Time to First Meeting¶

Definition¶

Time to First Meeting measures the average time between when a lead or user signs up (or enters your funnel) and when they attend their first scheduled meeting—such as a sales call, onboarding session, or demo. It helps track pipeline speed and engagement momentum.

Description¶

Time to First Meeting is a key indicator of lead conversion speed, follow-up effectiveness, and GTM readiness, reflecting how fast new prospects or users book and attend their first scheduled interaction.

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

In sales-led SaaS, it highlights demo or discovery meeting velocity
In product-led onboarding, it reflects check-ins or kickoff call timing
In high-touch CS models, it surfaces moment of guided onboarding handoff

A faster Time to First Meeting increases conversion odds and user momentum, while a slow path signals workflow gaps, scheduling friction, or low intent. By segmenting by persona, campaign, or lead type, you improve handoff workflows and meeting conversions.

Time to First Meeting informs:

Strategic decisions, like lead routing and sales-assist prioritization
Tactical actions, such as CTA optimization or routing logic fixes
Operational improvements, including calendar tooling, alerts, and SDR enablement
Cross-functional alignment, by keeping sales, RevOps, product, and PMM synced on conversion velocity

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

Scheduling Tools and Calendars: Friction in booking slows progress — or kills it entirely.
Lead Routing and Rep Bandwidth: Delayed assignment = delayed outreach = lower meeting rates.
Lead Intent and CTA Clarity: If the prospect doesn’t know a meeting is the next step, they won’t book.

Improvement Tactics & Quick Wins¶

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

If time to meeting is long, embed calendar links directly after signup or demo requests.
Add “schedule now” CTAs in auto-responses with rep calendar availability.
Run sales alerts for demo forms with under-10-min SLAs.
Refine CTA copy to emphasize meeting value (“Plan your strategy with a product expert”).
Partner with RevOps to build lead status reports and monitor meeting lag in real time.

Required Datapoints to calculate the metric
- User or Lead Signup Timestamp
- First Meeting Attendance Timestamp
- Filters for Exclusions (no-shows, disqualified, etc.)
Example to show how the metric is derived

10 leads booked meetings Total time between signup and meeting: 240 hours Formula: 240 ÷ 10 = 24 hours Time to First Meeting

Formula¶

Formula

\[ \mathrm{Time\ to\ First\ Meeting} = \mathrm{Avg.} \left( \mathrm{Meeting\ Timestamp} - \mathrm{Signup\ Timestamp} \right) \]

Data Model Definition¶

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

UserSignupsMeetingsTimeToFirstMeeting

cube('UserSignups', {
  sql: `SELECT * FROM user_signups`,

  measures: {
    count: {
      type: 'count',
      sql: 'id',
      title: 'Total Signups',
      description: 'Total number of user signups.'
    }
  },

  dimensions: {
    id: {
      sql: 'id',
      type: 'string',
      primaryKey: true
    },

    signupTimestamp: {
      sql: 'signup_timestamp',
      type: 'time',
      title: 'Signup Timestamp',
      description: 'The timestamp when the user signed up.'
    }
  }
});

cube('Meetings', {
  sql: `SELECT * FROM meetings`,

  measures: {
    count: {
      type: 'count',
      sql: 'id',
      title: 'Total Meetings',
      description: 'Total number of meetings.'
    }
  },

  dimensions: {
    id: {
      sql: 'id',
      type: 'string',
      primaryKey: true
    },

    meetingTimestamp: {
      sql: 'meeting_timestamp',
      type: 'time',
      title: 'Meeting Timestamp',
      description: 'The timestamp when the meeting occurred.'
    },

    userId: {
      sql: 'user_id',
      type: 'string',
      title: 'User ID',
      description: 'The ID of the user attending the meeting.'
    }
  }
});

cube('TimeToFirstMeeting', {
  sql: `SELECT us.id AS user_id, MIN(m.meeting_timestamp) AS first_meeting_timestamp, us.signup_timestamp
        FROM user_signups us
        JOIN meetings m ON us.id = m.user_id
        WHERE m.status != 'no-show' AND m.status != 'disqualified'
        GROUP BY us.id, us.signup_timestamp`,

  measures: {
    averageTimeToFirstMeeting: {
      type: 'avg',
      sql: `TIMESTAMPDIFF(SECOND, signup_timestamp, first_meeting_timestamp)`,
      title: 'Average Time to First Meeting',
      description: 'Average time in seconds from signup to first meeting.'
    }
  },

  dimensions: {
    userId: {
      sql: 'user_id',
      type: 'string',
      title: 'User ID',
      description: 'The ID of the user.'
    },

    signupTimestamp: {
      sql: 'signup_timestamp',
      type: 'time',
      title: 'Signup Timestamp',
      description: 'The timestamp when the user signed up.'
    },

    firstMeetingTimestamp: {
      sql: 'first_meeting_timestamp',
      type: 'time',
      title: 'First Meeting Timestamp',
      description: 'The timestamp of the first meeting attended by the user.'
    }
  }
});

