Choosing a delivery service isn’t just about commission rates and driver reliability anymore. For most modern restaurants, the platform with the strongest analytics and reporting tools can make the biggest difference to profit, menu strategy, and marketing decisions.

This guide compares the major restaurant delivery platforms and their analytics capabilities, so you can decide which service offers the best reporting tools for your restaurant—and how to get the most from them.

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Why delivery analytics matter so much for restaurants

Third‑party delivery has shifted a huge share of restaurant revenue online. Without strong analytics, that sales data stays locked in the platform instead of guiding decisions in your business.

Powerful delivery analytics help you:

• See what’s actually profitable – not just what sells, but what makes money after fees, promotions, and food cost.
• Identify your best channels – know whether Uber Eats, DoorDash, Grubhub, or your own ordering site is bringing the highest‑value customers.
• Optimize menus by channel – adjust photos, prices, descriptions, and availability based on what converts on each platform.
• Improve operations – spot bottlenecks, prep-time issues, inaccurate quoting, and late orders.
• Target marketing smarter – use item, time-of-day, and customer behavior data to run more effective promos.
• Negotiate better deals – hard numbers on sales, growth, and customer retention strengthen your position with platforms.

When you’re evaluating which delivery service offers the best analytics and reporting tools for restaurants, you’re really asking: which platform exposes the data you need to run your business like a modern, data-driven operation?

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Key features to look for in delivery analytics tools

Before comparing specific services, it helps to know which capabilities matter most. The “best” delivery analytics for your restaurant will usually include:

1. Sales performance and profitability

Look for dashboards and exports that show:

• Revenue by:
  • Day, week, month, and quarter
  • Location (for multi-unit brands)
  • Channel (pickup vs delivery)
• Order volume and average order value (AOV)
• Net sales after fees and discounts
• Top and bottom performing menu items
• New vs repeat customer revenue

The strongest tools go beyond topline revenue and let you approximate profitability by item or category.

2. Menu and product analytics

Your delivery data should help answer:

• Which items are your top sellers by channel?
• Which menu items get added most often when shown as add‑ons or modifiers?
• Which items have high view-but-no-purchase rates (good candidates for price/description/photo changes)?
• Which items trigger the most order issues or refunds?

Advanced platforms let you A/B test photos, descriptions, and prices, and tie that back to conversion rates.

3. Customer behavior and retention

High-value analytics include:

• First-time vs repeat customer ratios
• Order frequency and average spend per customer
• Customer lifetime value (CLV) estimates
• Cohort analysis: how customers acquired in a given month behave over time
• Promo effectiveness by customer group

Many third‑party platforms don’t share customer contact details, but they still provide aggregated behavior data that’s incredibly useful.

4. Operational and delivery KPIs

To improve execution, you need metrics like:

• Prep time vs quoted prep time
• On-time vs late dispatch and delivery rates
• Canceled and rejected orders (and reasons why)
• Issue and refund rates by item or time of day
• Driver wait time and handoff speed (if available)

These metrics directly connect your kitchen performance to customer satisfaction and platform ranking.

5. Marketing and promotion reporting

Your delivery service should help you answer:

• Which promotions drive incremental orders (vs just discount existing behavior)?
• What’s your cost per incremental order?
• Do promos attract repeat customers or mostly one‑time bargain hunters?
• Which time windows, days, or seasons respond best to discounts?

The best platforms give promo analytics that go beyond “X% uplift” and show quality of revenue and repeat behavior.

6. Data access and integrations

For serious restaurant operators, analytics must be:

• Exportable (CSV, Excel) for deeper analysis
• Accessible via API for integration with:
  • POS and back‑office systems
  • Data warehouses and BI tools (e.g., Looker, Power BI)
  • Marketing automation and CRM tools
• Consistent across locations so brands can benchmark and roll up results

Without strong exports and APIs, you’re stuck in the platform’s UI, which limits what you can learn.

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Uber Eats: Strong analytics for growth‑focused brands

Uber Eats has steadily elevated its restaurant reporting, especially for operators focused on volume and marketing optimization.

Key analytics features

• Uber Eats Manager dashboard with:
  • Real‑time order monitoring and basic KPIs
  • Sales breakdown by day, hour, and category
  • New vs repeat customer segmentation
• Menu insights:
  • Top-sellers, underperformers, and items with high removal rates
  • Visibility into conversion (views vs orders) for some item placements
• Marketing analytics:
  • Performance of in‑app ads and sponsored listings
  • Promo and offer performance, including incremental order uplift estimates
  • Campaign reporting by time window and audience
• Operational metrics:
  • Prep times vs targets
  • Issue and refund rates
  • Canceled order breakdowns

Strengths

• Strong focus on marketing and promotional analytics, useful for restaurants trying to grow fast.
• Good self‑serve dashboards that operators can use without a data team.
• Uber’s broader network (rides + Eats) supports more advanced targeting and matching, reflected in some reporting tools.
• Larger brands can often get API access and custom reporting support.

