Identify conversion drivers in your funnel analyses

Knowing which events lead to conversions and which events don't is a crucial part of any analytics program. With Amplitude, you can also conduct deeper analyses and learn why users convert or churn after a specific event, with conversion drivers.

Use this feature to understand which behaviors drive key outcomes in your customer journey. To help you do that, Amplitude provides several relevant metrics in each conversion driver analysis:

• A correlation score.
• Behavior frequency.
• Percentage of users engaging in that behavior.
• Overall time to convert when a user engages in that behavior.

These metrics help clarify the frequency of different user actions, and whether they help or impede conversion.

Before you begin

• If you haven't already, familiarize yourself with the Funnel Analysis chart.
• Always keep in mind that correlation doesn't equal causation.
• This feature only works for funnel charts set up for the conversion metric, with the order of events set to "this order".

For a more advanced look at funnel analysis, refer to the funnel analysis interpretation guide.

Analyze events performed between funnel steps

A conversion drivers analysis begins with a simple, two-step funnel. Step one should be the starting event—for example, Search Song or Video in a music app—while step two should be the conversion event you're interested in, like Purchase Song or Video. Amplitude then automatically sorts through, aggregates, and analyzes all events that occur for each user between these two steps to identify which user actions correlate most strongly with that outcome.

To start a conversion drivers analysis, follow these steps:

1. From within a funnel analysis chart, find the step you want to examine as a conversion event. It can be any step after the initial event in the funnel. This opens the Microscope.
2. From the Microscope, click Explore Conversion Drivers. This opens the conversion drivers panel.

The conversion drivers panel has two sections. The step controller lets you choose the beginning and ending steps for your conversion driver analysis. You can change these by clicking on them and selecting the events you want.

This section also displays the conversion and drop-off numbers for the steps you selected, in terms of both unique users and a percentage of users.

Below the step controller is the events table. This lists all the events users performed between the two selected steps. At the top of the table, you can choose to look at the event list either for users who converted, or for users who dropped off.

The events table shows four relevant metrics for each event listed:

• Correlation Score: Correlation means there's a relationship between two things. In this context, the correlation column quantifies the relationship between the event in question and conversion (or drop-off), depending on which tab you selected (Converted or Dropped Off). The higher the score, the stronger the relationship.
• Frequency: The average number of times users fired a given event between the two selected funnel steps.
• % Who Did Event: The percentage (and absolute numbers) of users in the selected cohort who fired a given event.
• Time Between Steps: How long it took users who fired a given event to convert between the two selected funnel steps.

How Amplitude identifies events to include in a conversion drivers analysis

For users who convert, Amplitude looks at the events performed between the timestamps of the two selected funnel steps. For users who churn, Amplitude looks at the timestamps of the first selected funnel step, and their entry into the funnel plus the conversion window.

Imagine a funnel defined as A --> B --> C, and you want to investigate drivers of conversion at step C. The following table shows the time periods analyzed for each set of users, where t() represents the timestamp of the event performed:

Understand the correlation score

Correlation is a measure (ranging from -1 to 1) of how two variables relate to each other. In a conversion drivers analysis, the variables for each user are:

• Whether the user performed the selected event.
• Whether the user was in the cohort you selected (converted or dropped off).

Click View Correlation data for a detailed confusion matrix (also known as a prediction summary). This matrix shows the count and percentage of users in your base cohort that constitute:

• True Positives (TP, top left of matrix): Converted users predicted to perform the event.
• False Positives (FP, top right): Dropped-off users predicted to perform the event.
• False Negatives (FN, bottom left): Converted users predicted not to perform the event.
• True Negatives (TN, bottom right): Dropped-off users predicted not to perform the event.

You might have heard of different variations and definitions of correlation, including Matthews correlation, Pearson correlation, phi coefficient, and R-value. In this case, all these definitions are equivalent because a conversion drivers analysis looks at pairs of binary random variables.

Remember, correlation isn't causation, so you must still test and verify hypotheses generated by a conversion drivers analysis in the real world.

Event properties and conversion drivers

When you look at combinations of attributes on an event, you get a more accurate picture of what a user does in your product, which leads to a more layered and nuanced analysis.

To use this feature, open a funnel chart and follow these steps:

1. On the chart, find the event you want to analyze. Open the Microscope by clicking either the top section (for churn) or the bottom section (for conversions). Then click Explore Conversion Drivers. This opens the conversion drivers tab.

The conversion drivers tab lists every event included in your project, along with each event's correlation with either conversion or churn. In this example, the Add Content to Cart event correlates very highly (+0.97) with conversion on the Purchase Song or Video event.

2. Locate the event you want. Below the event name, click Expand by Property.
3. Click the Select property … button and click the property you want to analyze.

In this example, the goal is to find out which genres customers most frequently add to their carts and then purchase—remember, this analysis looks at users who converted on Purchase Song or Video. Here, pop is the most popular genre, with a correlation of +0.41.

Share the report

When you find a valuable insight using conversion drivers, you can share it with a teammate:

1. Click Share.
2. Click Copy Chart Link to copy the chart's unique URL to your clipboard, then send your analysis to others.