Time to First Contact¶

Definition¶

Time to First Contact measures the time elapsed between a user or lead’s initial conversion event (e.g., signup, form submission, demo request) and your team’s first outreach or response. It helps assess responsiveness and lead handling speed.

Description¶

Time to First Contact is a key indicator of response velocity, lead nurturing efficiency, and buyer experience, reflecting how fast your team reaches out after a signup, inquiry, or lead signal.

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

In Sales-led B2B, it highlights form fill to SDR/AE outreach time
In CS or onboarding, it reflects initial welcome or kickoff engagement
In Support, it surfaces first-touch responsiveness (related but distinct metric)

A shorter Time to First Contact boosts qualification rates and trust, while delays can lead to drop-off, disengagement, or lost deals. By segmenting by channel, region, or rep, you can spot bottlenecks and optimize outreach logic.

Time to First Contact informs:

Strategic decisions, like SLA definitions and lead scoring models
Tactical actions, such as automation rules or rep capacity planning
Operational improvements, including routing flows, alert systems, and CRM hygiene
Cross-functional alignment, by bringing sales, CS, ops, and RevOps together on fast, consistent lead handling

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

Speed-to-Lead Routing: The faster you assign leads, the faster you can follow up.
Sales Coverage Model: Unassigned leads or off-hour submissions increase lag.
Automation and Notification Setup: Real-time alerts or round-robins reduce delay.

Improvement Tactics & Quick Wins¶

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

If first contact takes too long, implement a lead routing audit and set SLAs per lead type.
Add automated “we’re on it” emails within minutes of signup or form completion.
Run lead scoring to prioritize high-fit leads for immediate rep outreach.
Refine scheduling workflows to offer calendar links instantly.
Partner with RevOps to monitor lead-to-first-touch time daily.

Required Datapoints to calculate the metric
- Timestamp of User Action (e.g., signup or request)
- Timestamp of First Outreach (email, call, chat, message)
- User ID or lead ID (for tracking at account/user level)
Example to show how the metric is derived

150 new PQLs in a week Time between signup and first outreach ranged from 5 mins to 8 hours Average Time to First Contact = 1.7 hours

Formula¶

Formula

\[ \mathrm{Time\ to\ First\ Contact} = \mathrm{Avg}\left( \mathrm{Time\ of\ Outreach} - \mathrm{Time\ of\ User\ Action} \right) \]

Data Model Definition¶

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

UserActionsFirstOutreachTimeToFirstContact

cube('UserActions', {
  sql: `SELECT * FROM user_actions`,
  measures: {
    count: {
      type: 'count',
      sql: 'user_id',
      title: 'User Action Count',
      description: 'Counts the number of user actions.'
    }
  },
  dimensions: {
    id: {
      sql: 'id',
      type: 'string',
      primaryKey: true,
      title: 'User Action ID',
      description: 'Unique identifier for each user action.'
    },
    userId: {
      sql: 'user_id',
      type: 'string',
      title: 'User ID',
      description: 'Identifier for the user associated with the action.'
    },
    actionTimestamp: {
      sql: 'action_timestamp',
      type: 'time',
      title: 'Action Timestamp',
      description: 'Timestamp of the user action.'
    }
  }
})

cube('FirstOutreach', {
  sql: `SELECT * FROM first_outreach`,
  measures: {
    count: {
      type: 'count',
      sql: 'user_id',
      title: 'First Outreach Count',
      description: 'Counts the number of first outreach actions.'
    }
  },
  dimensions: {
    id: {
      sql: 'id',
      type: 'string',
      primaryKey: true,
      title: 'First Outreach ID',
      description: 'Unique identifier for each first outreach action.'
    },
    userId: {
      sql: 'user_id',
      type: 'string',
      title: 'User ID',
      description: 'Identifier for the user associated with the outreach.'
    },
    outreachTimestamp: {
      sql: 'outreach_timestamp',
      type: 'time',
      title: 'Outreach Timestamp',
      description: 'Timestamp of the first outreach action.'
    }
  }
})

