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First Session Completion Rate

Definition

First Session Completion Rate measures the percentage of new users who complete a defined onboarding or usage flow during their first session. It helps track early-stage friction and product clarity.

Description

First Session Completion Rate is a key indicator of onboarding usability and early experience quality, reflecting how many users complete critical first-session steps like setup, tutorials, or guided tours.

The relevance and interpretation of this metric shift depending on the model or product:

  • In SaaS, it may track onboarding checklist completion or creating a first project
  • In consumer apps, it could mean account creation, tutorial progression, or initial personalization
  • In freemium models, it marks whether users reach the "aha moment" during the first interaction

A rising completion rate signals clear guidance and intuitive UX, while a low rate suggests friction, overwhelm, or confusion in first use. By segmenting by persona, entry point, or acquisition source, you uncover insights to refine onboarding flows, remove friction, and accelerate time to value.

First Session Completion Rate informs:

  • Strategic decisions, like onboarding design and activation milestone definition
  • Tactical actions, such as in-app nudges, progress bars, or welcome emails
  • Operational improvements, including tutorial sequencing or checklist UX
  • Cross-functional alignment, connecting product, growth, and lifecycle teams to drive activation and retention

Key Drivers

These are the main factors that directly impact the metric. Understanding these lets you know what levers you can pull to improve the outcome

  • Flow Length and Cognitive Load: If onboarding has too many steps or unclear value, users abandon early.
  • In-Session Guidance and Momentum: Smart nudges and visual cues help users stay on track and complete what they started.
  • Device and Performance Friction: Long load times or mobile-unfriendly designs cause early exits before success is reached.

Improvement Tactics & Quick Wins

Actionable ideas to optimize this KPI, from fast, low-effort wins to strategic initiatives that drive measurable impact.

  • If completion rate is low, shorten the onboarding flow and break it into logical chunks.
  • Add real-time progress bars (“Step 2 of 3 – You’re almost there!”) to keep users moving.
  • Run a test with a “pause and return later” option vs. forcing all steps in one go.
  • Refine empty states and tooltips to focus on next-best actions, not just orientation.
  • Partner with product analytics to identify drop-off points and friction hotspots.

  • Required Datapoints to calculate the metric

    • New Users or Sessions Started
    • Sessions Where All Onboarding Steps Completed
    • Session Tracking & Milestones

  • Example to show how the metric is derived

    • 1,000 new sessions
    • 780 completed onboarding
    • Formula: 780 ÷ 1,000 = 78% First Session Completion Rate

Formula

Formula

\[ \mathrm{First\ Session\ Completion\ Rate} = \left( \frac{\mathrm{Completed\ Sessions}}{\mathrm{Total\ New\ Sessions}} \right) \times 100 \]

Data Model Definition

How this KPI is structured in Cube.js, including its key measures, dimensions, and calculation logic for consistent reporting.

cube('UserSessions', {
  sql: `SELECT * FROM user_sessions`,

  measures: {
    newUsers: {
      sql: `new_user`,
      type: 'count',
      title: 'New Users',
      description: 'Count of new users who started a session.'
    },
    completedOnboarding: {
      sql: `completed_onboarding`,
      type: 'count',
      title: 'Completed Onboarding',
      description: 'Count of sessions where all onboarding steps were completed.'
    },
    firstSessionCompletionRate: {
      sql: `completed_onboarding / new_user`,
      type: 'number',
      format: 'percent',
      title: 'First Session Completion Rate',
      description: 'Percentage of new users who complete onboarding during their first session.'
    }
  },

  dimensions: {
    sessionId: {
      sql: `session_id`,
      type: 'string',
      primaryKey: true,
      title: 'Session ID',
      description: 'Unique identifier for each session.'
    },
    userId: {
      sql: `user_id`,
      type: 'string',
      title: 'User ID',
      description: 'Unique identifier for each user.'
    },
    sessionStartTime: {
      sql: `session_start_time`,
      type: 'time',
      title: 'Session Start Time',
      description: 'Timestamp when the session started.'
    }
  }
});

Note: This is a reference implementation and should be used as a starting point. You’ll need to adapt it to match your own data model and schema

Positive & Negative Influences

  • Negative influences

    Factors that drive the metric in an undesirable direction, often signaling risk or decline.

