variants.png | Bin 0 -> 297161 bytes 8 files changed, 84 insertions(+), 38 deletions(-) create mode 100644 website/docs/reference/api/unleash/sidebar.js create mode 100644 website/static/img/tutorial-building-blocks-strategy-variants.png create mode 100644 website/static/img/use-case-abvbandit.png create mode 100644 website/static/img/use-case-add-new-strategy.png create mode 100644 website/static/img/use-case-create-experiment-flag.png create mode 100644 website/static/img/use-case-gradual-rollout.png create mode 100644 website/static/img/use-case-variants.png diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 791a2cc9aaf6..97e1bcc491be 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -1,21 +1,27 @@ --- -title: How to do A/B Testing +title: Effective A/B Testing slug: /feature-flag-tutorials/use-cases/a-b-testing --- ## What is A/B Testing? -**A/B testing** is a randomized controlled experiment where you test two or more versions of a feature to see which version performs better. If you have more than two versions, it's known as multivariate testing. Coupled with analytics, A/B and multivariate testing enable you to better understand your users and how to serve them better. +**A/B testing** is a randomized controlled experiment where you test two or more versions of a feature to see which version performs better. If you have more than two versions, it's known as **A/B/n testing**. Coupled with analytics, A/B testing enables you to better understand your users and how to serve them better. -Feature flags are a great way to run A/B tests to decouple them from your code, and Unleash ships with features to make it easy to get started with. In this tutorial, we will walk through how to do an A/B test using Unleash with your application. +**Multivariate testing** is used to test multiple variables simultaneously in order to determine the optimal combination of elements that will produce the best results. Different combinations of variables such as design, content and functionality can be tested to measure which combination has the greatest impact on user behavior or conversion rates. + +Feature flags are a great way to run A/B tests with minimal code modifications, and Unleash offers built-in features that make it easy to get started. In this tutorial, we will walk through how to do an A/B test using Unleash with your application. ## How to Perform A/B Testing with Unleash +<<<<<<< HEAD To follow along with this tutorial, you will need an Unleash instance. If you’d prefer to self-host Unleash, read our [Quickstart guide](/quickstart). Alternatively, if you’d like your project to be hosted by Unleash, go to [www.getunleash.io](https://www.getunleash.io/pricing?_gl=1*1ytmg93*_gcl_au*MTY3MTQxNjM4OS4xNzIxOTEwNTY5*_ga*OTkzMjI0MDMwLjE3MDYxNDc3ODM.*_ga_492KEZQRT8*MTcyNzQzNTQwOS4yMzcuMS4xNzI3NDM1NDExLjU4LjAuMA). +======= +To follow along with this tutorial, you will need access to an Unleash Instance. Head over to our [Quick Start documentation](/quickstart) for options, including running locally, or using an [Unleash SaaS instance](https://www.getunleash.io/pricing?). +>>>>>>> 471f6a231 (updating a/b testing doc: v2) With Unleash set up, you can use your application to talk to Unleash through one of our SDKs. -To conduct an A/B test, we will need to create the feature flag that will implement an activation strategy. In the next section, we will explore what strategies are and how they are configured in Unleash. +To do A/B testing, we will need to create the feature flag that will implement the rollout strategy. After that, we will explore what strategies are and how they are configured in Unleash. In the projects view, the Unleash platform shows a list of feature flags that you’ve generated. Click on the ‘New Feature Flag' button to create a new feature flag. @@ -29,84 +35,123 @@ The feature flag we are creating is considered an ‘Experimentation’ flag typ Read our docs on [Projects](/reference/projects) to learn more about how to configure and manage them for your team/organization. A description of the flag can help properly identify its specific purposes. However, this field is optional. -![Create a feature flag by filling out the form fields.](/img/react-tutorial-create-flag-form.png) +![Create a feature flag by filling out the form fields.](/img/use-case-create-experiment-flag.png) Once you have completed the form, you can click ‘Create feature flag’. -Your new feature flag has been created and is ready to be used. Upon returning to your projects view, enable the flag for your development environment, which makes it accessible to use in your app. +Your new feature flag has been created and is ready to be used. Next, we will configure the A/B testing strategy for your new flag. -![Enable the development environment for your feature flag for use in your application.](/img/tutorial-enable-dev-env.png) +### Target Users for A/B Testing -Next, we will configure the A/B testing strategy for your new flag. +With an A/B testing strategy, you’ll be able to: -### Implementing a Default Activation Strategy for A/B Testing +- Determine the percentage of users exposed to the new feature +- Determine the percentage of users that get exposed to each version of the feature -An important Unleash concept that enables developers to perform an A/B test is an [activation strategy](/reference/activation-strategies). An activation strategy defines who will be exposed to a particular flag or flags. Unleash comes pre-configured with multiple activation strategies that let you enable a feature only for a specified audience, depending on the parameters under which you would like to release a feature. +To target users accordingly, we will create an [activation strategy](/reference/activation-strategies). This Unleash concept defines who will be exposed to a particular flag or flags. Unleash comes pre-configured with multiple activation strategies that let you enable a feature only for a specified audience, depending on the parameters under which you would like to release a feature. ![Anatomy of an activation strategy](/img/anatomy-of-unleash-strategy.png) -Different strategies use different parameters. Predefined strategies are bundled with Unleash. The default strategy is the gradual rollout strategy with 100% rollout, which basically means that the feature is enabled for all users. In this case, we have only enabled the flag in the development environment for all users in the previous section. +Different strategies use different parameters. Predefined strategies are bundled with Unleash. The default strategy is the gradual rollout strategy with 100% rollout, which basically means that the feature is enabled for all users. In this tutorial, we will adjust the percentage of users who have access to the feature. +:::note Activation strategies are defined on the server. For server-side SDKs, activation strategy implementation is done on the client side. For frontend SDKs, the feature is calculated on the server side. +::: + +On the feature flag view in Unleash, click on the ‘Add your first strategy’ button to navigate to a (default) gradual rollout strategy form. + +![Add your first strategy from the flag view in Unleash.](/img/use-case-add-new-strategy.png) + +The gradual rollout strategy form has multiple fields that control the rollout of your feature. You can name the strategy something relevant to the A/B test you’re creating, but this is an optional field. + +![In the gradual rollout form, you can configure the parameters of your A/B tests and releases.](/img/use-case-gradual-rollout.png) + +In this form, you can configure the rollout percentage so only a certain portion of your users are targeted. For example, you can adjust the dial so that 35% of all users are targeted. The remaining percentage of users will not experience any variation of the new feature. Decide on the percentage of users that the feature will target by adjusting the rollout dial or keep it at 100% to target all users. There are two more advanced extensions of a default strategy that you will see available to customize in the form: - [Strategy Variants](/reference/strategy-variants) - [Strategy Constraints](/reference/strategy-constraints) -Variants and constraints are not required for A/B testing. These additional customizations can be built on top of the overall strategy should you need more granular conditions for your feature beyond the rollout percentage. +Variants and constraints are additional Unleash customizations that can be built on top of the overall strategy should you need more granular conditions for your feature beyond the rollout percentage. We **recommend** using strategy variants to configure an A/B test. -[Strategy variants](/reference/strategy-variants) can expose a particular version of a feature to select user bases when a flag is enabled. From there, a way to use the variants is to view the performance metrics and see which is more efficient. We can create several variations of this feature to release to users and gather performance metrics to determine which one yields better results. +[Strategy variants](/reference/strategy-variants) can expose a particular version of a feature to select user bases when a flag is enabled. From there, a way to use the variants is to collect data to see which is one yields better results, which we will cover later in the tutorial. -For A/B testing, _strategy variants_ are most applicable for more granular conditions of a feature release. In the next section, we’ll explore how to apply a strategy variant on top of an A/B test for more advanced use cases. +Using strategy variants in your activation strategy is the canonical way to run A/B tests with Unleash and your application. -### Applying Strategy Variants - -Using strategy variants in your activation strategy is the canonical way to run A/B tests with Unleash and your application. You can expose a particular version of the feature to select user bases when a flag is enabled. From there, a way to use the variants is to view the performance metrics and see which is more efficient. +![This diagram breaks down how strategy variants sit on top activation strategies for flags in Unleash.](/img/tutorial-building-blocks-strategy-variants.png) A variant has four components that define it: -- **name**: This must be unique among the strategy's variants. When working with a feature with variants in a client, you will typically use the variant's name to find out which variant it is. -- **weight**: The weight is the likelihood of any one user getting this specific variant. See the weights section for more info. -- **value** -- **(optional) payload**: A variant can also have an associated payload. Use this to deliver more data or context. See the payload section for more details. +- **a name**: This must be unique among the strategy's variants. When working with a feature with variants in a client, you will typically use the variant's name to find out which variant it is. +- **a weight**: The weight is the likelihood of any one user getting this specific variant. See the [weights section](/reference/strategy-variants#variant-weight) for more info. +- **an optional payload**: A variant can also have an associated payload. Use this to deliver more data or context. See the [payload section](/reference/strategy-variants#variant-payload) for more details. +- **a value** + +While teams may have different goals for measuring performance, Unleash enables you to configure strategy variants within your application/service and the platform. + +![You can review the anatomy of an Unleash strategy variants in relation to other Unleash features.](/img/anatomy-of-unleash-variants.png) -While teams may have different goals for measuring performance, Unleash enables you to configure a strategy for the feature variants