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Restaurant Delivery Analytics: What Metrics Actually Matter

You're drowning in data. Here's how to identify the metrics that actually drive decisions and improve profits.

SM
Sarah Martinez
Head of Product
August 10, 2024
11 min read

The Analytics Problem


Restaurants have more data than ever. Sales reports, platform analytics, customer data, inventory tracking.


But most restaurant owners don't know what to do with it.


They look at numbers, feel overwhelmed, and go back to gut instinct.


But the restaurants that use data effectively see 20-30% better profits.


Here's how to cut through the noise and focus on what matters.


The Metrics That Matter


Revenue Metrics


Total Delivery Revenue

  • Track monthly, weekly, daily
  • Compare to previous periods
  • Set growth targets

  • Revenue by Platform

  • DoorDash vs. UberEats vs. Grubhub
  • Identify strongest platform
  • Allocate resources accordingly

  • Average Order Value (AOV)

  • Track overall and by platform
  • Compare to industry benchmarks
  • Identify opportunities to increase

  • Revenue per Customer

  • Total revenue / number of customers
  • Track over time
  • Identify high-value customers

  • Profitability Metrics


    Gross Profit Margin

  • (Revenue - Cost of Goods) / Revenue
  • Target: 60-70% for delivery
  • Track by platform and item

  • Net Profit Margin

  • (Revenue - All Costs) / Revenue
  • Target: 15-25% for delivery
  • Track monthly

  • Profit per Order

  • Net profit / number of orders
  • Track by platform
  • Identify most profitable channels

  • Food Cost Percentage

  • Cost of goods / Revenue
  • Target: 28-32%
  • Track by category and item

  • Operational Metrics


    Order Volume

  • Total orders per period
  • Track by platform and day of week
  • Identify trends and patterns

  • Prep Time Accuracy

  • Actual vs. estimated prep time
  • Target: Within 2 minutes
  • Track by item and time of day

  • Order Accuracy

  • % of orders with no errors
  • Target: 98%+
  • Track error types

  • Refund Rate

  • Refunds / Total orders
  • Target: Under 3%
  • Track by reason

  • Customer Metrics


    Customer Acquisition Cost (CAC)

  • Marketing spend / new customers
  • Track by channel
  • Compare to customer lifetime value

  • Customer Lifetime Value (CLV)

  • Average revenue per customer over lifetime
  • Track by acquisition channel
  • Compare to CAC (should be 3x+)

  • Repeat Order Rate

  • % of customers who order again
  • Target: 30%+ within 90 days
  • Track by acquisition channel

  • Customer Retention Rate

  • % of customers who return
  • Track monthly and annually
  • Identify churn patterns

  • Platform-Specific Metrics


    DoorDash Metrics

  • Order acceptance rate
  • Average delivery time
  • Customer rating
  • Promoted listing performance

  • UberEats Metrics

  • Order acceptance rate
  • Average delivery time
  • Customer rating
  • Uber One performance

  • Grubhub Metrics

  • Order acceptance rate
  • Average delivery time
  • Customer rating
  • Promotional performance

  • Setting Up Analytics


    1. Choose Your Tools


    Spreadsheets (Simple)

  • Google Sheets or Excel
  • Manual data entry
  • Basic calculations
  • Free

  • POS Analytics (Medium)

  • Built into POS system
  • Automatic data collection
  • Basic reporting
  • Included with POS

  • Analytics Platforms (Advanced)

  • Chowfly, Restaurant365, etc.
  • Advanced analytics
  • Automated reporting
  • $100-500/month

  • 2. Define Your Dashboard


    Daily Metrics:

  • Revenue
  • Order volume
  • Top items
  • Issues/refunds

  • Weekly Metrics:

  • Revenue trends
  • Platform performance
  • Customer metrics
  • Operational metrics

  • Monthly Metrics:

  • Profitability
  • Growth trends
  • Customer lifetime value
  • Strategic insights

  • 3. Set Up Tracking


    Data Sources:

  • POS system
  • Delivery platforms
  • Payment processors
  • Marketing tools

  • Automation:

  • Automatic data import
  • Scheduled reports
  • Alerts for issues

  • Using Analytics to Make Decisions


    Menu Optimization

    Data to track:

  • Item sales volume
  • Item profitability
  • Item ratings
  • Item refund rates

  • Decisions:

  • Remove low-performing items
  • Promote high-margin items
  • Adjust pricing
  • Create new items

  • Pricing Strategy

    Data to track:

  • Price elasticity
  • Competitor pricing
  • Profit margins
  • Sales volume

  • Decisions:

  • Adjust prices
  • Test new prices
  • Create bundles
  • Implement dynamic pricing

  • Platform Strategy

    Data to track:

  • Revenue by platform
  • Profitability by platform
  • Order volume by platform
  • Customer acquisition by platform

  • Decisions:

  • Focus on strongest platform
  • Optimize weaker platforms
  • Adjust pricing per platform
  • Allocate marketing budget

  • Marketing Strategy

    Data to track:

  • Customer acquisition cost
  • Customer lifetime value
  • Channel performance
  • Campaign ROI

  • Decisions:

  • Double down on best channels
  • Cut underperforming channels
  • Test new channels
  • Optimize campaigns

  • Common Analytics Mistakes


    1. Tracking Too Much

    Too many metrics = analysis paralysis. Focus on 10-15 key metrics.


    2. Not Tracking Enough

    No data = flying blind. Track at least basic revenue and costs.


    3. Not Acting on Data

    Data without action = wasted time. Use data to make decisions.


    4. Ignoring Trends

    One data point doesn't tell the story. Look at trends over time.


    5. Not Benchmarking

    Without benchmarks, you don't know if you're doing well. Compare to industry standards.


    Real Results


    A restaurant we work with started using analytics:

  • Tracked key metrics daily
  • Weekly analysis and decisions
  • Monthly strategic reviews
  • Data-driven optimizations

  • Results:

  • 25% improvement in profitability
  • 20% increase in revenue
  • 30% reduction in waste
  • 15% improvement in customer retention

  • Getting Started


  • Week 1: Identify 10 key metrics to track
  • Week 2: Set up basic tracking (spreadsheet or tool)
  • Week 3: Start collecting data
  • Week 4: Create first dashboard
  • Month 2: Start making data-driven decisions

  • The Bottom Line


    Analytics isn't about having data—it's about using data to make better decisions.


    Focus on the metrics that matter:

  • Revenue and profitability
  • Operational efficiency
  • Customer value
  • Growth trends

  • Track them consistently. Analyze them regularly. Act on insights.


    The restaurants that use data effectively see 20-30% better profits.


    Start with 10 key metrics. Track them for 30 days. Then use the insights to make one improvement.


    You'll be surprised by the impact.


    For a restaurant doing $50k/month:

  • 20% profit improvement = $1,000/month
  • Over a year = $12,000

  • Worth the effort? Absolutely.

    Tags

    analyticsmetricsdataprofit optimization

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    SM

    Sarah Martinez

    Head of Product

    Sarah Martinez leads restaurant success at Chowfly, helping hundreds of restaurants optimize their delivery operations and recover lost profits.

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