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Number of Monthly Sign-ups

Definition

Number of Monthly Sign-Ups is the total count of new users, customers, or accounts that sign up for a product, service, or platform within a given month.

Description

Number of Monthly Sign-Ups is a key indicator of acquisition success and product interest, measuring how many new users start their journey during a given month—whether that’s for a free trial, freemium plan, or direct purchase.

Its relevance changes by model:

  • In PLG, it tracks bottom-up product-led momentum
  • In B2B SaaS, it may reflect lead gen through gated onboarding
  • In consumer, it highlights brand reach and top-funnel conversion

A rising sign-up count shows strong campaign effectiveness or organic discovery, while a decline can indicate channel fatigue, poor targeting, or friction in conversion paths. By segmenting by source, campaign, or geo, you uncover what’s driving real intent—and where drop-off might be hiding.

Number of Monthly Sign-Ups informs:

  • Strategic decisions, like budget allocation and ICP validation
  • Tactical actions, such as signup flow testing or incentive placement
  • Operational improvements, including form design, SSO enablement, or friction analysis
  • Cross-functional alignment, linking growth, product marketing, and UX around funnel health

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

  • Traffic Quality and Volume: High intent = high signup. Broad reach without fit kills conversion.
  • Signup Flow UX: Every added step or unclear form field reduces completion.
  • Offer Clarity and Immediate Value: Users sign up faster when they understand what they’ll gain right away.

Improvement Tactics & Quick Wins

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

  • If signups are trending down, A/B test signup page copy, visual layout, and CTA text.
  • Add a “quick-start” option or one-click demo entry.
  • Run campaigns that tie signup to instant outcome (“Plan your first campaign in under 5 minutes”).
  • Refine mobile form experience — many drop-offs happen on small screens.
  • Partner with paid and lifecycle teams to retarget abandoned signup flows.

  • Required Datapoints to calculate the metric

    • Total New Users: Count of new sign-ups during the month.
    • Sign-Up Channels: Breakdown by acquisition source (e.g., organic, paid, social, referral).
    • Sign-Up Type: Free, trial, or paid.

  • Example to show how the metric is derived

    A subscription service sees 1,000 sign-ups in January, up from 800 in December, reflecting a 25% growth rate. By analyzing sources, they find that a referral campaign contributed to 40% of new sign-ups, leading them to double down on referral incentives

Formula

Formula

\[ \mathrm{Monthly\ Sign\text{-}Up\ Growth\ Rate} = \left( \frac{\mathrm{Sign\text{-}Ups\ This\ Month} - \mathrm{Sign\text{-}Ups\ Last\ Month}}{\mathrm{Sign\text{-}Ups\ Last\ Month}} \right) \times 100 \]

Data Model Definition

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

cube('SignUps', {
  sql: `SELECT * FROM sign_ups`,

  measures: {
    totalNewUsers: {
      sql: `id`,
      type: 'count',
      title: 'Total New Users',
      description: 'Count of new sign-ups during the month.'
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: 'number',
      primaryKey: true
    },

    signUpChannel: {
      sql: `sign_up_channel`,
      type: 'string',
      title: 'Sign-Up Channel',
      description: 'Breakdown by acquisition source (e.g., organic, paid, social, referral).'
    },

    signUpType: {
      sql: `sign_up_type`,
      type: 'string',
      title: 'Sign-Up Type',
      description: 'Type of sign-up: Free, trial, or paid.'
    },

    createdAt: {
      sql: `created_at`,
      type: 'time',
      title: 'Sign-Up Date',
      description: 'Date when the sign-up occurred.'
    }
  }
});

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.

    • Traffic Quality and Volume: A broad reach without targeting the right audience can lead to low conversion rates, negatively impacting the Number of Monthly Sign-ups.
    • Signup Flow UX: Complex or unclear signup processes can deter users from completing the signup, reducing the Number of Monthly Sign-ups.
    • Page Load Speed: Slow page load times can frustrate users, leading to higher bounce rates and fewer sign-ups.
    • Mobile Optimization: Poor mobile experience can result in lower sign-up rates as more users access services via mobile devices.
    • Customer Support Availability: Lack of immediate support can discourage potential sign-ups if users have questions or issues during the process.

  • Positive influences

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

    • Traffic Quality and Volume: High-quality, targeted traffic with high intent can significantly increase the Number of Monthly Sign-ups.
    • Signup Flow UX: A streamlined and intuitive signup process encourages more users to complete the signup, boosting the Number of Monthly Sign-ups.
    • Offer Clarity and Immediate Value: Clear communication of benefits and immediate value can motivate users to sign up quickly.
    • Referral Programs: Incentivizing current users to refer others can lead to an increase in sign-ups.
    • Promotional Campaigns: Effective marketing campaigns that highlight unique selling points can drive more sign-ups.

Involved Roles & Activities

Funnel Stage & Type

  • AAARRR Funnel Stage

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

    Acquisition

  • 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.

    • Product Qualified Leads: Product Qualified Leads (PQLs) are a strong precursor to sign-ups, as they reflect users who have engaged deeply enough with the product to be highly likely to sign up soon. Monitoring PQLs provides an early indication of future sign-up trends.
    • Unique Visitors: Unique Visitors is a foundational top-of-funnel metric that signals the potential pool of new sign-ups. An increase in unique visitors often forecasts a rise in monthly sign-ups if conversion rates hold steady.
    • Monthly Active Users: Monthly Active Users (MAU) tracks the engaged user base, with higher MAU typically leading to more new sign-ups through network effects or increased product visibility/referrals.
    • Trial-to-Paid Conversion Rate: Trial-to-Paid Conversion Rate helps contextualize the quality of sign-ups, indicating how many new sign-ups are likely to become paying customers, thus acting as a leading signal for the quality and not just the quantity of sign-ups.
    • Activation Rate: Activation Rate measures how many new users experience the product's core value, forecasting future monthly sign-ups by indicating the effectiveness of onboarding and early engagement processes.

  • Lagging

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

    • Signup Completion Rate: Signup Completion Rate quantifies what proportion of initiated sign-ups are successfully completed, providing direct feedback to recalibrate and optimize top-of-funnel leading metrics and conversion strategies.
    • Conversion Rate: Conversion Rate reflects the effectiveness of the user journey from visit to sign-up, offering insights that can inform adjustments to leading indicators like unique visitors or trial sign-up rates.
    • Drop-Off Rate: Drop-Off Rate identifies where potential sign-ups are lost, allowing teams to diagnose friction points and refine leading indicators and user flows for better forecasting.
    • Trial Sign-Up Rate: Trial Sign-Up Rate measures the percentage of visitors initiating a trial, which can be used to recalibrate leading metrics by indicating the true effectiveness of acquisition and awareness efforts.
    • New Account Creation Rate: New Account Creation Rate provides an aggregate outcome metric that can be used to validate and adjust upstream leading indicators, ensuring that early funnel metrics are aligned with actual user onboarding.