within your application/service and the platform. +In your gradual rollout form, there is a ‘Variants’ section. Click on the ‘Add variant’ button. A form will appear where you can provide a unique name for the variant. For the purpose of this tutorial, we’ve created 2 variants shown in the image below: `variantA` and `variantB`. In a real world use case, we recommend more specific names to be comprehensible and relevant to the versions of the feature you’re referencing. Create additional variants if you need to test more versions. -## A/B Testing with Enterprise Security Automation +Next, decide on the percentage of users that will be targeted for each variant, which is known as the _variant weight_. By default, 50% of users will be targeted between 2 variants. For example, 50% users within the 35% of users targeted from the rollout percentage you defined earlier would experience `variantA`. Switch on the ‘Custom percentage’ toggle to change the default of the variant weights. -For large-scale organizations, managing feature flags across many teams can be complex and challenging. Unleash was architected for your feature flag management to be scalable and traceable for enterprises, which boosts overall internal security posture while delivering software efficiently. +![You can configure multiple strategy variants for A/B testing within the gradual rollout form.](/img/use-case-variants.png) -After you have implemented an A/B test, we recommend managing it by: +To learn more, read our documentation on [strategy variants](/reference/strategy-variants). -- Tracking performance of feature releases within your application -- Reviewing audit logs of each change to your flag configurations over time by project collaborators within your organization, which is exportable for reporting -- Reviewing and approving change requests to your flags and strategy configurations +### Manage User Session Behavior -Read our documentation on how to effectively manage [feature flags at scale](/topics/feature-flags/best-practices-using-feature-flags-at-scale) while reducing security risks. Let’s walk through these recommended Unleash features in the subsequent sections. +Unleash is built to give developers confidence in their ability to run A/B tests effectively. One critical component of implementing A/B testing strategies is maintaining a consistent experience for each user across multiple user sessions. -### Enabling Impression Data +For example, user `uuid1234` should be the target of `variantA` regardless of their session. The original subset of users that get `variantA` will continue to experience that variation of the feature over time. At Unleash, we call this [stickiness](/reference/stickiness). You can define the parameter of stickiness in the gradual rollout form. By default, stickiness is calculated by `sessionId` and `groupId`. -Once you have created a feature flag and configured your A/B test, you can use Unleash to collect insights about the ongoing results of the test. One way to collect this data is through enabling [impression data](/reference/impression-data#impression-event-data) per feature flag. Impression data contains information about a specific feature flag activation check. It’s important to review data from an A/B test, as this could inform you on how (and if) users interact with the feature you have released. +### Track A/B Testing for your Key Performance Metrics -Strategy variants are meant to work with impression data. You get the name of the variant to your analytics which allows you a better understanding of what happened, rather than seeing a simple true/false from your logs. +An A/B testing strategy is most useful when you can track the results of a feature rollout to users. When your team has clearly defined the goals for your A/B tests, you can use Unleash to analyze how results tie back to key metrics, like conversion rates or time spent on a page. One way to collect this data is through enabling impression data per feature flag. [Impression data](/reference/impression-data) contains information about a specific feature flag activation check. -To enable impression data for your flag, navigate to your feature flag form and turn the toggle on. +To enable impression data for your rollout, navigate to your feature flag form and turn the toggle on. -Next, in your application code, use the SDK to capture the impression events as they are being emitted in real time. Follow [language and framework-specific tutorials](/languages-and-frameworks) to learn how to capture the events and send them to data analytics and warehouse platforms of your choice. +![Enable impression data in the strategy rollout form for your flag.](/img/enable-impression-data.png) + +Next, in your application code, use the SDK to capture the impression events as they are being emitted in real time. Now that the application is capturing impression events, you can configure the correct data fields and formatting to send to any analytics tool or data warehouse you use. -#### Collect Event Type Data +Strategy variants are meant to work with impression data. You get the name of the variant sent to your analytics tool, which allows you a better understanding of what happened, rather than seeing a simple true/false from your logs. -Your client SDK will emit an impression event when it calls `isEnabled` or `getVariant`. Some front-end SDKs emit impression events only when a flag is enabled. +Next, in your application code, use the SDK to capture the impression events as they are being emitted in real time. Follow [language and framework-specific tutorials](/languages-and-frameworks) to learn how to capture the events and send them to data analytics and warehouse platforms of your choice. Your client SDK will emit an impression event when it calls `isEnabled` or `getVariant`. Some front-end SDKs emit impression events only when a flag is enabled. You can define custom event types to track specific user actions. If you want to confirm that users from your A/B test have the new feature, Unleash will receive the `isEnabled` event. If you have created variants, the `getVariant` event type will be sent to Unleash. -You can define custom event types to track specific user actions. If you want to confirm that users from your A/B test have the new feature, Unleash will receive the `isEnabled` event. If you have created one or more variations of the same feature, known as strategy variants, the `getVariant` event type will be sent to Unleash. +By enabling impression data for your feature flag and listening to events within your application code, you can leverage this data flowing to your integrated analytics tools to make informed decisions faster and adjust your strategies based on real user behavior. -### Automating A/B Tests with Actions & Signals +## A/B Testing with Enterprise Automation Unleash provides the ability to automate your feature flags using [actions](/reference/actions) and [signals](/reference/signals). When running A/B tests, you can configure your projects to execute tasks in response to application metrics and thresholds you define. If an experimentation feature that targets a part of your user base logs errors, your actions can automatically disable the feature so your team is given the time to triage while still providing a seamless, alternative experience to users. In another case, you can use actions to modify the percentage of users targeted for variations of a feature based off users engaging with one variation more than the other. A/B tests are performed safely and strategically with extra safeguards when you automate your flags based on user activity and other metrics of your choice. Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. + +### Multi-arm bandit tests to find the winning variant + +When running complex multivariate tests with numerous combinations, automating the process of finding the best variation of a feature is the most optimal, cost-effective approach for organizations with a large user base. [Multi-arm bandit tests](https://en.wikipedia.org/wiki/Multi-armed_bandit) are a powerful technique used in A/B testing to allocate traffic to different versions of a feature or application in a way that maximizes the desired outcome, such as conversion rate or click-through rate. This approach offers several advantages over traditional A/B testing, and is a viable solution for large enterprise teams. + +The variants you created with Unleash would be the “arms” in the multi-bandit context. You can use a multi-arm bandit algorithm, such as [epsilon-greedy](https://www.geeksforgeeks.org/epsilon-greedy-algorithm-in-reinforcement-learning/) or [Thompson sampling](https://en.wikipedia.org/wiki/Thompson_sampling), to dynamically allocate traffic based on the performance of each variant. Experiment with different variants to gather more information. Allocate more traffic to the variants that seem to be performing better. As the test progresses, the algorithm will adjust the traffic allocation to favor the variants that are showing promising results. Once the test is complete, you can analyze the data to determine the winning variant. By dynamically allocating traffic based on performance, multi-arm bandit tests can identify the winning variant more quickly than traditional A/B testing. + +![This is a graph comparing traditional A/B testing and multi-arm bandit selection.](/img/use-case-abvbandit.png) + +> [Image Source: Matt Gershoff](https://blog.conductrics.com/balancing-earning-with-learning-bandits-and-adaptive-optimization/) + +To use Unleash to conduct a multi-arm bandit test, you will need to: + +- collect the necessary data from each variant’s performance by enabling impression data for your feature flag +- capture impression events in your application code +- funnel the impression events captured from your application code to an external analytics tool +- create signal endpoint(s) in Unleash that will point to your external analytics tools +- create actions in Unleash that will react to your signals that were integrated + +This approach minimizes the "regret" associated with allocating traffic to lower performing variants. Multi-arm bandit tests using Unleash can adapt to changing conditions, such as seasonal fluctuations or user behavior changes. In some cases, they can be used to ensure that users are not exposed to suboptimal experiences for extended periods. + +A/B tests are performed safely and strategically with extra safeguards when you automate your flags based on user activity and other metrics of your choice. + +Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. diff --git a/website/docs/reference/api/unleash/sidebar.js b/website/docs/reference/api/unleash/sidebar.js new file mode 100644 index 000000000000..268b0c0a1bfd --- /dev/null +++ b/website/docs/reference/api/unleash/sidebar.js @@ -0,0 +1 @@ +module.exports = [{"type":"doc","id":"reference/api/unleash/unleash-api"},{"type":"category","label":"Addons","link":{"type":"doc","id":"reference/api/unleash/addons"},"items":[{"type":"doc","id":"reference/api/unleash/get-addons","label":"Get all addons and providers","className":"api-method 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zPC=M-i`ftbjZJls?44b0nEp)9v9VX#C2yutG!l}>f?orcd(4TYalo6^W#TQrXp^}o zTHthGS^3)HLj9>zWIbyM}oFqcr!2BtwzoKFf{n@2JVG{O{ZUx zVBiE8*k3!J>)XIrkb$Y2{~7rELV}h5Gu8hX*FW3oXZPpzj|2I?c9{(z9X*+H+Oi?` zyNi+9gTx?Ph!s)A&jU-QMbHJeKKOoh`X0>x9CuuJfXunC>pGA`QGTSLkk#L{?R(Hi zQS70wQwQg5Px&~KAk8v9`b7(ReDzL$`v-seBKQ5fMW)P*GM+$y*ava!@k8Hlq2k1T zuN}KapNto0q3%gHy2b}AE#Ar67LfD$Z-ZC`M4#n+fvyV>&>r8dY<+(oe%l!ExvwPU z!^IDf0I{5l9}`oqc3u(brjXURuJES^*~}v(b+=Ilto9z9hA37k4OO>WFTcgJ9r730 z@10-y?3|Szz^=R$`|3-XTeO*1!to5wpKbEnJHE(%}40QN}eT!p}B-V~CqN{qN%RL^=dm-Lv}I@S4vdiBdRzb@PRP@k-qxeT7?B zwAsFM&tX%{KKtnKKwD_ie%Sf#AN*<6aB2|mvt!