Intelligent Rollouts

Maximize conversions by automatically optimizing message campaign performance in real time. AXP

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About Intelligent Rollouts

Intelligent Rollouts identify and distribute your best-performing message variant automatically using real-time engagement data. This helps maximize conversions while the campaign is active, eliminates the manual effort of A/B testing, and minimizes exposure to less effective variants. They are powered by reinforcement learning (multi-armed bandit) to dynamically optimize for the winning variant.

They are great for time-sensitive campaigns:

  • Optimize flash sales — Test offers during a 12-hour sale, such as “20% Off” against another promotion, and let Airship shift more of the remaining audience to the offer driving more clicks.
  • Tune newsletter subject lines — Send a weekly newsletter over a 24-hour window, compare subject lines, and automatically deliver the better-performing version to more subscribers.
  • Maximize holiday campaign engagement — Compare messages such as “Gifts for Her” and “Gifts for Him,” then increase delivery to the variant performing best with your general audience.

When running a message experiment and a Holdout ExperimentMeasures the effects of excluding a group of audience members from all messages or messages with specific campaign categories. You can compare the performance of the two audience groups in reports for selected goal events. simultaneously, Airship prevents holdout group users from being included in the message experiment. This eliminates potentially skewed data in cases where there are overlapping experimentation audiences. It also ensures that the most critical experiments maintain integrity.

Supported channels and measuring engagement

These channels and message types are supported for Intelligent Rollouts:

  • App — Push notifications, in-app messages, and Message Center
  • Web
  • Email
  • SMS
  • Open channel

Airship uses the following engagement signals to determine the top-performing variant:

  • Push — Direct clicks on a push message
  • Message Center — Message reads
  • Email — Clicks on any link in the email, excluding unsubscribe links
  • SMS — Clicks on a link in the message

Because Airship uses email and SMS link clicks to measure engagement, links are required for those message types to drive optimization.

Workflow

Set up an Intelligent Rollout in three steps:

  1. Create two or more message variants — Just like in the Message composer, for each variant, select channels, configure content for each channel, and set up delivery.

  2. Allocate an audience — You can designate all users as eligible for the experiment or target specific users. To limit your audience, set the percentage that can participate.

  3. Schedule timing — Set a send window between 6 and 24 hours, then choose whether to start immediately or at a specific date and time. The window gives Airship time to optimize delivery while the campaign is active.

After setup, you can start the experiment and review its results.

Create an Intelligent Rollout

First, select the Create dropdown menu (), then Intelligent Rollout. Or you can start from your list of all message experiments by going to Experiments, then Message Experiments, selecting Add experiment, and then selecting the same option.

Next, select the experiment name and change it to something descriptive, then select the check mark to save it.

To finish setup, add message variants, determine the audience, and configure the schedule. You can configure them in any order.

Add message variants

You can add up to 26 variants:

  1. Select Add variant. After completing a step, select the next step in the header to move on.

  2. For Channels:

    First, select a Channel CoordinationA group of strategies for targeting users where they are most likely to receive your message. strategy:

    • Fan Out targets a Named User on all the channels they are opted in to, maximizing the chances they receive your message.
    • Last Active targets a Named User on the opted-in channel they used most recently.
    • Priority Channel targets a Named User on the first channel they are opted in to, in the priority order you set.

    Then, enable the channel types to include in your audience. For Mobile Apps, also select from the available platforms. For Priority Channel, also drag the channel types into priority order.

    Note

    For projects using the channel-level segmentation system, instead of Channel Coordination, enable the channels you want to send the message to.

    Use Channel conditions to filter which channels are included in the audience. A channel must meet the conditions to remain in the audience.

    For example, if your audience includes users with app, email, and SMS channels, and you set a channel condition requiring membership in an email Subscription List:

    • Only email channels that meet that condition would remain in the audience.
    • All app and SMS channels would be excluded.

    To set channel conditions, use the same process as when building a segmentA reusable audience group you create by selecting unique or shared user data.. You can use the following data in your conditions:

    Selected Lifecycle, Subscription, and Uploaded Lists must contain Channel IDs or Named Users as the identifier, not a mix of the two.