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.
- Scheduling Tools and Calendars: Inefficient or complex scheduling tools can create friction, leading to delays in booking meetings and increasing the Time to First Meeting.
- Lead Routing and Rep Bandwidth: Delayed lead assignment due to inefficient routing or overburdened reps results in slower outreach, thus extending the Time to First Meeting.
- Lead Intent and CTA Clarity: If the call-to-action is unclear or the lead's intent is not well understood, prospects may not realize that scheduling a meeting is the next step, increasing the Time to First Meeting.
- Technical Issues: Technical problems with the meeting platform or scheduling tools can cause delays in setting up the first meeting.
- Time Zone Differences: Lack of consideration for time zone differences can lead to scheduling conflicts and delays, increasing the Time to First Meeting.
Positive influences

Factors that push the metric in a favorable direction, supporting growth or improvement.
- Automated Scheduling: Implementing automated scheduling tools can streamline the booking process, reducing friction and decreasing the Time to First Meeting.
- Efficient Lead Routing: Optimizing lead routing processes ensures quick assignment to available reps, facilitating faster outreach and reducing the Time to First Meeting.
- Clear CTA and Lead Education: Providing clear calls-to-action and educating leads on the next steps can encourage quicker meeting bookings, reducing the Time to First Meeting.
- Rep Availability: Ensuring that reps have adequate bandwidth to handle new leads promptly can decrease the Time to First Meeting.
- Proactive Follow-Up: Implementing proactive follow-up strategies can engage leads more effectively, encouraging quicker scheduling of the first meeting.

Involved Roles & Activities¶

Involved Roles

These roles are typically responsible for implementing or monitoring this KPI:

Product Marketing (PMM)
Revenue Operations
Sales Development Representative (SDR)
Sales Manager
Sales Enablement
Activities

Common initiatives or actions associated with this KPI:

Demo Booking
Onboarding
Lead Handoff
Sales Acceleration
SDR Cadences

Funnel Stage & Type¶

AAARRR Funnel Stage

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

Acquisition
Revenue
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.
- Activation Rate: A higher Activation Rate (percentage of users who reach a meaningful engagement milestone) typically accelerates and reduces the Time to First Meeting, as more users become product-engaged and ready for sales or onboarding outreach sooner.
- Deal Velocity: Faster Deal Velocity (speed at which deals move through the pipeline) signals a more efficient sales process, which shortens the average Time to First Meeting by reducing delays between sign-up and initial engagement.
- Product Qualified Accounts: As more Product Qualified Accounts (accounts demonstrating high-value engagement) are identified, sales or CS teams can prioritize and schedule meetings faster, directly decreasing Time to First Meeting.
- Number of Monthly Sign-ups: A surge in Monthly Sign-ups can create pressure on scheduling, potentially increasing Time to First Meeting if not managed; conversely, steady sign-up growth with balanced resources can indicate process health and predict future trends in this KPI.
- Lead Response Time: A shorter Lead Response Time (the speed at which teams respond to new leads) typically results in a faster Time to First Meeting, as prompt follow-up boosts engagement momentum and meeting scheduling rates.
Lagging

These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
- Activation Conversion Rate: This measures how many users achieve activation after onboarding; high rates often correlate with lower Time to First Meeting, confirming that onboarding and early engagement are effective at moving users to meetings.
- Trial Engagement Rate: High engagement during trials shows users are active and interested, likely reducing Time to First Meeting; changes in this metric clarify whether trial quality supports quick meeting scheduling.
- Onboarding Satisfaction Score (OSS): A high OSS (user satisfaction with onboarding) typically means users are more willing and ready to attend meetings early, helping to explain low Time to First Meeting results.
- Percent of Accounts Completing Key Activation Milestones: When more accounts complete high-value activation tasks, it validates that users are progressing efficiently toward their first meeting, amplifying the impact of onboarding improvements on Time to First Meeting.
- First Feature Usage Rate: A higher rate of new users trying key features signals that onboarding and engagement steps are working, which is often reflected in shorter Time to First Meeting as users reach readiness milestones faster.