=yL7 Date: Wed, 30 Oct 2024 19:47:14 +0100 Subject: [PATCH 02/22] multivariate update Co-authored-by: Michael Ferranti --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 97e1bcc491be..2c3c9a48c480 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -9,7 +9,7 @@ slug: /feature-flag-tutorials/use-cases/a-b-testing **Multivariate testing** is used to test multiple variables simultaneously in order to determine the optimal combination of elements that will produce the best results. Different combinations of variables such as design, content and functionality can be tested to measure which combination has the greatest impact on user behavior or conversion rates. -Feature flags are a great way to run A/B tests with minimal code modifications, and Unleash offers built-in features that make it easy to get started. In this tutorial, we will walk through how to do an A/B test using Unleash with your application. +Feature flags are a great way to run A/B or multivariate tests with minimal code modifications, and Unleash offers built-in features that make it easy to get started. In this tutorial, we will walk through how to do an A/B test using Unleash with your application. ## How to Perform A/B Testing with Unleash From 459ea15ff411beb2350761099a5061933944af58 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Wed, 30 Oct 2024 19:47:44 +0100 Subject: [PATCH 03/22] title update Co-authored-by: Michael Ferranti --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 2c3c9a48c480..704ecfac66e7 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -1,5 +1,5 @@ --- -title: Effective A/B Testing +title: Effective A/B Testing using Feature Flags slug: /feature-flag-tutorials/use-cases/a-b-testing --- From 76474daf1207057b07a331f2b447db0bfc693b1b Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Wed, 30 Oct 2024 19:48:12 +0100 Subject: [PATCH 04/22] unbranded section title update Co-authored-by: Michael Ferranti --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 704ecfac66e7..897f4d87d07f 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -11,7 +11,7 @@ slug: /feature-flag-tutorials/use-cases/a-b-testing Feature flags are a great way to run A/B or multivariate tests with minimal code modifications, and Unleash offers built-in features that make it easy to get started. In this tutorial, we will walk through how to do an A/B test using Unleash with your application. -## How to Perform A/B Testing with Unleash +## How to Perform A/B Testing with Feature Flags <<<<<<< HEAD To follow along with this tutorial, you will need an Unleash instance. If you’d prefer to self-host Unleash, read our [Quickstart guide](/quickstart). Alternatively, if you’d like your project to be hosted by Unleash, go to [www.getunleash.io](https://www.getunleash.io/pricing?_gl=1*1ytmg93*_gcl_au*MTY3MTQxNjM4OS4xNzIxOTEwNTY5*_ga*OTkzMjI0MDMwLjE3MDYxNDc3ODM.*_ga_492KEZQRT8*MTcyNzQzNTQwOS4yMzcuMS4xNzI3NDM1NDExLjU4LjAuMA). From c9b29cb8d1aa111d16ab92113975eb0a1b7d2ffb Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Wed, 30 Oct 2024 19:49:33 +0100 Subject: [PATCH 05/22] update tenses and wording Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 897f4d87d07f..b3d630948a88 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -94,7 +94,7 @@ While teams may have different goals for measuring performance, Unleash enables In your gradual rollout form, there is a ‘Variants’ section. Click on the ‘Add variant’ button. A form will appear where you can provide a unique name for the variant. For the purpose of this tutorial, we’ve created 2 variants shown in the image below: `variantA` and `variantB`. In a real world use case, we recommend more specific names to be comprehensible and relevant to the versions of the feature you’re referencing. Create additional variants if you need to test more versions. -Next, decide on the percentage of users that will be targeted for each variant, which is known as the _variant weight_. By default, 50% of users will be targeted between 2 variants. For example, 50% users within the 35% of users targeted from the rollout percentage you defined earlier would experience `variantA`. Switch on the ‘Custom percentage’ toggle to change the default of the variant weights. +Next, decide the percentage of users to target for each variant, known as the variant weight. By default, 50% of users will be targeted between 2 variants. For example, 50% of users within the 35% of users targeted from the rollout percentage you defined earlier would experience `variantA`. Toggle **Custom percentage** to change the default variant weights. ![You can configure multiple strategy variants for A/B testing within the gradual rollout form.](/img/use-case-variants.png) From 907046d502390a20b80b4e47bcf1c5dc9bdb3f4e Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Wed, 30 Oct 2024 19:52:59 +0100 Subject: [PATCH 06/22] remove repeat doc link sentence Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 1 - 1 file changed, 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index b3d630948a88..8159482d358b 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -98,7 +98,6 @@ Next, decide the percentage of users to target for each variant, known as the va ![You can configure multiple strategy variants for A/B testing within the gradual rollout form.](/img/use-case-variants.png) -To learn more, read our documentation on [strategy variants](/reference/strategy-variants). ### Manage User Session Behavior From 43aa867f774fa83bce7bc5922a1e7cf99e144b7f Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Mon, 4 Nov 2024 15:40:09 -0500 Subject: [PATCH 07/22] continue merging main --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 8159482d358b..02971a2afce1 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -13,11 +13,15 @@ Feature flags are a great way to run A/B or multivariate tests with minimal code ## How to Perform A/B Testing with Feature Flags +<<<<<<< HEAD <<<<<<< HEAD To follow along with this tutorial, you will need an Unleash instance. If you’d prefer to self-host Unleash, read our [Quickstart guide](/quickstart). Alternatively, if you’d like your project to be hosted by Unleash, go to [www.getunleash.io](https://www.getunleash.io/pricing?_gl=1*1ytmg93*_gcl_au*MTY3MTQxNjM4OS4xNzIxOTEwNTY5*_ga*OTkzMjI0MDMwLjE3MDYxNDc3ODM.*_ga_492KEZQRT8*MTcyNzQzNTQwOS4yMzcuMS4xNzI3NDM1NDExLjU4LjAuMA). ======= To follow along with this tutorial, you will need access to an Unleash Instance. Head over to our [Quick Start documentation](/quickstart) for options, including running locally, or using an [Unleash SaaS instance](https://www.getunleash.io/pricing?). >>>>>>> 471f6a231 (updating a/b testing doc: v2) +======= +To follow along with this tutorial, you will need access to an Unleash Instance which will be used to create and manage feature flags. Head over to our [Quick Start documentation](/quickstart) for options, including running locally, or using an [Unleash SaaS instance](https://www.getunleash.io/pricing?). +>>>>>>> 7db166905 (update official getting started intro) With Unleash set up, you can use your application to talk to Unleash through one of our SDKs. From eedb4b24aaf4ce3f7263551523ab13898d015059 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Wed, 30 Oct 2024 19:54:40 +0100 Subject: [PATCH 08/22] remove bold letters and simplify wording Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 02971a2afce1..93e3405ff04a 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -7,7 +7,7 @@ slug: /feature-flag-tutorials/use-cases/a-b-testing **A/B testing** is a randomized controlled experiment where you test two or more versions of a feature to see which version performs better. If you have more than two versions, it's known as **A/B/n testing**. Coupled with analytics, A/B testing enables you to better understand your users and how to serve them better. -**Multivariate testing** is used to test multiple variables simultaneously in order to determine the optimal combination of elements that will produce the best results. Different combinations of variables such as design, content and functionality can be tested to measure which combination has the greatest impact on user behavior or conversion rates. +Multivariate testing is used to test multiple variables simultaneously to determine the optimal combination of elements that will produce the best results. Different combinations of variables such as design, content, and functionality can be tested to measure which combination has the greatest impact on user behavior or conversion rates. Feature flags are a great way to run A/B or multivariate tests with minimal code modifications, and Unleash offers built-in features that make it easy to get started. In this tutorial, we will walk through how to do an A/B test using Unleash with your application. From bdb6c347910e5f95504027c6449df7d58c55dc50 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Wed, 30 Oct 2024 20:05:46 +0100 Subject: [PATCH 09/22] fix text Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 93e3405ff04a..a88de194ad93 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -153,7 +153,7 @@ To use Unleash to conduct a multi-arm bandit test, you will need to: - create signal endpoint(s) in Unleash that will point to your external analytics tools - create actions in Unleash that will react to your signals that were integrated -This approach minimizes the "regret" associated with allocating traffic to lower performing variants. Multi-arm bandit tests using Unleash can adapt to changing conditions, such as seasonal fluctuations or user behavior changes. In some cases, they can be used to ensure that users are not exposed to suboptimal experiences for extended periods. +This approach minimizes the "regret" associated with allocating traffic to lower-performing variants. Multi-arm bandit tests using Unleash can adapt to changing conditions, such as seasonal fluctuations or user behavior changes. In some cases, they can be used to ensure that users are not exposed to suboptimal experiences for extended periods. A/B tests are performed safely and strategically with extra safeguards when you automate your flags based on user activity and other metrics of your choice. From 23a1615639e072cf6a54b31cc561362c49a7ea53 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 31 Oct 2024 02:04:01 +0100 Subject: [PATCH 10/22] remove bold formatting Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index a88de194ad93..29a182fcd558 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -5,7 +5,7 @@ slug: /feature-flag-tutorials/use-cases/a-b-testing ## What is A/B Testing? -**A/B testing** is a randomized controlled experiment where you test two or more versions of a feature to see which version performs better. If you have more than two versions, it's known as **A/B/n testing**. Coupled with analytics, A/B testing enables you to better understand your users and how to serve them better. +A/B testing is a randomized controlled experiment where you test two or more versions of a feature to see which version performs better. If you have more than two versions, it's known as A/B/n testing. Coupled with analytics, A/B testing enables you to better understand your users and how to serve them better. Multivariate testing is used to test multiple variables simultaneously to determine the optimal combination of elements that will produce the best results. Different combinations of variables such as design, content, and functionality can be tested to measure which combination has the greatest impact on user behavior or conversion rates. From 9e191da2bf297c71a5caa6ea5955bbddc77de281 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 31 Oct 2024 08:51:55 -0400 Subject: [PATCH 11/22] additional wording updates --- .../use-cases/a-b-testing.md | 59 +++++++++---------- 1 file changed, 28 insertions(+), 31 