    Note

    Setting channel conditions is not supported for projects using the channel-level segmentation system.

    Under Localization, enable the option if you want to provide different content to app and web users depending on their language and country.

  3. For Content, configure the message content per enabled channel. See the Content documentation per message type, Content options, and Localization.

  4. For Delivery, configure the options. See Message delivery.

  5. In the Review step, review the device preview and message summary:

    • Use the arrows to page through the various previews. The channel and display type dynamically update in the dropdown menu above. You can also select a preview directly from the menu.
    • If you want to make changes, select the associated step in the header, make your changes, then return to Review.
    • Select Send Test to send a test message to verify its appearance and behavior on each configured channel. The message is sent to your selected recipients immediately, and it appears as a test in Messages Overview. Follow the same steps as in the Review step for the Message composer.

    When your review is complete, select Save Variant.

To add another variant from scratch, select Add variant. To duplicate an existing variant, select the more menu icon () at the end of a row and select Copy to variant.

Set the audience

After creating an experiment, select Audience and then set it up:

  1. Choose and configure users:
    OptionDescriptionSteps
    All UsersThis option makes the experiment available to a percentage of your total audience.n/a
    Target Specific UsersThis option makes the experiment available to a percentage of users who meet specified conditions.Select and configure one or more conditions. Use the same process as when building a segmentA reusable audience group you create by selecting unique or shared user data..
  2. (Optional) Under Total audience allocation, limit the selected audience to your specified percentage.
  3. Select Save.

Set the schedule

Select Schedule to configure the send window and timing:

  1. Set a send window between 6 and 24 hours. Longer windows give Airship more time to learn and optimize delivery. Choose a shorter window when your message is time-sensitive.
  2. Choose whether to start immediately or at a specific date and time.
  3. Select Save.

Start the experiment

Once you’ve completed the setup, select Start and confirm. Airship then distributes variants automatically during the send window according to live engagement.

You’ll also see an Overview section added to your experiment. It contains the same Variant Allocation Over Time chart as in Results, plus a summary of the schedule and audience.

View results

After starting the experiment, see how it performed. Use experiment- and message-level reports to evaluate engagement, variant distribution during the experiment window, and strategies for improving future campaigns.

To access results, go to Experiments, then Message Experiments, select the more menu icon () for an experiment in the list, then View results. You can also select the name of an experiment from the list and then go to Results.

Note

Engagement data is sent to Airship as soon as it becomes available. Data may be delayed due to connectivity issues with a user’s carrier, Wi-Fi, power, etc. Wait at least 12 to 24 hours before acting on the data to allow for potential lags.

Performance

The Performance view is the initial state of experiment results. Its first component is a summary explaining what happened during the experiment, including whether Airship identified a winner or the data was inconclusive. For completed experiments, final results reflect the total optimized distribution across all variants.

Following the summary, a table lists this data for each variant:

DataDescription
Probability To Be BestAlso known as PTBB. This metric represents the likelihood that the variant is the top-performing option. A higher value indicates a greater chance of success. A value of 95% or above indicates high statistical confidence that the variant will outperform the others.
Expected LossThe potential risk of choosing one variant over another. It represents the average performance you might lose if the selected variant is not actually the best option. A value below 5% indicates minimal risk, meaning that even if the variant is not the absolute best, the performance difference is negligible. Values of 10% and above suggest greater potential risk, indicating more significant differences between the chosen variant and what the best option would be if more data were collected.
Conversion rateThe percentage of users who engaged with the variant, calculated as (conversion count / audience) x 100. The comparison to the top-performing variant indicates how much lower the conversion rate is for this variant relative to the best option, where the top variant shows a difference of 0%.
Conversion countThe total number of users who engaged with this variant group during the experiment
AudienceThe total number and percentage of contacts assigned to the variant based on audience distribution.

Select a variant name to open its message report.

