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Advanced Funnel Options

Advanced funnel options let you answer deeper questions about your funnels. Instead of just seeing who converted, you can explore how quickly users tend to move between key steps and how often they perform certain actions before moving forward in the funnel.

Time to convert - Unique Users: This option distributes the time users take to complete the specified steps. For a single user, MoEngage considers the best time to convert (least time) between the specified steps. This analysis can be performed between two defined steps:
- Auto: This displays the time taken for each percentile of users who completed the selected steps. For instance, it shows how much time is required for 50% of the users to convert. The X-axis represents user percentiles (from 1 to 100), while the Y-axis indicates the corresponding time to convert.
- Custom: Using custom distribution, you can customize time buckets. This will provide the number of users converted for the selected step within the time bucket. You can analyze a maximum of 25 buckets. Distribution buckets include the lower boundary point and exclude the upper boundary point.
Time to convert - All Occurrences: This option provides the distribution of time taken by all occurrences of conversion for the defined steps. For a single user, MoEngage considers the best conversion time out of all the conversions between the defined steps if the user has completed the steps multiple times. You can perform this analysis between two defined steps. This funnel type has Distribution bucketing options similar to those of Time to convert - Unique Users.
Frequency - Unique Users: This option provides the distribution of the number of times (frequency) a step has been performed before the succeeding (next) step. For a single user, MoEngage considers the lowest frequency count for the analysis. This analysis can be performed between two consecutive defined steps:
- Auto: This provides the frequency of performing a step before the next step for each percentile of users. For example, how many times users have viewed the product before purchasing it for 50% of the users. Here, the X-axis provides the user percentile (1 to 100), and the Y-axis provides the respective frequency count.
- Custom: Using custom distribution, you can customize the frequency buckets. This will provide the number of users for the selected frequency bucket. You can analyze a maximum of 25 frequency buckets in a single analysis. Distribution buckets include the lower boundary point and exclude the upper boundary point.
Frequency - All Occurrences: This option provides the distribution of the number of times (frequency) a step has been performed before the succeeding (next) step. For a single user, MoEngage considers all frequencies for the analysis. You can perform this analysis between two consecutive steps. This funnel type has Distribution bucketing options similar to those of Frequency - Unique Users.

When to Use Advanced Funnel Options

Standard funnel analysis illustrates who converted between steps and at what rate. Advanced Funnel Options go further, allowing you to explore the dynamics of how users progress through your funnels, specifically, how quickly they move and how often they perform steps before advancing.

Use these advanced options when your analysis requires understanding:

Conversion Velocity: You need to know how much time typically passes between key funnel steps.
Action Repetition: You want to understand how many times users perform a specific action before moving to the next step in the funnel.
Behavior Across Attempts: You need to differentiate between analyzing a user's first/fastest path versus analyzing all their attempts through the funnel steps.

Here’s how each specific option helps solve different analytical challenges:

Time to Convert - Unique Users

What it does: Measures and distributes the time taken for users to complete a sequence between two defined steps for the first time or their fastest time if they've done it multiple times. It offers Auto (percentile distribution) and Custom (user-defined time buckets) views.
When to use it:
- When you need to understand the typical speed of initial conversion between two key milestones.
- To measure the effectiveness of time-sensitive campaigns or promotions.
- To identify bottlenecks where users take an unusually long time on their first successful attempt.
- When focusing on the optimal or initial user journey between two points.

Example Use Cases

Some of the use cases that you can solve using this option:

Campaign Urgency: Analyze the time between Campaign Email Clicked and Purchase Completed to see if limited-time offers drive faster conversions (for example, using Custom buckets like 0-1 hr, 1-6 hrs, 6+ hrs). The Auto view can show the median time (50th percentile).
Onboarding Efficiency: Measure the time taken from Account Created to First Key Action Completed.
Feature Adoption Speed: Track how quickly users move from Feature Discovery Event to First Feature Use Event.

Time to Convert - All Occurrences

What it does: Measures and distributes the time taken for all occurrences of conversion between two defined steps, considering users might complete the sequence multiple times. It also offers Auto and Custom distribution.
When to use it:
- When users can repeat the funnel sequence, and you want to analyze the time dynamics across all their successful attempts.
- To understand conversion speed for recurring behaviors or processes.

Example Use Cases

Some of the use cases that you can solve using this option:

Repeat Purchase Velocity: Analyze the typical time between Added to Cart and Purchase Completed across all purchase journeys for repeat buyers.
Recurring Task Duration: Measure the time taken from Task Started to Task Completed for processes users might perform repeatedly (for example, submitting expense reports, completing lessons).

Frequency - Unique Users

What it does: Measures and distributes the number of times users perform a specific step before successfully moving to the next consecutive step for the first time (or the instance with the lowest frequency count). It offers Auto (percentile distribution) and Custom (user-defined frequency buckets) views.
When to use it:
- To understand how much hesitation, exploration, or repetition occurs before a user commits to the next step in their initial journey.
- To identify friction points where users repeat an action many times before proceeding.
- When focusing on the efficiency of the initial or most direct path between two consecutive steps.

Example Use Cases

Some of the use cases that you can solve using this option:

Product Consideration: Analyze how many times users perform Product Page Viewed before Add to Cart (lowest frequency) to understand initial browsing behavior.
Search Effectiveness: Measure the number of Search Performed events before a SearchResult Clicked event.
Form Completion: Track how many times Help Tooltip Viewed occurs before Form Field Completed for a complex field.

Frequency - All Occurrences

What it does: Measures and distributes how many times users perform a specific step before successfully moving to the next consecutive step, considering all instances where the user completes this transition. It also offers Auto and Custom distribution.
When to use it:
- When users can repeat a sequence of steps, you want to understand the repetition behavior across all their journeys through those steps.
- To analyze prerequisite actions or exploration behavior in recurring processes.

Example Use Cases

Some of the use cases that you can solve using this option:

Cross-sell/Upsell Exploration: Across all purchase journeys, how many times do users trigger View Recommended Product before Add to Cart?
Learning Patterns: For users completing multiple modules, how many times do they typically perform View Lesson Video before Complete Quiz across all modules?
Support Interaction: Analyze the frequency of View FAQ Article before Submit Support Ticket across all instances of users submitting tickets.

By leveraging these advanced funnel options, you gain deeper insights into user momentum and behavior within your funnels. This enables better optimization of conversion speed, identification of friction points, and a more nuanced understanding of user journeys.

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