deletions(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 29a182fcd558..b3447d76f3c2 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -23,19 +23,19 @@ To follow along with this tutorial, you will need access to an Unleash Instance. To follow along with this tutorial, you will need access to an Unleash Instance which will be used to create and manage feature flags. Head over to our [Quick Start documentation](/quickstart) for options, including running locally, or using an [Unleash SaaS instance](https://www.getunleash.io/pricing?). >>>>>>> 7db166905 (update official getting started intro) -With Unleash set up, you can use your application to talk to Unleash through one of our SDKs. +With Unleash set up, you can use your application to talk to Unleash through one of our [SDKs](/reference/sdks). -To do A/B testing, we will need to create the feature flag that will implement the rollout strategy. After that, we will explore what strategies are and how they are configured in Unleash. +To do A/B testing, we'll create a feature flag to implement the rollout strategy. After that, we'll explore what strategies are and how they are configured in Unleash. -In the projects view, the Unleash platform shows a list of feature flags that you’ve generated. Click on the ‘New Feature Flag' button to create a new feature flag. +In the Unleash Admin UI, open a project and click **New feature flag**. ![Create a new feature flag in Unleash.](/img/react-tutorial-create-new-flag.png) Next, you will create a feature flag on the platform and turn it on for your app. -Flags can be used with different purposes and we consider experimentation important enough to have its own flag type. Experimentation flags have a lifetime expectancy suited to let you run an experiment and gather enough data to know whether it was a success or not. Learn more about [feature flag types](/reference/feature-toggles#feature-flag-types) in our documentation. +Feature flags can be used for different purposes and we consider experimentation important enough to have its own flag type. Experimentation flags have a lifetime expectancy suited for running an experiment and gathering enough data to know whether the experiment was a success or not. -The feature flag we are creating is considered an ‘Experimentation’ flag type. The project will be ‘Default’ or the named project in which you are working in for the purpose of this tutorial. As the number of feature flags grows, you can organize them in your projects. +The feature flag we are creating is considered an Experiment flag type. Read our docs on [Projects](/reference/projects) to learn more about how to configure and manage them for your team/organization. A description of the flag can help properly identify its specific purposes. However, this field is optional. @@ -52,17 +52,17 @@ With an A/B testing strategy, you’ll be able to: - Determine the percentage of users exposed to the new feature - Determine the percentage of users that get exposed to each version of the feature -To target users accordingly, we will create an [activation strategy](/reference/activation-strategies). This Unleash concept defines who will be exposed to a particular flag or flags. Unleash comes pre-configured with multiple activation strategies that let you enable a feature only for a specified audience, depending on the parameters under which you would like to release a feature. +To target users accordingly, let's create an [activation strategy](/reference/activation-strategies). This Unleash concept defines who will be exposed to a particular flag. Unleash comes pre-configured with multiple activation strategies that let you enable a feature only for a specified audience, depending on the parameters under which you would like to release a feature. ![Anatomy of an activation strategy](/img/anatomy-of-unleash-strategy.png) -Different strategies use different parameters. Predefined strategies are bundled with Unleash. The default strategy is the gradual rollout strategy with 100% rollout, which basically means that the feature is enabled for all users. In this tutorial, we will adjust the percentage of users who have access to the feature. +Different strategies use different parameters. Predefined strategies are bundled with Unleash. The default strategy is a gradual rollout to 100%, which means that the feature is enabled for all users. In this tutorial, we'll adjust the percentage of users who have access to the feature. :::note Activation strategies are defined on the server. For server-side SDKs, activation strategy implementation is done on the client side. For frontend SDKs, the feature is calculated on the server side. ::: -On the feature flag view in Unleash, click on the ‘Add your first strategy’ button to navigate to a (default) gradual rollout strategy form. +Open your feature flag and click **Add strategy**. ![Add your first strategy from the flag view in Unleash.](/img/use-case-add-new-strategy.png) @@ -70,16 +70,16 @@ The gradual rollout strategy form has multiple fields that control the rollout o ![In the gradual rollout form, you can configure the parameters of your A/B tests and releases.](/img/use-case-gradual-rollout.png) -In this form, you can configure the rollout percentage so only a certain portion of your users are targeted. For example, you can adjust the dial so that 35% of all users are targeted. The remaining percentage of users will not experience any variation of the new feature. Decide on the percentage of users that the feature will target by adjusting the rollout dial or keep it at 100% to target all users. +Next, configure the rollout percentage so only a certain portion of your users are targeted. For example, you can adjust the dial so that 35% of all users are targeted. The remaining percentage of users will not experience any variation of the new feature. Adjust the rollout dial to set the percentage of users the feature targets, or keep it at 100% to target all users. There are two more advanced extensions of a default strategy that you will see available to customize in the form: -- [Strategy Variants](/reference/strategy-variants) -- [Strategy Constraints](/reference/strategy-constraints) +- [Strategy variants](/reference/strategy-variants) +- [Strategy constraints](/reference/strategy-constraints) -Variants and constraints are additional Unleash customizations that can be built on top of the overall strategy should you need more granular conditions for your feature beyond the rollout percentage. We **recommend** using strategy variants to configure an A/B test. +With strategy variants and constraints, you can extend your overall strategy. They help you define more granular conditions for your feature beyond the rollout percentage. We recommend using strategy variants to configure an A/B test. -[Strategy variants](/reference/strategy-variants) can expose a particular version of a feature to select user bases when a flag is enabled. From there, a way to use the variants is to collect data to see which is one yields better results, which we will cover later in the tutorial. +[Strategy variants](/reference/strategy-variants) let you expose a particular version of a feature to select user bases when a flag is enabled. You can then collect data to determine which variant performs better, which we'll cover later in this tutorial. Using strategy variants in your activation strategy is the canonical way to run A/B tests with Unleash and your application. @@ -87,22 +87,21 @@ Using strategy variants in your activation strategy is the canonical way to run A variant has four components that define it: -- **a name**: This must be unique among the strategy's variants. When working with a feature with variants in a client, you will typically use the variant's name to find out which variant it is. -- **a weight**: The weight is the likelihood of any one user getting this specific variant. See the [weights section](/reference/strategy-variants#variant-weight) for more info. -- **an optional payload**: A variant can also have an associated payload. Use this to deliver more data or context. See the [payload section](/reference/strategy-variants#variant-payload) for more details. -- **a value** +- a name: This must be unique among the strategy's variants. You typically use the name to identify the variant in your client. +- a weight: The[variant weight](<(/reference/strategy-variants#variant-weight)>) is the likelihood of any one user getting this specific variant. +- an optional payload: A variant can also have an associated [payload](/reference/strategy-variants#variant-payload) to deliver more data or context. +- a value While teams may have different goals for measuring performance, Unleash enables you to configure strategy variants within your application/service and the platform. ![You can review the anatomy of an Unleash strategy variants in relation to other Unleash features.](/img/anatomy-of-unleash-variants.png) -In your gradual rollout form, there is a ‘Variants’ section. Click on the ‘Add variant’ button. A form will appear where you can provide a unique name for the variant. For the purpose of this tutorial, we’ve created 2 variants shown in the image below: `variantA` and `variantB`. In a real world use case, we recommend more specific names to be comprehensible and relevant to the versions of the feature you’re referencing. Create additional variants if you need to test more versions. +Open the gradual rollout strategy, select the **Variants** tab, and click **Add variant**. Enter a unique name for the variant. For the purpose of this tutorial, we’ve created 2 variants: `variantA` and `variantB`. In a real-world use case, we recommend more specific names to be comprehensible and relevant to the versions of the feature you’re referencing. Create additional variants if you need to test more versions. Next, decide the percentage of users to target for each variant, known as the variant weight. By default, 50% of users will be targeted between 2 variants. For example, 50% of users within the 35% of users targeted from the rollout percentage you defined earlier would experience `variantA`. Toggle **Custom percentage** to change the default variant weights. ![You can configure multiple strategy variants for A/B testing within the gradual rollout form.](/img/use-case-variants.png) - ### Manage User Session Behavior Unleash is built to give developers confidence in their ability to run A/B tests effectively. One critical component of implementing A/B testing strategies is maintaining a consistent experience for each user across multiple user sessions. @@ -111,7 +110,7 @@ For example, user `uuid1234` should be the target of `variantA` regardless of th ### Track A/B Testing for your Key Performance Metrics -An A/B testing strategy is most useful when you can track the results of a feature rollout to users. When your team has clearly defined the goals for your A/B tests, you can use Unleash to analyze how results tie back to key metrics, like conversion rates or time spent on a page. One way to collect this data is through enabling impression data per feature flag. [Impression data](/reference/impression-data) contains information about a specific feature flag activation check. +An A/B testing strategy is most useful when you can track the results of a feature rollout to users. When your team has clearly defined the goals for your A/B tests, you can use Unleash to analyze how results tie back to key metrics, like conversion rates or time spent on a page. One way to collect this data is by enabling [impression data](/reference/impression-data) per feature flag. Impression data contains information about a specific feature flag activation check. To enable impression data for your rollout, navigate to your feature flag form and turn the toggle on. @@ -131,27 +130,25 @@ By enabling impression data for your feature flag and listening to events within Unleash provides the ability to automate your feature flags using [actions](/reference/actions) and [signals](/reference/signals). When running A/B tests, you can configure your projects to execute tasks in response to application metrics and thresholds you define. If an experimentation feature that targets a part of your user base logs errors, your actions can automatically disable the feature so your team is given the time to triage while still providing a seamless, alternative experience to users. In another case, you can use actions to modify the percentage of users targeted for variations of a feature based off users engaging with one variation more than the other. -A/B tests are performed safely and strategically with extra safeguards when you automate your flags based on user activity and other metrics of your choice. - Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. -### Multi-arm bandit tests to find the winning variant +### Multi-arm Bandit Tests to Find the Winning Variant -When running complex multivariate tests with numerous combinations, automating the process of finding the best variation of a feature is the most optimal, cost-effective approach for organizations with a large user base. [Multi-arm bandit tests](https://en.wikipedia.org/wiki/Multi-armed_bandit) are a powerful technique used in A/B testing to allocate traffic to different versions of a feature or application in a way that maximizes the desired outcome, such as conversion rate or click-through rate. This approach offers several advantages over traditional A/B testing, and is a viable solution for large enterprise teams. +When running complex multivariate tests with numerous combinations, automating the process of finding the best variation of a feature is the most optimal, cost-effective approach for organizations with a large user base. [Multi-arm bandit tests](https://en.wikipedia.org/wiki/Multi-armed_bandit) are a powerful technique used in A/B testing to allocate traffic to different versions of a feature or application in a way that maximizes the desired outcome, such as conversion rate or click-through rate. This approach offers several advantages over traditional A/B testing and is a viable solution for large enterprise teams. -The variants you created with Unleash would be the “arms” in the multi-bandit context. You can use a multi-arm bandit algorithm, such as [epsilon-greedy](https://www.geeksforgeeks.org/epsilon-greedy-algorithm-in-reinforcement-learning/) or [Thompson sampling](https://en.wikipedia.org/wiki/Thompson_sampling), to dynamically allocate traffic based on the performance of each variant. Experiment with different variants to gather more information. Allocate more traffic to the variants that seem to be performing better. As the test progresses, the algorithm will adjust the traffic allocation to favor the variants that are showing promising results. Once the test is complete, you can analyze the data to determine the winning variant. By dynamically allocating traffic based on performance, multi-arm bandit tests can identify the winning variant more quickly than traditional A/B testing. +The variants you created with Unleash would be the "arms" in the multi-bandit context. You can use a multi-arm bandit algorithm, such as [epsilon-greedy](https://www.geeksforgeeks.org/epsilon-greedy-algorithm-in-reinforcement-learning/) or [Thompson sampling](https://en.wikipedia.org/wiki/Thompson_sampling), to dynamically allocate traffic based on the performance of each variant. Experiment with different variants to gather more information. Allocate more traffic to the variants that are performing better. As the test progresses, the algorithm will adjust the traffic allocation to favor the variants that are showing promising results. After completing the test, you can analyze the data to determine the winning variant. By dynamically allocating traffic based on performance, multi-arm bandit tests can identify the winning variant more quickly than traditional A/B testing. ![This is a graph comparing traditional A/B testing and multi-arm bandit selection.](/img/use-case-abvbandit.png) > [Image Source: Matt Gershoff](https://blog.conductrics.com/balancing-earning-with-learning-bandits-and-adaptive-optimization/) -To use Unleash to conduct a multi-arm bandit test, you will need to: +To use Unleash to conduct a multi-arm bandit test, follow these steps: -- collect the necessary data from each variant’s performance by enabling impression data for your feature flag -- capture impression events in your application code -- funnel the impression events captured from your application code to an external analytics tool -- create signal endpoint(s) in Unleash that will point to your external analytics tools -- create actions in Unleash that will react to your signals that were integrated +1. Collect the necessary data from each variant’s performance by enabling impression data for your feature flag +2. Capture impression events in your application code +3. Funnel the impression events captured from your application code to an external analytics tool +4. Create signal endpoints in Unleash that will point to your external analytics tools +5. Create actions in Unleash that will react to your signals that were integrated This approach minimizes the "regret" associated with allocating traffic to lower-performing variants. Multi-arm bandit tests using Unleash can adapt to changing conditions, such as seasonal fluctuations or user behavior changes. In some cases, they can be used to ensure that users are not exposed to suboptimal experiences for extended periods. From 76ef3bc2ff1055722b71bed73f285cc5f9feff7d Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 31 Oct 2024 08:58:17 -0400 Subject: [PATCH 12/22] adding outline of tutorial --- .../feature-flag-tutorials/use-cases/a-b-testing.md | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index b3447d76f3c2..d33f3f9ed045 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -25,6 +25,15 @@ To follow along with this tutorial, you will need access to an Unleash Instance With Unleash set up, you can use your application to talk to Unleash through one of our [SDKs](/reference/sdks). +In this tutorial, you will learn how to set up and run an A/B testing using feature flags. You will learn: + +how to use feature flags to define variants of your application for testing, +target specific users for each test variant, +manage cross-session visibility of test variants, +connect feature flag impression data to conversion outcomes, and +roll out the winning variant to all users. +You will also learn about how to automate advanced A/B testing strategies such as multi-arm bandit testing using feature flags. + To do A/B testing, we'll create a feature flag to implement the rollout strategy. After that, we'll explore what strategies are and how they are configured in Unleash. In the Unleash Admin UI, open a project and click **New feature flag**. @@ -92,8 +101,6 @@ A variant has four components that define it: - an optional payload: A variant can also have an associated [payload](/reference/strategy-variants#variant-payload) to deliver more data or context. - a value -While teams may have different goals for measuring performance, Unleash enables you to configure strategy variants within your application/service and the platform. - ![You can review the anatomy of an Unleash strategy variants in relation to other Unleash features.](/img/anatomy-of-unleash-variants.png) Open the gradual rollout strategy, select the **Variants** tab, and click **Add variant**. Enter a unique name for the variant. For the purpose of this tutorial, we’ve created 2 variants: `variantA` and `variantB`. In a real-world use case, we recommend more specific names to be comprehensible and relevant to the versions of the feature you’re referencing. Create additional variants if you need to test more versions. From a0e921c129e082419568b1b9c833175064ec9467 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 31 Oct 2024 15:51:32 -0400 Subject: [PATCH 13/22] retaking all unleash UI screenshots --- .../use-cases/a-b-testing.md | 31 +++++++++--------- .../img/use-case-ab-testing-vs-bandit.png | Bin 0 -> 215265 bytes website/static/img/use-case-abvbandit.png | Bin 24942 -> 0 bytes .../static/img/use-case-add-new-strategy.png | Bin 361934 -> 0 bytes .../img/use-case-create-experiment-flag.png | Bin 386128 -> 300550 bytes .../img/use-case-experiment-add-strategy.png | Bin 0 -> 634490 bytes ...case-experiment-enable-impression-data.png | Bin 0 -> 519558 bytes .../use-case-experiment-gradual-rollout.png | Bin 0 -> 534548 bytes .../img/use-case-experiment-variants.png | Bin 0 -> 403604 bytes .../static/img/use-case-gradual-rollout.png | Bin 462879 -> 0 bytes website/static/img/use-case-new-flag.png | Bin 0 -> 219663 bytes website/static/img/use-case-variants.png | Bin 297161 -> 0 bytes 12 files changed, 16 insertions(+), 15 deletions(-) create mode 100644 website/static/img/use-case-ab-testing-vs-bandit.png delete mode 100644 website/static/img/use-case-abvbandit.png delete mode 100644 website/static/img/use-case-add-new-strategy.png create mode 100644 website/static/img/use-case-experiment-add-strategy.png create mode 100644 website/static/img/use-case-experiment-enable-impression-data.png create mode 100644 website/static/img/use-case-experiment-gradual-rollout.png create mode 100644 website/static/img/use-case-experiment-variants.png delete mode 100644 website/static/img/use-case-gradual-rollout.png create mode 100644 website/static/img/use-case-new-flag.png delete mode 100644 website/static/img/use-case-variants.png diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index d33f3f9ed045..d656e3bbc93e 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -27,18 +27,21 @@ With Unleash set up, you can use your application to talk to Unleash through one In this tutorial, you will learn how to set up and run an A/B testing using feature flags. You will learn: -how to use feature flags to define variants of your application for testing, -target specific users for each test variant, -manage cross-session visibility of test variants, -connect feature flag impression data to conversion outcomes, and -roll out the winning variant to all users. +1. How to use feature flags to define variants of your application for testing, +2. Target specific users for each test variant, +3. Manage cross-session visibility of test variants, +4. Connect feature flag impression data to conversion outcomes, and +5. Roll out the winning variant to all users. + You will also learn about how to automate advanced A/B testing strategies such as multi-arm bandit testing using feature flags. +### Create a Feature Flag + To do A/B testing, we'll create a feature flag to implement the rollout strategy. After that, we'll explore what strategies are and how they are configured in Unleash. In the Unleash Admin UI, open a project and click **New feature flag**. -![Create a new feature flag in Unleash.](/img/react-tutorial-create-new-flag.png) +![Create a new feature flag in the Unleash Admin UI.](/img/use-case-new-flag.png) Next, you will create a feature flag on the platform and turn it on for your app. @@ -73,11 +76,11 @@ Activation strategies are defined on the server. For server-side SDKs, activatio Open your feature flag and click **Add strategy**. -![Add your first strategy from the flag view in Unleash.](/img/use-case-add-new-strategy.png) +![Add your first strategy from the flag view in Unleash.](/img/use-case-experiment-add-strategy.png) The gradual rollout strategy form has multiple fields that control the rollout of your feature. You can name the strategy something relevant to the A/B test you’re creating, but this is an