Planning a Predictive Goal

For your predictive goals to be as effective as they can be, there are a few things to address before you build them.

# In this article

# Understand your objective

When you create a predictive goal, it's important to be clear about what you want to learn from it. Questions you might consider include:

• Do you want to discover whether users are performing specific tasks, or general tasks?

  For example, maybe you want to find users who are likely to make a specific type of purchase in the next month (like the purchase of a discounted item), or maybe you're interested in more general actions (like finding users who'd make any kind of purchase).

• Are you looking for potential trends?

  Because predictive goals don't have finite start and stop dates (they "roll" from one refresh to the next), a single goal can tell you how many users are likely to perform an action within a 30-day period of time, starting when you create a goal, and for the same period of time after subsequent weekly refreshes. This can help you track, for example, how many users might upgrade to a premium account in a one month period.

• Do you want to evaluate brand engagement based on unique custom events?

  If you're already familiar with Brand Affinity™, you can think of this as the next step in measuring users' loyalty to your brand. Instead of assessing engagement based on historical clicks and opens, use Predictive Goals to see who's likely to engage based on your unique events.

  For example, if building a sense of community is important to your brand, you might be particularly interested to discover who's likely to perform actions represented by custom events like BlogViewed or ReferFriend.

# Verify your data for Predictive Goals

Before you build a predictive goal, verify that you have enough and the right type of data.

# Amount of data

At a minimum, your Iterable project should have:

• Three to six months of historical data. The amount of data required will vary by industry vertical, data quality, and the goals you're considering. If you have questions, reach out to your customer success manager.

• 100,000 unique users

• 100,000 event and user profile field occurrences across users, with at least 20—30 active events that have been frequently updated across all users in the past month.

# Type of data

The criteria for a predictive goal can include user profile fields, system events, custom events, and purchase events.

• Use user profile fields to track information that defines a user, in some way. For example, you could use them to query the types of accounts users have.

• Use Iterable system events and your unique custom events to track actions users take. For example, you could query when users click an email, or when they perform an action that's specific to your business (maybe a travel site would track booking types, with custom events like BookingHotel, BookingAir, and BookingAuto).

• Use Iterable Purchase events to query a dollar value and the number of purchase occurrences.

For more information about how Predictive Goals uses the data you select, talk with your customer success manager.

# Select meaningful data points

Once you've verified that you have the right amount and type of data for effective predictions, consider how your data maps to the business goal you want to track.

# Example goal: Predict churn

The approach you take to anticipate which of your customers might stop using your product or service depends on the user properties and actions you track.

• If your project tracks user engagement through user profile information (like account status–either active, inactive, or churned), a goal that strives to identify users who may churn could include criteria with a user profile field like this:

  AccountStatus = inactive

• Or, if your project tracks this type of information through actions users perform, your goal criteria might include custom events like this, where a user has created an account but hasn't downloaded your app (so may not be as engaged as you would like):

  AccountCreated = 1AND DownloadApp ﹤ 1

Either path helps you find the audience you want to reach when trying to reduce churn.

# Example goal: Increase subscriptions

If you’re focused on increasing the number of subscribers to your service, and your project tracks users who subscribe, you might find people who are likely to subscribe in the future with goal criteria like this:

• If a user profile field tracks users who subscribe:

  Subscribed = true

  NOTE

  The user profile field Subscribed = true includes users in segmentation who've already subscribed. If your messaging will encourage users to subscribe, exclude them from the selected segment, so they don't receive messaging that encourages an action they've already taken. See Exclude users from segmentation.

• If a custom event is triggered when a user clicks a Subscribe Now button from their trial:

  ClickSubscribe ≥ 1

When your prediction is ready, select the users with the highest likelihood of conversion and send them a limited-time offer to encourage them to upgrade soon.

# Example goal: Increase app downloads

If you're looking to increase the number of users who download your app, and your project tracks app downloads, you could find users who are likely to download your app in the next month like this:

• If a user profile field tracks users who have your mobile app:

  HasMobileApp = true

• If, instead, a custom event is triggered when a user clicks a Download App button:

  DownloadApp ≥ 1

With either criteria, choose two segments for messaging designed to help increase downloads of your app.

• Users who are more likely to download can receive a promotional offer that encourages them to install within the next week so you keep them on the trajectory they're already on.

• Users who are less likely to download can receive messaging that considers why they’re less likely to do so. For example, consider whether these users aren’t aware of the benefits of using the app, or perhaps they have an alternate preferred channel (maybe they don’t use mobile).

  To address both scenarios, you could send this segment a campaign that highlights the benefits of the app, but also provides an option to specify their preferred method of communication.

# Next steps

• Learn how to create a new predictive goal. See Building a predictive goal.

• See how a fictional company built predictive goals to meet their needs, check out Use case: Reward loyalty with memorable experiences.