Return on Ad Spend (ROAS)¶

Definition¶

Return on Ad Spend (ROAS) measures the revenue generated for every dollar spent on advertising. It is a critical metric for assessing the profitability and efficiency of advertising campaigns.

Description¶

Return on Ad Spend (ROAS) is a key indicator of marketing efficiency and campaign profitability, reflecting how much revenue your ads generate relative to their cost.

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

In DTC, it tracks product-specific revenue from Facebook, Google, or influencer ads
In SaaS, it may reflect PQL or MQL value vs. spend on LinkedIn or Google Ads
In freemium or PLG, it may blend conversion and activation performance per dollar

A rising ROAS means you're spending efficiently and targeting well, while a low ROAS flags potential issues with creative, audience targeting, or funnel conversion. By segmenting ROAS by campaign, channel, or audience, you can double down on what works and quickly pivot from what doesn't.

ROAS informs:

Strategic decisions, like budget allocation across growth channels
Tactical actions, such as pausing underperforming campaigns or optimizing creatives
Operational improvements, including better attribution, conversion tracking, or audience segmentation
Cross-functional alignment, between growth, PMM, and analytics, to drive revenue-positive media spend

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

Audience Targeting Precision: Great targeting = high intent = more revenue per click.
Creative and Offer Alignment: Ads that match landing page experience and buyer need convert higher.
Sales Cycle Length and Deal Size: ROAS improves with fast-converting, high-ACV products.

Improvement Tactics & Quick Wins¶

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

If ROAS is weak, test messaging variations based on pain points, not features.
Add post-click experiences tailored to ad channel (e.g., social vs. search).
Run creative fatigue audits — rotate new assets every 2–3 weeks.
Refine audience segments based on conversion + revenue — not just clicks.
Partner with RevOps to track ad-influenced pipeline, not just first-touch attribution.

Required Datapoints to calculate the metric
- Revenue from Ads: Total revenue generated directly from the advertising campaign.
- Advertising Spend: The total cost of the advertising campaign during the same period.
Example to show how the metric is derived

An e-commerce store spends $5,000 on Google Ads, generating $20,000 in sales. The ROAS is:
- ROAS = $20,000 / $5,000 = 4.0 (or 400%)

Formula¶

Formula

\[ \mathrm{Return\ on\ Ad\ Spend} = \frac{\mathrm{Revenue\ from\ Ads}}{\mathrm{Advertising\ Spend}} \]

Data Model Definition¶

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

AdCampaigns

cube('AdCampaigns', {
  sql: `SELECT * FROM ad_campaigns`,

  measures: {
    revenueFromAds: {
      sql: `revenue_from_ads`,
      type: 'sum',
      title: 'Revenue from Ads',
      description: 'Total revenue generated directly from the advertising campaign.'
    },
    advertisingSpend: {
      sql: `advertising_spend`,
      type: 'sum',
      title: 'Advertising Spend',
      description: 'The total cost of the advertising campaign during the same period.'
    },
    returnOnAdSpend: {
      sql: `revenue_from_ads / NULLIF(advertising_spend, 0)`,
      type: 'number',
      title: 'Return on Ad Spend',
      description: 'Measures the revenue generated for every dollar spent on advertising.'
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: 'string',
      primaryKey: true,
      title: 'ID'
    },
    campaignName: {
      sql: `campaign_name`,
      type: 'string',
      title: 'Campaign Name'
    },
    startDate: {
      sql: `start_date`,
      type: 'time',
      title: 'Start Date'
    },
    endDate: {
      sql: `end_date`,
      type: 'time',
      title: 'End Date'
    }
  }
});

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.
- Poor Audience Targeting: Inaccurate targeting results in lower conversion rates, reducing ROAS.
- Misaligned Creative and Offers: Ads that do not match landing page experience or buyer needs lead to lower conversion rates, negatively affecting ROAS.
- Long Sales Cycle: Extended sales cycles delay revenue realization, decreasing ROAS.
- Low Conversion Rate: A lower conversion rate means fewer sales per ad dollar spent, reducing ROAS.
- High Cost Per Click: Increased costs per click without a corresponding increase in revenue reduce ROAS.
Positive influences

Factors that push the metric in a favorable direction, supporting growth or improvement.
- Audience Targeting Precision: Improved targeting leads to higher conversion rates, increasing revenue per ad dollar spent.
- Creative and Offer Alignment: Ads that align well with landing pages and buyer needs result in higher conversion rates, boosting ROAS.
- Sales Cycle Length: Shorter sales cycles lead to quicker revenue realization, enhancing ROAS.
- Deal Size: Larger deal sizes increase the revenue generated per conversion, positively impacting ROAS.
- Ad Quality Score: Higher quality ads are more engaging and likely to convert, improving ROAS.

Involved Roles & Activities¶

Involved Roles

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

Finance
Marketing
Activities

Common initiatives or actions associated with this KPI:

Lead and Demand Generation
Content Marketing
Paid Channel Attribution

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.
- Product Qualified Leads: Product Qualified Leads (PQLs) are a strong predictor of future advertising ROI, as they reflect the volume and quality of users who exhibit high-intent behaviors. Rising PQLs usually signal that ad campaigns are attracting prospects likely to convert, leading to improved Return on Ad Spend (ROAS) in subsequent periods.
- Activation Rate: Activation Rate indicates the percentage of users who reach a meaningful onboarding milestone. Higher activation rates from ad-driven users signal that advertising is not just generating clicks but high-quality, engaged users that are more likely to convert and generate revenue, thus increasing future ROAS.
- Deal Velocity: Deal Velocity tracks the speed at which prospects move through the sales funnel. If advertising efforts accelerate deal velocity, revenue from those campaigns is realized sooner. Fast-moving deals from ad campaigns can foreshadow a near-term lift in ROAS.
- Trial-to-Paid Conversion Rate: This measures the proportion of trial users (often acquired via ads) who upgrade to paid plans. Improvements here mean ad spend is translating into paying customers more efficiently, directly impacting future ROAS.
- Customer Loyalty: Customer Loyalty as a leading indicator reflects the likelihood that users acquired via advertising will make repeat purchases or renew. High loyalty among ad-acquired cohorts forecasts sustainable revenue streams from advertising, thus improving ROAS over time.
Lagging

These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
- Average Order Value: Average Order Value (AOV) measures the typical revenue per transaction. If ad campaigns drive higher AOV, ROAS will increase because each conversion delivers more revenue per advertising dollar spent.
- Conversion Rate: Conversion Rate quantifies how many ad-driven visitors actually complete a purchase or desired action. Higher conversion rates mean greater revenue for the same ad spend, directly improving ROAS.
- Customer Acquisition Cost: Customer Acquisition Cost (CAC) helps explain ROAS by showing how much is spent to acquire each customer. Lower CAC with stable or increasing revenue improves ROAS, while high CAC can erode it.
- Revenue Growth: Revenue Growth quantifies the increase in overall sales, which can be driven by successful ad campaigns. Strong revenue growth after increased ad spend validates ROAS performance and frames its impact on the broader business.
- Net Profit Margin: Net Profit Margin contextualizes ROAS by revealing how much actual profit is retained after all expenses, including advertising. High ROAS with low profit margin may indicate inefficiencies elsewhere, while strong margins confirm true advertising efficiency.