Below the table, the following charts visualize variant performance:

  • Probability of Being the Best Variant — This chart shows the probability that each variant is the top performer in your experiment. Taller bars indicate a higher likelihood of success, and a variant typically needs to reach 95% or higher to be declared the winner. If the bars are roughly the same height, the variants are performing similarly.

  • Conversion Lift Compared to Others — This chart shows the potential uplift of each variant compared to the top performer, helping you distinguish meaningful improvements from minor fluctuations.

    • 0% uplift line — This line represents no difference between variants. Curves to the right indicate improvement. Curves to the left indicate decline.
    • Distribution spread — A narrow, tall curve indicates high confidence, while a wider curve suggests more uncertainty.
    • Bulk mass — If the majority of a variant’s curve lies above zero, the variant is highly likely to outperform the others.
  • Likelihood of Variant Success — This chart shows the estimated conversion rate for each variant as a curve.

    • Height — The higher the peak, the more likely that conversion rate represents the variant’s true performance.
    • Width — A narrow curve indicates high confidence, while a wider curve suggests more uncertainty.
    • Overlap — Significant overlap means the variants are performing similarly. Minimal overlap indicates a clearer performance gap between them.

By channel

Select By Channel to see how variant performance differed across each channel in the experiment. Select a variant name to open its message report.

Export results

Export options for experiment results vary by view:

Statistical methods

Airship analyzes Intelligent Rollout results using Bayesian statistics, measuring confidence in each variant’s success while accounting for uncertainty in the data. Rather than relying on a fixed confidence threshold only after the experiment ends, Bayesian methods allow for continuously updating the understanding of variant performance as engagement data comes in.

Airship estimates probability distributions for each variant’s performance. These distributions help calculate how likely each variant is to be the best. A Beta(1,1) prior is used to create the distributions, starting with a neutral assumption and letting the data drive the results.

Instead of only comparing variants to a single control, Airship evaluates each variant against all other variants. This gives a more complete picture of which variant performs best. For Intelligent Rollouts, these methods also inform how Airship shifts traffic to stronger-performing variants while the experiment is active.

Benefits of using Bayesian methods:

  • Transparent decision-making — You can see whether a variant is performing better than others and the confidence in that result.
  • More than just statistical significance — Instead of a pass/fail outcome, Bayesian methods give you probability-based confidence in the results.
  • Flexibility — You can decide how much certainty you need before applying what you learned to future campaigns.

Real-Time Data Streaming events

Messages used as variants include experiment information in Real-Time Data StreamingA service that delivers user-level events in real time to your backend or third-party systems using the Data Streaming API. events.

The Send event includes an experiments object with the experiment details, including experiment_id, type, and variant_id. The experiment_id also appears in the body object.

Managing Intelligent Rollouts

Go to Experiments, then Message Experiments to view and manage your message A/B tests. You can filter the list by experiment type and archive status. Each experiment is listed by name with its status and the date it was last modified. Your last modified experiment is listed first, and you can search by experiment name.

You can perform the following actions from the list:

OptionDescriptionSteps
ViewOpen the experiment to access its message variants, audience configuration, schedule, and results.Select its name, or select its more menu icon () and then Edit.
DuplicateMake a draft copy with its message variants, audience configuration, and schedule.Select its more menu icon () and then Duplicate.
View resultsOpen the experiment’s performance reports.Select its more menu icon () and then View results.
ArchiveStops and archives the experiment. Archiving a started/active test also cancels its undelivered messages.Select an experiment’s more menu icon () and then Archive.

Editing message variants, audience, and schedule

You can edit variants, audience settings, and schedule settings for any experiment that has not yet been started. After opening it from the Message Experiments list, select the more menu icon () for a variant and select an option:

OptionDescription
EditModify the variant’s channels, content, or delivery settings.
DuplicateCreate a copy of the variant as a starting point for a new variant.
DeleteRemove the variant from the experiment.

To modify the audience, select Audience and adjust targeting or allocation settings. See Set the audience for configuration details.

To modify the schedule, select Schedule and adjust the send window or timing.