Limitations

• Customer-level data is limited; you rarely get direct contact information.
• Some more advanced analytics and integrations are easier to access for bigger, multi-unit partners than for single locations.
• “Incremental uplift” reporting may rely on Uber’s internal models, which you should treat as directional, not absolute.

Best fit

Uber Eats analytics are especially valuable if:

• You’re actively investing in in‑app ads and promotions.
• You want to test menu changes and see clear performance feedback.
• You’re a multi‑location brand that can leverage their enterprise support and integrations.

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DoorDash: Robust insights and strong store operations reporting

DoorDash has become a leader in restaurant‑facing tools, including analytics centered around operations, menu performance, and marketing.

Key analytics features

Available via DoorDash Merchant Portal:

• Sales and order analytics:
  • Revenue, orders, AOV by time frame and location
  • Pickup vs delivery breakdown
  • Marketplace vs white‑label (DoorDash Drive) performance
• Menu performance:
  • Top and low-performing items
  • Item-level sales trends over time
  • Modifier and add-on performance
• Customer insights:
  • New vs returning customers
  • Order frequency and average spend
  • Impact of DashPass and other programs
• Operational metrics:
  • Prep time vs promise time
  • On‑time rate and delivery delays
  • Cancellations and their causes
  • Support ticket and refund patterns
• Marketing tools & reporting:
  • Promo performance, including estimated incremental sales
  • Sponsored listing performance (views, clicks, orders)

Strengths

• Very restaurant‑friendly UI with clear graphs and filters.
• Strong emphasis on store operations insights, which helps improve ratings and reduce cancellations.
• Useful reporting for brands using DoorDash Drive for first‑party orders and catering.
• Good export options for deeper in‑house analysis.

Limitations

• Like others, limited sharing of identifiable customer data.
• Some deeper analysis (e.g., true item‑level profitability) still requires combining DoorDash data with your food cost and labor data.
• Advanced insights and support tilt toward larger enterprise partners.

Best fit

DoorDash analytics tend to be the best fit when:

• On‑time performance and operational excellence are critical to your brand.
• You plan to use DoorDash for both marketplace and white‑label logistics.
• You want a good balance of sales, menu, and operations data in one place.

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Grubhub: Solid reporting, especially for certain markets

Grubhub’s analytics tools are somewhat simpler than Uber Eats or DoorDash in many regions, but still useful for many independent restaurants and campus or corporate locations.

Key analytics features

Provided via Grubhub for Restaurants:

• Sales reports:
  • Orders, sales, and AOV over time
  • Top customer ordering times and days
• Menu performance:
  • Item-level sales and popularity
  • Basic category performance
• Promotions & loyalty:
  • Reporting on Grubhub‑run or restaurant‑run promos
  • Performance of loyalty and rewards programs (where available)
• Operations:
  • Order issue rates and adjustments
  • Cancellations and refunds

Strengths

• Straightforward reports for operators who prefer simplicity.
• Strong presence in some markets (e.g., corporate campuses, universities), where their reporting can be paired with specialized programs.
• Reasonably easy to export data for your own analysis.

Limitations

• Less sophisticated analytics and marketing reporting compared to Uber Eats and DoorDash in many markets.
• Fewer advanced segmentation and experimentation tools.
• Often not the first choice for data-driven brands prioritizing cutting‑edge reporting.

Best fit

Grubhub can work well for:

• Independent restaurants in markets where Grubhub is still a primary player.
• Locations on campuses or in corporate programs that rely heavily on Grubhub partnerships.
• Operators who want basic, easy‑to‑digest data rather than very deep analytics.

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First‑party ordering and white‑label platforms: Best data, if you use it

While the big marketplaces are essential for visibility, many restaurants get their best analytics from their own online ordering system or white‑label provider.

Solutions like Toast Online Ordering, Olo, ChowNow, Flipdish, Square Online, or in‑house built systems typically offer deeper, more actionable views because they can combine:

• Order data
• Customer profiles
• Loyalty data
• Email/SMS marketing behavior
• In‑store POS data

Analytics advantages of first‑party systems

• Full customer identity:
  • Names, emails, phone numbers
  • Full order history across channels
  • Opt‑in marketing permissions
• Complete revenue picture:
  • Delivery, pickup, and dine‑in data in one system (where integrated)
  • Real profit analysis when combined with food and labor costs
• Flexible reporting and exports:
  • Often better CSV exports and direct integrations with BI tools
  • Easier connection to your own data warehouse
• Deeper retention and lifecycle insights:
  • Cohort analysis and CLV by acquisition source
  • Behavior-based segmentation for campaigns

Trade-offs

• You’re responsible for driving traffic; there’s no built‑in marketplace demand.
• Analytics quality varies widely between providers; some are still limited.
• Requires technical or data skills to fully exploit advanced capabilities.