cube('TimeToFirstContact', {
  sql: `SELECT ua.user_id, TIMESTAMPDIFF(SECOND, ua.action_timestamp, fo.outreach_timestamp) AS time_to_first_contact
        FROM user_actions ua
        JOIN first_outreach fo ON ua.user_id = fo.user_id`,
  measures: {
    averageTimeToFirstContact: {
      type: 'avg',
      sql: 'time_to_first_contact',
      title: 'Average Time to First Contact',
      description: 'Average time in seconds from user action to first outreach.'
    }
  },
  dimensions: {
    userId: {
      sql: 'user_id',
      type: 'string',
      title: 'User ID',
      description: 'Identifier for 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.
- Unassigned Leads: Leads that are not immediately assigned to a sales representative can significantly increase the Time to First Contact, as they may sit idle until manually addressed.
- Off-Hour Submissions: Leads submitted during non-business hours often experience delays in response, extending the Time to First Contact.
- Manual Lead Assignment: Relying on manual processes for lead assignment can introduce delays, as it depends on human intervention, increasing the Time to First Contact.
- Lack of Real-Time Alerts: Without real-time notifications, sales teams may not be promptly aware of new leads, leading to increased Time to First Contact.
- Inefficient Sales Coverage Model: A poorly structured sales coverage model can result in leads being overlooked or delayed, negatively impacting the Time to First Contact.
Positive influences

Factors that push the metric in a favorable direction, supporting growth or improvement.
- Speed-to-Lead Routing: Implementing fast and efficient lead routing processes ensures that leads are quickly assigned to the appropriate sales representative, reducing the Time to First Contact.
- Automation in Lead Assignment: Using automated systems to assign leads can significantly decrease the Time to First Contact by eliminating manual delays.
- Real-Time Notification Setup: Setting up real-time alerts for new leads ensures that sales teams can respond promptly, reducing the Time to First Contact.
- Round-Robin Assignment: A round-robin system for lead distribution ensures that leads are evenly and quickly assigned, minimizing the Time to First Contact.
- 24/7 Sales Coverage: Ensuring that there is always a sales representative available to respond to leads, regardless of the time of submission, can greatly reduce the Time to First Contact.

Involved Roles & Activities¶

Involved Roles

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

Customer Success
Growth
Marketing Operations
Revenue Operations
Sales Manager
Activities

Common initiatives or actions associated with this KPI:

Lead Routing
Sales Enablement
Onboarding
PLG-to-Sales Handoff
Demo Flows
CRM Alerts

Funnel Stage & Type¶

AAARRR Funnel Stage

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

Acquisition
Activation
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.
- Lead Response Time: Lead Response Time acts as a direct leading indicator to Time to First Contact by measuring the average time it takes to respond to a new lead after their initial inquiry. Faster lead response times typically reduce Time to First Contact, improving responsiveness and increasing the likelihood of successful engagement.
- Activation Rate: Activation Rate reflects how quickly and efficiently new users reach a meaningful engagement milestone post-signup. High activation rates signal streamlined onboarding and prompt outreach, often resulting in shorter Time to First Contact as teams are alerted to high-intent users sooner.
- Product Qualified Accounts: Product Qualified Accounts (PQAs) identify accounts whose engagement signals indicate readiness for sales. Detecting PQAs early allows sales teams to prioritize outreach, thus reducing Time to First Contact for the most valuable potential customers.
- Sales Qualified Leads: Sales Qualified Leads (SQLs) are prospects identified as ready for sales engagement. The faster and more accurately SQLs are flagged, the sooner the sales team can initiate first contact, making this a key upstream driver of Time to First Contact.
- Marketing Qualified Leads (MQLs): Marketing Qualified Leads (MQLs) are leads deemed likely to convert based on behavioral and fit criteria. Effective MQL identification streamlines handoff to sales, enabling faster initial outreach and thus influencing Time to First Contact.
Lagging

These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
- Lead Response Time (Post-Onboarding): Lead Response Time (Post-Onboarding) measures how quickly teams respond to leads after onboarding. Analyzing this lagging KPI allows organizations to recalibrate their leading indicators (like Lead Response Time and Activation Rate), informing process improvements and outreach strategies to further reduce Time to First Contact.
- Initial Sales Touch Engagement Rate: Initial Sales Touch Engagement Rate quantifies the effectiveness of first outreach. High or low engagement rates can guide teams to refine their lead scoring and response prioritization, recalibrating how leading indicators are interpreted to optimize Time to First Contact.
- Onboarding Satisfaction Score (OSS): OSS captures user feedback after onboarding, revealing friction points that may delay outreach. By analyzing OSS trends, teams can update leading metrics (e.g., Activation Rate) to better predict and accelerate Time to First Contact for future cohorts.
- Signup Completion Rate: Signup Completion Rate highlights the proportion of users who finish the signup process. If this lagging metric drops, it may signal issues upstream that slow down the trigger for first contact, prompting teams to refine leading indicators and funnel processes.
- Trial Engagement Rate: Trial Engagement Rate reflects how actively new users engage during their trial period, post-initial contact. Poor engagement can prompt a review of how and when first contact occurs, leading to targeted adjustments of leading metrics and playbooks to improve responsiveness.