    • Flow Length and Cognitive Load: Long or complex onboarding processes increase abandonment rates, reducing the First Session Completion Rate.
    • Device and Performance Friction: Poor performance, such as long load times or non-responsive designs, leads to early exits, negatively impacting the First Session Completion Rate.
    • User Interface Complexity: A cluttered or confusing interface can overwhelm users, causing them to leave before completing the session.
    • Lack of Personalization: Generic onboarding experiences that do not cater to individual user needs can result in disengagement and lower completion rates.
    • Inadequate Error Handling: Frequent or poorly managed errors during the first session can frustrate users, leading to session abandonment.

  • Positive influences

    Factors that push the metric in a favorable direction, supporting growth or improvement.

    • In-Session Guidance and Momentum: Effective use of nudges and visual cues keeps users engaged and increases the likelihood of completing the first session.
    • Clear Value Proposition: Communicating the benefits and value of the product early in the session encourages users to complete the onboarding process.
    • Responsive Design: Ensuring the product is mobile-friendly and performs well across devices enhances user experience and completion rates.
    • Personalized Onboarding: Tailoring the onboarding process to individual user needs and preferences can increase engagement and completion rates.
    • Effective Feedback Mechanisms: Providing users with immediate feedback and support during the session can help them overcome obstacles and complete the process.

Involved Roles & Activities

Funnel Stage & Type

  • AAARRR Funnel Stage

    This KPI is associated with the following stages in the AAARRR (Pirate Metrics) funnel:

    Activation

  • Type

    This KPI is classified as a Lagging Indicator. It reflects the results of past actions or behaviors and is used to validate performance or assess the impact of previous strategies.

Supporting Leading & Lagging Metrics

  • Leading

    These leading indicators influence this KPI and act as early signals that forecast future changes in this KPI.

    • Onboarding Completion Rate: High onboarding completion directly forecasts a higher First Session Completion Rate, as users who finish onboarding are most likely to complete their first session flow. Monitoring this metric gives an early signal of potential friction in the onboarding funnel.
    • Drop-Off Rate: Elevated drop-off rates in onboarding or early product flows act as a precursor to lower First Session Completion Rates. Tracking drop-off identifies specific stages where users abandon the process, enabling proactive improvements.
    • Activation Rate: A strong Activation Rate indicates users are quickly reaching value, which typically translates to higher First Session Completion Rates. It acts as an upstream indicator of onboarding and product clarity.
    • Task Success Rate: High early-stage task success rates signal users are able to complete key actions, directly influencing whether they complete the first session flow. Poor rates indicate friction before lagging completion metrics are impacted.
    • Immediate Time to Value: Shorter times to initial value in the first session predict higher completion rates, as users recognize product benefits early. This metric anticipates downstream completion performance and guides onboarding optimization.

  • Lagging

    These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.

    • Onboarding Drop-off Rate: High onboarding drop-off rates confirm and quantify friction points that result in lower First Session Completion Rates, helping to pinpoint exactly where users are abandoning the process after the fact.
    • Signup Completion Rate: Signup Completion Rate amplifies First Session Completion Rate by explaining how many users make it through the very first funnel step. Gaps between signup and session completion clarify where user loss is occurring.
    • Percent Completing Key Activation Tasks: This metric quantifies how many users accomplish core actions during onboarding, further explaining the drivers behind First Session Completion Rate performance.
    • Activation Conversion Rate: Activation Conversion Rate measures how many users reach activation after starting onboarding, offering a downstream view on the progression from initial engagement to full session completion.
    • Engagement Depth (First 3 Sessions): This metric provides insight into how deeply users engage after their first session. A low First Session Completion Rate often correlates with shallow engagement in early sessions, confirming broader onboarding challenges.