optional field. -![In the gradual rollout form, you can configure the parameters of your A/B tests and releases.](/img/use-case-gradual-rollout.png) +![In the gradual rollout form, you can configure the parameters of your A/B tests and releases.](/img/use-case-experiment-gradual-rollout.png) Next, configure the rollout percentage so only a certain portion of your users are targeted. For example, you can adjust the dial so that 35% of all users are targeted. The remaining percentage of users will not experience any variation of the new feature. Adjust the rollout dial to set the percentage of users the feature targets, or keep it at 100% to target all users. @@ -97,17 +100,15 @@ Using strategy variants in your activation strategy is the canonical way to run A variant has four components that define it: - a name: This must be unique among the strategy's variants. You typically use the name to identify the variant in your client. -- a weight: The[variant weight](<(/reference/strategy-variants#variant-weight)>) is the likelihood of any one user getting this specific variant. +- a weight: The [variant weight](/reference/strategy-variants#variant-weight) is the likelihood of any one user getting this specific variant. - an optional payload: A variant can also have an associated [payload](/reference/strategy-variants#variant-payload) to deliver more data or context. -- a value - -![You can review the anatomy of an Unleash strategy variants in relation to other Unleash features.](/img/anatomy-of-unleash-variants.png) +- a value: This describes the purpose of the variant. For example, "Most Read" or "Most Popular". Open the gradual rollout strategy, select the **Variants** tab, and click **Add variant**. Enter a unique name for the variant. For the purpose of this tutorial, we’ve created 2 variants: `variantA` and `variantB`. In a real-world use case, we recommend more specific names to be comprehensible and relevant to the versions of the feature you’re referencing. Create additional variants if you need to test more versions. Next, decide the percentage of users to target for each variant, known as the variant weight. By default, 50% of users will be targeted between 2 variants. For example, 50% of users within the 35% of users targeted from the rollout percentage you defined earlier would experience `variantA`. Toggle **Custom percentage** to change the default variant weights. -![You can configure multiple strategy variants for A/B testing within the gradual rollout form.](/img/use-case-variants.png) +![You can configure multiple strategy variants for A/B testing within the gradual rollout form.](/img/use-case-experiment-variants.png) ### Manage User Session Behavior @@ -121,7 +122,7 @@ An A/B testing strategy is most useful when you can track the results of a featu To enable impression data for your rollout, navigate to your feature flag form and turn the toggle on. -![Enable impression data in the strategy rollout form for your flag.](/img/enable-impression-data.png) +![Enable impression data in the strategy rollout form for your flag.](/img/use-case-experiment-enable-impression-data.png) Next, in your application code, use the SDK to capture the impression events as they are being emitted in real time. @@ -145,7 +146,7 @@ When running complex multivariate tests with numerous combinations, automating t The variants you created with Unleash would be the "arms" in the multi-bandit context. You can use a multi-arm bandit algorithm, such as [epsilon-greedy](https://www.geeksforgeeks.org/epsilon-greedy-algorithm-in-reinforcement-learning/) or [Thompson sampling](https://en.wikipedia.org/wiki/Thompson_sampling), to dynamically allocate traffic based on the performance of each variant. Experiment with different variants to gather more information. Allocate more traffic to the variants that are performing better. As the test progresses, the algorithm will adjust the traffic allocation to favor the variants that are showing promising results. After completing the test, you can analyze the data to determine the winning variant. By dynamically allocating traffic based on performance, multi-arm bandit tests can identify the winning variant more quickly than traditional A/B testing. -![This is a graph comparing traditional A/B testing and multi-arm bandit selection.](/img/use-case-abvbandit.png) +![This is a graph comparing traditional A/B testing and multi-arm bandit selection.](/img/use-case-ab-testing-vs-bandit.png) > [Image Source: Matt Gershoff](https://blog.conductrics.com/balancing-earning-with-learning-bandits-and-adaptive-optimization/) diff --git a/website/static/img/use-case-ab-testing-vs-bandit.png b/website/static/img/use-case-ab-testing-vs-bandit.png new file mode 100644 index 0000000000000000000000000000000000000000..58283439e6d8eab08d38d8b5529dbfaf88390a15 GIT binary patch literal 215265 zcmeFYWms1I_AW|^NGnK5gMdhjbT`r+B8`M}cZZaSbPEWGyoiW^bPEUwNJ&YHba(CX z_^!47@7m{lIM>-<_jOI>iTTX=ixKyIk1-=vm1S`-$uNp=+?qF)c=4s~$XComA ziF!Jkm_4&_r8c#&w6+&!+^TD0q_#E}X4HA8#G&LUX<=n8=k08v;jOG`=Kai!-<(lY 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zPC=M-i`ftbjZJls?44b0nEp)9v9VX#C2yutG!l}>f?orcd(4TYalo6^W#TQrXp^}o zTHthGS^3)HLj9>zWIbyM}oFqcr!2BtwzoKFf{n@2JVG{O{ZUx zVBiE8*k3!J>)XIrkb$Y2{~7rELV}h5Gu8hX*FW3oXZPpzj|2I?c9{(z9X*+H+Oi?` zyNi+9gTx?Ph!s)A&jU-QMbHJeKKOoh`X0>x9CuuJfXunC>pGA`QGTSLkk#L{?R(Hi zQS70wQwQg5Px&~KAk8v9`b7(ReDzL$`v-seBKQ5fMW)P*GM+$y*ava!@k8Hlq2k1T zuN}KapNto0q3%gHy2b}AE#Ar67LfD$Z-ZC`M4#n+fvyV>&>r8dY<+(oe%l!ExvwPU z!^IDf0I{5l9}`oqc3u(brjXURuJES^*~}v(b+=Ilto9z9hA37k4OO>WFTcgJ9r730 z@10-y?3|Szz^=R$`|3-XTeO*1!to5wpKbEnJHE(%}40QN}eT!p}B-V~CqN{qN%RL^=dm-Lv}I@S4vdiBdRzb@PRP@k-qxeT7?B zwAsFM&tX%{KKtnKKwD_ie%Sf#AN*<6aB2|mvt!=yL7 Date: Mon, 4 Nov 2024 13:24:16 -0500 Subject: [PATCH 14/22] breaking down impression data and analytics tools integration --- .../use-cases/a-b-testing.md | 90 +++++++++++++++++-- 1 file changed, 85 insertions(+), 5 deletions(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index d656e3bbc93e..9c3493922e24 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -125,12 +125,92 @@ To enable impression data for your rollout, navigate to your feature flag form a ![Enable impression data in the strategy rollout form for your flag.](/img/use-case-experiment-enable-impression-data.png) Next, in your application code, use the SDK to capture the impression events as they are being emitted in real time. - -Now that the application is capturing impression events, you can configure the correct data fields and formatting to send to any analytics tool or data warehouse you use. +Your client SDK will emit an impression event when it calls `isEnabled` or `getVariant`. Some front-end SDKs emit impression events only when a flag is enabled. You can define custom event types to track specific user actions. If you want to confirm that users from your A/B test have the new feature, Unleash will receive the `isEnabled` event. If you have created variants, the `getVariant` event type will be sent to Unleash. Strategy variants are meant to work with impression data. You get the name of the variant sent to your analytics tool, which allows you a better understanding of what happened, rather than seeing a simple true/false from your logs. -Next, in your application code, use the SDK to capture the impression events as they are being emitted in real time. Follow [language and framework-specific tutorials](/languages-and-frameworks) to learn how to capture the events and send them to data analytics and warehouse platforms of your choice. Your client SDK will emit an impression event when it calls `isEnabled` or `getVariant`. Some front-end SDKs emit impression events only when a flag is enabled. You can define custom event types to track specific user actions. If you want to confirm that users from your A/B test have the new feature, Unleash will receive the `isEnabled` event. If you have created variants, the `getVariant` event type will be sent to Unleash. +The output from the impression data in your app may look like this code snippet: + +```js +{ + "eventType": "getVariant", + "eventId": "c41aa58b-d2c7-45cf-b668-7267f465e01a", + "context": { + "sessionId": 386689528, + "appName": "my-example-app", + "environment": "default" + }, + "enabled": true, + "featureName": "ab-testing-example", + "impressionData": true, + "variant": "variantA" +} +``` + +In order to capture impression events in your app, follow our [language and framework-specific tutorials](/languages-and-frameworks). + +Now that your application is capturing impression events, you can configure the correct data fields and formatting to send to any analytics tool or data warehouse you use. + +Here are two code examples of collecting impression data in an application to send to Google Analytics: + +Example 1 + +```js +unleash.on(UnleashEvents.Impression, (e: ImpressionEvent) => { + // send to google analytics, something like + gtag("event", "screen_view", { + app_name: e.context.appName, + feature: e.featureName, + treatment: e.enabled ? e.variant : "Control", // in case we use feature disabled for control + }); +}); +``` + +Example 2 + +```js +unleash.on(UnleashEvents.Impression, (e: ImpressionEvent) => { + if (e.enabled) { + // send to google analytics, something like + gtag("event", "screen_view", { + app_name: e.context.appName, + feature: e.featureName, + treatment: e.variant, // in case we use a variant for the control treatment + }); + } +}); +``` + +In these example code snippets, `e` references the event object from the impression data output. Map these values to plug into the appropriate functions that make calls to your analytics tools and data warehouses. + +In some cases like in Example 1, you may want to use the "disabled feature" state as the "Control group". + +Alternatively, in Example 2, you can expose the feature to 100% of users and use two variants: "Control" and "Test". In either case, the variants are always used for the "Test" group. The difference is determined by how you use the "Control" group. + +An advantage of having your feature disabled for the Control group is that you can use metrics to see how many of the users are exposed to experiment(s) in comparison to the ones that are not. If you use only variants (for both the test and control group), you may see the feature metric as 100% exposed and would have to look deeper into the variant to know how many were exposed. + +Here is an example of a payload that is returned from Google Analytics that includes impression event data: + +```js +{ + "client_id": "unleash_client" + "user_id": "uuid1234" + "timestamp_micros": "1730407349525000" + "non_personalized_ads": true + "events": [ + { + "name":"select_item" + "params": { + "items":[] + "event":"screen_view" + "app_name":"myAppName" + "feature":"myFeatureName" + "treatment":"variantValue" + } + } + ] +} +``` By enabling impression data for your feature flag and listening to events within your application code, you can leverage this data flowing to your integrated analytics tools to make informed decisions faster and adjust your strategies based on real user behavior. @@ -158,8 +238,8 @@ To use Unleash to conduct a multi-arm bandit test, follow these steps: 4. Create signal endpoints in Unleash that will point to your external analytics tools 5. Create actions in Unleash that will react to your signals that were integrated +Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. + This approach minimizes the "regret" associated with allocating traffic to lower-performing variants. Multi-arm bandit tests using Unleash can adapt to changing conditions, such as seasonal fluctuations or user behavior changes. In some cases, they can be used to ensure that users are not exposed to suboptimal experiences for extended periods. A/B tests are performed safely and strategically with