Predictive Goals Overview

# In this article

# How Predictive Goals works

Predictive Goals analyzes your historical data to predict which users are likely to convert on your business goals in the future. Predictive Goals also provides insight into the events and properties that contribute most to a prediction, identifying those that may increase or decrease the likelihood of a certain outcome. These insights can help you connect customers with experiences that match their interests and encourage conversion, while promoting the outcomes you seek.

Predictive Goals bridges the gap between insights and actions.

Let’s say your business wants to connect customers with products they love; Predictive Goals can help you identify who’s likely to purchase luxury brands, so you can alert them to new arrivals. Or, if your business wants to mitigate churn, you can identify users who might disengage from your messaging, so you can reconnect with them before they do.

Use Predictive Goals to:

• Identify segments of users who are likely to convert on business goals that you want to optimize (like purchases and promotional clicks), or minimize (returns or unsubscribes), so you can send them personalized messaging. By sending a segment to a dynamic list, you can ensure that campaigns go to all of the contacts who match the segmentation query at send time.

• Identify which of your project's relevant user properties and first-party data (like purchase, system, and custom events) you want to increase or decrease in frequency to promote desired outcomes. For example, let's consider that you create a predictive goal to identify users who are likely to make multiple purchases a month. Predictive Goals uncovers that it's likely that these users will also complete OfferRedeemed events. To increase the likelihood that users will convert, you might increase the number of special offers you send to your customers.

• Generate conversion probability scores for use in journeys to direct how users interact with your brand. For example, users with strong probability scores might be assigned to a journey that recognizes brand loyalty, and those with low scores to one that incentivizes conversion with promotional offers.

# Requirements for valuable predictions

At a minimum, your Iterable project should have:

• Three to six months of historical data. The amount of data required varies by industry vertical, data quality, and the goals you're considering.
• 100,000 unique users.

The most valuable predictions:

• Use custom events or properties that represent unique business goals, not generic conversion metrics like email opens or clicks.
• Include at least 20–30 active events that have been frequently updated in the past month.
• Use goal criteria that's neither too broad nor too narrow.

For each goal, Predictive Goals looks at users who satisfy the full combination of conditions, not just the number of individual events or an aggregate total. Over the last 60 days, at least 1,000 users must meet your goal criteria within a 30-day lookback window on each day. If that count drops below 1,000 on any day, the goal may move to Needs Review, even when a project is large or appears to satisfy requirements.

When you define a goal:

• Optimize for a steady qualifying audience over time, not just a large one-time count.
• Treat Preview Users as an estimate—it doesn't guarantee the goal will pass validation.
• Prefer broader, outcome-oriented criteria, and use and conditions sparingly. Stacking several required conditions can shrink the qualifying audience more than each condition suggests on its own.

Predictive goals that apply to fewer than 1,000 users, or to almost all users in a project, don't provide a meaningful forecast. If a goal still looks broad enough but lands in Needs Review, work with Iterable to check whether project-level data readiness is affecting the goal.

# Keeping predictions current

Predictive Goals accounts for your ever-changing data landscape by refreshing predictions weekly to reflect the most recent user data.

# Terms you should know

These terms can help you understand your predictions.

# Want to learn more?

For more information about some of the topics in this article, check out this Iterable Academy course. Iterable Academy is open to everyone — you don't need to be an Iterable customer!

• Predictive Goals