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Effects deprecation

Spark AR regularly updates to ensure an optimal user experience for effects. As a result of these changes, stored effects are often deprecated if you've created them in older versions of Spark AR Studio. These updates also affect effects that you've built on older versions.

Spark AR emails you within 30-days and informs you whether your effects need to be updated. The status of your effect is also visible in the Spark AR hub, which clearly specifies which of your effects require an update. It's important to ensure that all of your effects are relatively current with the latest version of Spark AR to ensure they operate efficiently.

When possible, update your effect rather than create a new one. The process of updating allows you to maintain audience statistics. It also allows users who saved the effect to their carousel to continue to access it rather than locate it again. Lastly, updates preserve and maintain the metrics that belong to that particular effect.

You can update your effects through Spark AR Hub but not directly through the Spark AR publishing menu. When you decide whether to publish a new effect or update an existing one, confirm that your effect meets all of the platform requirements within Spark AR.

Example of notification for effect that requires an update

Not all effects will need to be updated, especially if you developed the effect for any fixed period of time or campaign. At the start of a project, discuss the conditions that would require an update with your clients or partners. Spark AR and its complementary platforms update their software frequently, and it's impossible to predict when those changes occur. It's therefore important to define a scope and the guidelines for updates.

If your effect is complex, it may be better to use the Patch Editor to reduce friction during future updates. Spark AR automatically updates effects, which tends to be more successful when you use the Patch Editor to build an effect rather than script it.

There are many ways to update a Spark AR effect. You can do it within Spark AR Studio or do it directly in Spark AR Hub. The decision rests on personal preference. The action is still the same. You replace the project file that's currently live with a more current version, which you can do automatically in Spark AR or the Spark AR Hub.

Updating an effect within Spark AR

Design play and user feedback

A client or partner may ask for an effect that runs for a specific campaign to be evergreen. For example, imagine if a client asked for an effect specifically for a holiday campaign. After the season ends, they may want to update the effect so it can remain on their profile. In that situation, they may request modifications or change assets that may be necessary to maintain or update the effect.

As a publishing developer, it's good practice to also implement user feedback into your effects. Users may find a part of your effect difficult to understand or they may prefer one aspect over another. To create a more positive experience for your users and clients, consider user feedback when you implement updates.

Maintaining version control

Version control in the development process is important, so it's crucial to maintain copies of all stages of development. Save each stage starting at the beginning of development, rather than later when patches may no longer be accessible. To maintain efficiency, regularly save your patch graphs and scripting and copies of milestones in Spark AR throughout the development, even if the purpose is simply to revert changes or ensure the compatibility.

Many users often forget that they may need to update an effect in the future, so be mindful of that fact during the development process.

Key takeaways

  • Before you start a project, be transparent about your updates process with the client.
  • Remember that every effect is an ongoing process even after you press Submit. As a developer, it's good practice to implement the feedback you receive into your development.
  • It's more efficient to update effects than creating new one, because you can maintain the same Effect ID and metrics.