extra safeguards when you automate your flags based on user activity and other metrics of your choice. - -Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. From ea375f525f1c31300ed2d4a4c72f33baa3012f3f Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Mon, 4 Nov 2024 15:35:48 -0500 Subject: [PATCH 15/22] number the tutorial steps in outline --- .../use-cases/a-b-testing.md | 32 ++++++++++--------- 1 file changed, 17 insertions(+), 15 deletions(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 9c3493922e24..73e474a4041f 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -1,14 +1,8 @@ --- -title: Effective A/B Testing using Feature Flags +title: A/B Testing using Feature Flags slug: /feature-flag-tutorials/use-cases/a-b-testing --- -## What is A/B Testing? - -A/B testing is a randomized controlled experiment where you test two or more versions of a feature to see which version performs better. If you have more than two versions, it's known as A/B/n testing. Coupled with analytics, A/B testing enables you to better understand your users and how to serve them better. - -Multivariate testing is used to test multiple variables simultaneously to determine the optimal combination of elements that will produce the best results. Different combinations of variables such as design, content, and functionality can be tested to measure which combination has the greatest impact on user behavior or conversion rates. - Feature flags are a great way to run A/B or multivariate tests with minimal code modifications, and Unleash offers built-in features that make it easy to get started. In this tutorial, we will walk through how to do an A/B test using Unleash with your application. ## How to Perform A/B Testing with Feature Flags @@ -25,15 +19,15 @@ To follow along with this tutorial, you will need access to an Unleash Instance With Unleash set up, you can use your application to talk to Unleash through one of our [SDKs](/reference/sdks). -In this tutorial, you will learn how to set up and run an A/B testing using feature flags. You will learn: +In this tutorial, you will learn how to set up and run an A/B test using feature flags. You will learn: -1. How to use feature flags to define variants of your application for testing, -2. Target specific users for each test variant, -3. Manage cross-session visibility of test variants, -4. Connect feature flag impression data to conversion outcomes, and -5. Roll out the winning variant to all users. +1. [How to use feature flags to define variants of your application for testing](#create-a-feature-flag) +2. [Target specific users for each test variant](#target-users-for-ab-testing) +3. [Manage cross-session visibility of test variants](#manage-user-session-behavior) +4. [Connect feature flag impression data to conversion outcomes](#track-ab-testing-for-your-key-performance-metrics) +5. [Roll out the winning variant to all users](#multi-arm-bandit-tests-to-find-the-winning-variant) -You will also learn about how to automate advanced A/B testing strategies such as multi-arm bandit testing using feature flags. +You will also learn about how to [automate advanced A/B testing strategies](#multi-arm-bandit-tests-to-find-the-winning-variant) such as multi-arm bandit testing using feature flags. ### Create a Feature Flag @@ -214,9 +208,17 @@ Here is an example of a payload that is returned from Google Analytics that incl By enabling impression data for your feature flag and listening to events within your application code, you can leverage this data flowing to your integrated analytics tools to make informed decisions faster and adjust your strategies based on real user behavior. +### Rollout the Winning Variant to All Users + +After you have implemented your A/B test and measured the performance of a feature to a subset of users, you can decide which variant is the most optimal experience to roll out to all users in production. + +Unleash gives you control over which environments you release your feature to, when you release the feature, and to whom. Every team's release strategy may vary, but the overarching goal of A/B testing is to select the most effective experience for users, whether it be a change in your app's UI, a web performance improvement, or backend optimizations. + +When rolling out the winning variant, your flag may already be on in your production environment. Adjust the rollout strategy configurations to release to 100% of your user base in the Unleash Admin. + ## A/B Testing with Enterprise Automation -Unleash provides the ability to automate your feature flags using [actions](/reference/actions) and [signals](/reference/signals). When running A/B tests, you can configure your projects to execute tasks in response to application metrics and thresholds you define. If an experimentation feature that targets a part of your user base logs errors, your actions can automatically disable the feature so your team is given the time to triage while still providing a seamless, alternative experience to users. In another case, you can use actions to modify the percentage of users targeted for variations of a feature based off users engaging with one variation more than the other. +With Unleash, you can automate your feature flags using [actions](/reference/actions) and [signals](/reference/signals). When running A/B tests, configure your projects to execute tasks in response to application metrics and thresholds you define. If an experimentation feature that targets a part of your user base logs errors, your actions can automatically disable the feature so your team is given the time to triage while still providing a seamless, alternative experience to users. In another case, you can use actions to modify the percentage of users targeted for variations of a feature based off users engaging with one variation more than the other. Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. From b31140696ef9a0d534dd2001b76b516ad608a12f Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Mon, 4 Nov 2024 16:02:08 -0500 Subject: [PATCH 16/22] post docusaurus resolve --- .../feature-flag-tutorials/use-cases/a-b-testing.md | 10 +--------- website/docs/reference/api/unleash/sidebar.js | 1 - 2 files changed, 1 insertion(+), 10 deletions(-) delete mode 100644 website/docs/reference/api/unleash/sidebar.js diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 73e474a4041f..e07a56228d63 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -7,15 +7,7 @@ Feature flags are a great way to run A/B or multivariate tests with minimal code ## How to Perform A/B Testing with Feature Flags -<<<<<<< HEAD -<<<<<<< HEAD -To follow along with this tutorial, you will need an Unleash instance. If you’d prefer to self-host Unleash, read our [Quickstart guide](/quickstart). Alternatively, if you’d like your project to be hosted by Unleash, go to [www.getunleash.io](https://www.getunleash.io/pricing?_gl=1*1ytmg93*_gcl_au*MTY3MTQxNjM4OS4xNzIxOTEwNTY5*_ga*OTkzMjI0MDMwLjE3MDYxNDc3ODM.*_ga_492KEZQRT8*MTcyNzQzNTQwOS4yMzcuMS4xNzI3NDM1NDExLjU4LjAuMA). -======= -To follow along with this tutorial, you will need access to an Unleash Instance. Head over to our [Quick Start documentation](/quickstart) for options, including running locally, or using an [Unleash SaaS instance](https://www.getunleash.io/pricing?). ->>>>>>> 471f6a231 (updating a/b testing doc: v2) -======= To follow along with this tutorial, you will need access to an Unleash Instance which will be used to create and manage feature flags. Head over to our [Quick Start documentation](/quickstart) for options, including running locally, or using an [Unleash SaaS instance](https://www.getunleash.io/pricing?). ->>>>>>> 7db166905 (update official getting started intro) With Unleash set up, you can use your application to talk to Unleash through one of our [SDKs](/reference/sdks). @@ -25,7 +17,7 @@ In this tutorial, you will learn how to set up and run an A/B test using feature 2. [Target specific users for each test variant](#target-users-for-ab-testing) 3. [Manage cross-session visibility of test variants](#manage-user-session-behavior) 4. [Connect feature flag impression data to conversion outcomes](#track-ab-testing-for-your-key-performance-metrics) -5. [Roll out the winning variant to all users](#multi-arm-bandit-tests-to-find-the-winning-variant) +5. [Roll out the winning variant to all users](#rollout-the-winning-variant-to-all-users) You will also learn about how to [automate advanced A/B testing strategies](#multi-arm-bandit-tests-to-find-the-winning-variant) such as multi-arm bandit testing using feature flags. diff --git a/website/docs/reference/api/unleash/sidebar.js b/website/docs/reference/api/unleash/sidebar.js deleted file mode 100644 index 268b0c0a1bfd..000000000000 --- a/website/docs/reference/api/unleash/sidebar.js +++ /dev/null @@ -1 +0,0 @@ -module.exports = [{"type":"doc","id":"reference/api/unleash/unleash-api"},{"type":"category","label":"Addons","link":{"type":"doc","id":"reference/api/unleash/addons"},"items":[{"type":"doc","id":"reference/api/unleash/get-addons","label":"Get all addons and providers","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/create-addon","label":"Create a new addon","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/get-addon","label":"Get a 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account.","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/update-service-account","label":"Update a service account.","className":"api-method put"},{"type":"doc","id":"reference/api/unleash/delete-service-account","label":"Delete a service account.","className":"api-method delete"},{"type":"doc","id":"reference/api/unleash/get-service-account-tokens","label":"List all tokens for a service account.","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/create-service-account-token","label":"Create a token for a service account.","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/delete-service-account-token","label":"Delete a token for a service account.","className":"api-method delete"}]},{"type":"category","label":"Strategies","link":{"type":"doc","id":"reference/api/unleash/strategies"},"items":[{"type":"doc","id":"reference/api/unleash/get-all-strategies","label":"Get all strategies","className":"api-method 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get"}]},{"type":"category","label":"Users","link":{"type":"doc","id":"reference/api/unleash/users"},"items":[{"type":"doc","id":"reference/api/unleash/get-groups","label":"Get a list of groups","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/create-group","label":"Create a new group","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/get-group","label":"Get a single group","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/update-group","label":"Update a group","className":"api-method put"},{"type":"doc","id":"reference/api/unleash/delete-group","label":"Delete a single group","className":"api-method delete"},{"type":"doc","id":"reference/api/unleash/get-roles","label":"Get a list of roles","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/create-role","label":"Create a new role","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/get-role-by-id","label":"Get a single role","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/update-role","label":"Update a role","className":"api-method put"},{"type":"doc","id":"reference/api/unleash/delete-role","label":"Delete a custom role","className":"api-method delete"},{"type":"doc","id":"reference/api/unleash/validate-role","label":"Validate a role","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/get-me","label":"Get your own user details","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/get-profile","label":"Get your own user profile","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/change-my-password","label":"Change