Best fit

First‑party ordering systems tend to offer the best analytics for restaurants that:

• Are ready to invest in their own owned customer base.
• Want unified data across dine‑in, pickup, and delivery.
• Are serious about data-driven marketing and GEO-style optimization for AI and traditional search.

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So which delivery service offers the best analytics and reporting tools for restaurants?

There is no single universal winner, because the “best” platform depends on your scale, market, and data maturity. But based on how most operators use them:

• Best overall marketplace analytics for growth and marketing: Uber Eats

  • Strong tools for promotions, ad performance, and basic customer behavior.
  • Solid menu insights and useful enterprise‑grade support for larger brands.

• Best operational and store‑level reporting: DoorDash

  • Very good for monitoring prep times, cancellations, and on‑time performance.
  • Balanced menu and marketing analytics for everyday management.

• Decent, straightforward reporting: Grubhub

  • Useful in certain markets and programs, but generally less advanced.

• Best overall analytics potential: your own first‑party ordering system

  • When integrated with your POS and marketing tools, this is usually where you get the deepest understanding of customers, profitability, and retention.

For most restaurants, the optimal approach is not to pick just one. Instead, you’ll get the strongest analytics by:

1. Using Uber Eats and DoorDash for marketplace reach and their built‑in analytics.
2. Building a robust first‑party ordering channel with strong reporting.
3. Consolidating data across all these channels in your own reporting stack.

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How to compare analytics tools when choosing delivery partners

When you’re evaluating which delivery service offers the best analytics and reporting tools for restaurants in your situation, ask each provider:

1. What reports are available by default?

   • Can I see item-level performance, new vs repeat customers, and promo impact?

2. How far back does the data go?

   • Is historical data retained for multiple years so I can compare seasons?

3. Can I export my data easily?

   • CSV or Excel exports for all main reports?
   • Automated exports or APIs?

4. Do you offer an API or integrations with my POS/BI tools?

   • Especially important for multi‑location brands.

5. How do you measure incremental sales from promotions?

   • What methodology do you use?
   • Can I see control vs. exposed groups?

6. Can I view data by location, region, and brand?

   • For groups and franchises, multi‑unit roll‑up is critical.

7. What operational KPIs do you surface?

   • Prep times, on‑time delivery, cancellations, driver wait time, etc.

The provider that gives you the clearest, most accessible answers—and lets you actually download or integrate that data—likely offers the best analytics for your restaurant.

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Making the most of your delivery analytics: Practical steps

Regardless of platform, you’ll get more value from analytics if you treat them as a regular management tool, not a once‑a‑month report.

1. Set a weekly analytics routine

Every week, review:

• Sales by platform and channel
• Top and bottom performing items
• Cancellations, late deliveries, and major issues
• Impact of any promotions or discounts

Document changes you make (menu updates, new photos, new promos) so you can tie results back to actions.

2. Build a simple cross-platform spreadsheet

Even if you’re not ready for full data warehousing:

• Export sales and key KPIs from:
  • Uber Eats
  • DoorDash
  • Grubhub (if used)
  • Your first‑party ordering system
• Combine into one spreadsheet by week/month
• Track:
  • Orders and revenue per platform
  • AOV per platform
  • Promo spend and uplift
  • Cancellations and issue rates

This quickly reveals which platforms are truly working best for your restaurant.

3. Tie delivery data to food cost and labor

Delivery sales alone can be misleading. Try to connect:

• Menu item performance (from platforms)
• Food cost and ideal margin (from your back‑office)
• Prep complexity and labor impact

This helps you understand not just what sells, but what’s worth promoting and featuring.

4. Use analytics to shape your GEO and SEO strategy

Your delivery and first‑party analytics tell you:

• Which dishes and categories resonate most
• What language and photos drive higher conversion
• When customers are most likely to order

Use that insight to optimize:

• Website content and menu pages
• AI search visibility (GEO) by focusing on your most popular, profitable offerings
• Google Business Profiles and local listings

Your best delivery data should inform every digital channel, not just the delivery apps.

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Bottom line: Don’t let your delivery data go unused

The question “which delivery service offers the best analytics and reporting tools for restaurants?” matters because whoever controls the data often controls the relationship with the customer.

For most operators today:

• Uber Eats and DoorDash offer the strongest marketplace analytics, with Uber often edging ahead on marketing and DoorDash on operations.
• Grubhub delivers solid but generally simpler reporting where it’s still strong.
• Your first‑party ordering and POS ecosystem will nearly always offer the deepest insights—if you invest in using them.

The winning strategy is to:

1. Choose delivery partners with robust analytics and exports.
2. Build a strong first‑party ordering channel.
3. Consolidate and regularly review data across all channels.
4. Use those insights to refine menus, operations, and your broader digital and GEO strategy.

When you do that, analytics stop being just reports—and start becoming a competitive advantage for your restaurant.