your own password","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/validate-user-password","label":"Validate password for a user","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/change-user-password","label":"Change password for a user","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/reset-user-password","label":"Reset user password","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/get-users","label":"Get all users and [root roles](https://docs.getunleash.io/reference/rbac#predefined-roles)","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/create-user","label":"Create a new user","className":"api-method post"},{"type":"doc","id":"reference/api/unleash/search-users","label":"Search users","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/get-base-users-and-groups","label":"Get basic user and group information","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/get-admin-count","label":"Get total count of admin accounts","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/get-user","label":"Get user","className":"api-method get"},{"type":"doc","id":"reference/api/unleash/update-user","label":"Update a user","className":"api-method put"},{"type":"doc","id":"reference/api/unleash/delete-user","label":"Delete a user","className":"api-method delete"}]}]; \ No newline at end of file From 2ebf91bdc4fc848d017354ed33ed3ee4c7fc57a9 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 7 Nov 2024 07:08:11 -0500 Subject: [PATCH 17/22] update sentence about actions Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index e07a56228d63..5a0191b75a5b 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -230,7 +230,7 @@ To use Unleash to conduct a multi-arm bandit test, follow these steps: 2. Capture impression events in your application code 3. Funnel the impression events captured from your application code to an external analytics tool 4. Create signal endpoints in Unleash that will point to your external analytics tools -5. Create actions in Unleash that will react to your signals that were integrated +5. Create [actions](/reference/actions) in Unleash that can react to your signals Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. From 70b9a30cab66055fb9ce83a9b1b07d562269300a Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 7 Nov 2024 07:08:28 -0500 Subject: [PATCH 18/22] remove extra actions sentence Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 1 - 1 file changed, 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 5a0191b75a5b..2db866c6da6a 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -212,7 +212,6 @@ When rolling out the winning variant, your flag may already be on in your produc With Unleash, you can automate your feature flags using [actions](/reference/actions) and [signals](/reference/signals). When running A/B tests, configure your projects to execute tasks in response to application metrics and thresholds you define. If an experimentation feature that targets a part of your user base logs errors, your actions can automatically disable the feature so your team is given the time to triage while still providing a seamless, alternative experience to users. In another case, you can use actions to modify the percentage of users targeted for variations of a feature based off users engaging with one variation more than the other. -Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. ### Multi-arm Bandit Tests to Find the Winning Variant From 0e24b90c1e2435f955adb801ca3ce6be18ed89a8 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 7 Nov 2024 07:08:46 -0500 Subject: [PATCH 19/22] update signals step wording Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 2db866c6da6a..4836bc3ac877 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -228,7 +228,7 @@ To use Unleash to conduct a multi-arm bandit test, follow these steps: 1. Collect the necessary data from each variant’s performance by enabling impression data for your feature flag 2. Capture impression events in your application code 3. Funnel the impression events captured from your application code to an external analytics tool -4. Create signal endpoints in Unleash that will point to your external analytics tools +4. Create [signal endpoints](/reference/signals) in Unleash and point them to your external analytics tools 5. Create [actions](/reference/actions) in Unleash that can react to your signals Learn how to configure [actions](/reference/actions) and [signals](/reference/signals) from our documentation to get started. From f6255c68e9e8dddd019e1ea11d33d6d7eddaad54 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 7 Nov 2024 07:10:03 -0500 Subject: [PATCH 20/22] remove future tense in intro Co-authored-by: Melinda Fekete --- website/docs/feature-flag-tutorials/use-cases/a-b-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index 4836bc3ac877..bb2f6bde3801 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -7,7 +7,7 @@ Feature flags are a great way to run A/B or multivariate tests with minimal code ## How to Perform A/B Testing with Feature Flags -To follow along with this tutorial, you will need access to an Unleash Instance which will be used to create and manage feature flags. Head over to our [Quick Start documentation](/quickstart) for options, including running locally, or using an [Unleash SaaS instance](https://www.getunleash.io/pricing?). +To follow along with this tutorial, you need access to an Unleash instance to create and manage feature flags. Head over to our [Quick Start documentation](/quickstart) for options, including running locally or using an [Unleash SaaS instance](https://www.getunleash.io/pricing?). With Unleash set up, you can use your application to talk to Unleash through one of our [SDKs](/reference/sdks). From 963287c149f82b4750ce5957968556c4aa7147a6 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 7 Nov 2024 11:08:26 -0500 Subject: [PATCH 21/22] improve wording --- .../feature-flag-tutorials/use-cases/a-b-testing.md | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index bb2f6bde3801..f4a4eabb7fdc 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -29,19 +29,15 @@ In the Unleash Admin UI, open a project and click **New feature flag**. ![Create a new feature flag in the Unleash Admin UI.](/img/use-case-new-flag.png) -Next, you will create a feature flag on the platform and turn it on for your app. +Next, you will create a feature flag and turn it on. -Feature flags can be used for different purposes and we consider experimentation important enough to have its own flag type. Experimentation flags have a lifetime expectancy suited for running an experiment and gathering enough data to know whether the experiment was a success or not. - -The feature flag we are creating is considered an Experiment flag type. - -Read our docs on [Projects](/reference/projects) to learn more about how to configure and manage them for your team/organization. A description of the flag can help properly identify its specific purposes. However, this field is optional. +Feature flags can be used for different purposes and we consider experimentation important enough to have its own flag type. Experimentation flags have a lifetime expectancy suited for running an experiment and gathering enough data to know whether the experiment was a success or not. The feature flag we are creating is considered an Experiment flag type. ![Create a feature flag by filling out the form fields.](/img/use-case-create-experiment-flag.png) -Once you have completed the form, you can click ‘Create feature flag’. +Once you have completed the form, click **Create feature flag**. -Your new feature flag has been created and is ready to be used. Next, we will configure the A/B testing strategy for your new flag. +Your new feature flag is now ready to be used. Next, we will configure the A/B testing strategy for your flag. ### Target Users for A/B Testing From dc130e13a24005a7ffead9944a8aa04092b3ebd5 Mon Sep 17 00:00:00 2001 From: Nnenna Ndukwe Date: Thu, 7 Nov 2024 15:58:58 -0500 Subject: [PATCH 22/22] last tweaks --- .../docs/feature-flag-tutorials/use-cases/a-b-testing.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md index f4a4eabb7fdc..082fb956d023 100644 --- a/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md +++ b/website/docs/feature-flag-tutorials/use-cases/a-b-testing.md @@ -1,5 +1,5 @@ --- -title: A/B Testing using Feature Flags +title: How to do A/B Testing using Feature Flags slug: /feature-flag-tutorials/use-cases/a-b-testing --- @@ -83,8 +83,8 @@ A variant has four components that define it: - a name: This must be unique among the strategy's variants. You typically use the name to identify the variant in your client. - a weight: The [variant weight](/reference/strategy-variants#variant-weight) is the likelihood of any one user getting this specific variant. -- an optional payload: A variant can also have an associated [payload](/reference/strategy-variants#variant-payload) to deliver more data or context. -- a value: This describes the purpose of the variant. For example, "Most Read" or "Most Popular". +- an optional payload: A variant can also have an associated [payload](/reference/strategy-variants#variant-payload) to deliver more data or context. The type defines the data format of the payload and can be one of the following options: `string`, `json`, `csv`, or `number`. +- a value: specifies the payload data associated with the variant. Define this if you want to return a value other than `enabled`/`disabled`. It must correspond with the payload type. Open the gradual rollout strategy, select the **Variants** tab, and click **Add variant**. Enter a unique name for the variant. For the purpose of this tutorial, we’ve created 2 variants: `variantA` and `variantB`. In a real-world use case, we recommend more specific names to be comprehensible and relevant to the versions of the feature you’re referencing. Create additional variants if you need to test more versions. @@ -204,11 +204,12 @@ Unleash gives you control over which environments you release your feature to, w When rolling out the winning variant, your flag may already be on in your production environment. Adjust the rollout strategy configurations to release to 100% of your user base in the Unleash Admin. +After the flag has been available to 100% of users over time, archive the flag and clean up your codebase. + ## A/B Testing with Enterprise Automation With Unleash, you can automate your feature flags using [actions](/reference/actions) and [signals](/reference/signals). When running A/B tests, configure your projects to execute tasks in response to application metrics and thresholds you define. If an experimentation feature that targets a part of your user base logs errors, your actions can automatically disable the feature so your team is given the time to triage while still providing a seamless, alternative experience to users. In another case, you can use actions to modify the percentage of users targeted for variations of a feature based off users engaging with one variation more than the other. - ### Multi-arm Bandit Tests to Find the Winning Variant When running complex multivariate tests with numerous combinations, automating the process of finding the best variation of a feature is the most optimal, cost-effective approach for organizations with a large user base. [Multi-arm bandit tests](https://en.wikipedia.org/wiki/Multi-armed_bandit) are a powerful technique used in A/B testing to allocate traffic to different versions of a feature or application in a way that maximizes the desired outcome, such as conversion rate or click-through rate. This approach offers several advantages over traditional A/B testing and is a viable solution for large enterprise teams.

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