How Digital Ordering Defaults Affect Restaurant Sales

When a customer adds guacamole to an online order, did they choose it, or was it already selected?

That distinction matters when restaurants use digital ordering data to make decisions about menu pricing, upselling, and customer loyalty. Higher add-on sales might reflect genuine customer demand, but they could also result from how the ordering system presents options.

The stakes are growing. According to the National Restaurant Association's 2025 Off-Premises Restaurant Trends report, 57% of adults had recently used mobile ordering. Consumers also identified speed, convenience, and easy-to-use ordering technology as important parts of the experience.

For restaurant owners, the challenge is understanding what sales reports actually reveal about customer behavior. Here's how to identify digital ordering defaults, track the right metrics, and test improvements without frustrating guests.

How digital ordering defaults influence restaurant sales

A digital ordering default is a setting that appears automatically when someone places an order. It might be a preselected side dish, a standard drink size, or a previously saved order.

Defaults can make ordering faster, particularly for returning customers. However, they can also influence purchasing decisions.

Consider a customer ordering a burger online. The restaurant offers a $2 premium side upgrade that's already selected when the customer reaches the customization screen.

If 80% of customers keep that selection, the restaurant might conclude that the premium side is popular. But the sales report alone cannot establish whether guests actively wanted the upgrade, noticed the selection, or simply continued through checkout.

The Federal Trade Commission's report on digital dark patterns identifies preselected purchases and confusing interface designs among practices that can manipulate consumer decisions. The report isn't specific to restaurants, but the principles are relevant to digital menus and checkout experiences.

Not every default is problematic. A clearly displayed standard side or saved favorite can make ordering easier. The important distinction is whether customers understand what they're getting and can change their selections without difficulty.

Defaults versus customer habits

Restaurants also need to distinguish between repeated purchases and default acceptance.

A customer who orders the same burrito bowl every Friday may have a genuine preference. Another customer might repeatedly purchase the same meal because the ordering app automatically displays their previous selection.

Both behaviors can produce similar sales results.

The same issue arises with loyalty programs. Members may spend more than nonmembers because the program encourages additional visits, because frequent customers are more likely to join, or because both factors are involved.

That makes repeat-order and loyalty data useful for identifying patterns, but less reliable for explaining what caused them.

Which digital ordering metrics should restaurants track?

Before changing an ordering setting, start with the information available in your point-of-sale (POS) and online ordering systems.

Most operators don't need advanced analytics to begin. Product mix, modifier sales, order values, and refunds can provide a useful starting point.

For example, Toast's menu reporting documentation describes reports for item sales, modifiers, sizes, and transaction details. These help operators understand what customers purchased, although they don't necessarily show which options were preselected or whether guests actively changed them.

The following metrics can help evaluate ordering behavior.

Examples are hypothetical. Actual results depend on consistent definitions, available reporting fields, and the period measured.

Each metric answers a different question.

For instance, an increasing add-on attach rate shows that more qualifying orders include an extra item. It doesn't necessarily prove that an ordering prompt caused the increase.

Similarly, a low modifier override rate doesn't mean customers prefer the default. It simply shows that relatively few customers changed it, assuming the system records those interactions.

Pro Tip: Ask your POS provider whether reports capture the original modifier state and subsequent changes. Many systems show which modifiers were sold without recording every interaction that happened before checkout. If that data isn't available, avoid drawing conclusions about whether a customer actively accepted a default.

Look beyond order value

A higher average order value isn't always a sign of better performance.

Suppose a new add-on prompt increases the average ticket from $18 to $20. That sounds promising until the kitchen reports longer preparation times and higher food waste.

Restaurants should consider ingredient costs, contribution margins, and preparation requirements alongside sales. Our guide to restaurant menu engineering explains why popular or high-revenue items aren't necessarily the most profitable.

The goal is to understand whether a menu change benefits the overall business, not simply whether customers spend more.

How to audit your restaurant's online ordering defaults

An ordering audit starts with the customer experience, not the sales dashboard.

Place a test order through your restaurant's website, mobile app, and any other ordering channels you control. Review each screen from menu selection through checkout.

Pay particular attention to:

• Preselected modifiers: Are sauces, toppings, and sides automatically selected?
• Default sizes: Does the menu clearly distinguish standard and upgraded portions?
• Add-on suggestions: Are desserts, drinks, or other extras optional and clearly priced?
• Combo prompts: Can customers understand what's included before selecting an upgrade?
• Saved orders: Does the system clearly show items carried over from a previous purchase?
• Checkout settings: Are tips, fees, and other charges presented clearly?
• Location-specific menus: Are prices, item availability, and settings consistent with the correct store?

A restaurant using multiple ordering platforms should review each one separately. Settings available through a restaurant's own website may not behave the same way on third-party delivery platforms.

If you're evaluating software capabilities, our comparison of the best restaurant online ordering systems covers menu customization, POS integration, direct ordering, and other operational features.

Make upgrades optional and easy to understand

Consider a pizza restaurant offering extra cheese for $2.

Instead of automatically adding the upgrade, the ordering page could display a clearly labeled suggestion:

Add extra cheese for $2

The customer can accept the offer without having to remove an unwanted selection.

This approach also gives the restaurant a clearer measure of active add-on choices, provided the platform records those selections.

The same principle applies to drink upgrades, premium sides, additional toppings, and other optional items.

Keep prices visible before checkout and avoid making necessary ordering information difficult to find.

For guest-protective practices, leave marketing-consent boxes unchecked, give customers a clear choice about tips, and make allergen-related information and substitutions easy to review. Applicable legal and payment requirements vary, so confirm them with the appropriate provider or qualified professional.

Check settings across locations

Multi-location operators should confirm whether each setting applies to an individual store, ordering channel, menu, or entire restaurant account.

A modifier change intended for one location could affect others if the system uses shared menu settings.

Before making changes, identify who can edit the configuration, how it will be published, and how to reverse it.

This is particularly important when restaurants use centralized POS systems to manage multiple locations.

How to test digital ordering changes without hurting guest experience

Once you've identified a setting worth changing, test one adjustment rather than redesigning the entire ordering experience.

Start with a non-sensitive choice, such as the placement of a suggested dessert, an optional side upgrade, or the order of menu categories.

Avoid experimenting with unclear pricing, preselected tips, marketing consent, or allergen-related selections.

Step 1: Choose one setting and a success metric

Suppose your restaurant wants to increase sales of an optional avocado topping.

The current online menu lists avocado among several modifiers. You want to find out whether a more visible, clearly priced suggestion encourages customers to add it.

Choose add-on attach rate as the primary metric.

Then identify one or two supporting measures, such as average order value, refunds, or customer complaints.

This keeps the test focused on a specific decision.

Step 2: Record your current performance

Before making the change, record how many eligible orders include the topping, the average order value, and any related refunds or complaints.

Use a period that reflects normal operations, including weekdays and weekends where appropriate.

Check whether promotions, seasonal demand, menu prices, or other changes could affect the comparison.

A short before-and-after snapshot can suggest a trend, but it shouldn't be treated as conclusive proof that the setting caused the result.

Step 3: Test the new ordering prompt

Replace the existing modifier presentation with a clearly labeled optional suggestion.

For example:

Make it a premium bowl: Add avocado for $2.

Keep the rest of the menu, pricing, and promotions as consistent as possible.

If your ordering platform supports randomized testing, compare the new prompt with the existing experience across comparable customers. Otherwise, use a carefully matched operating period or location and acknowledge the limitations of the comparison.

The test should run long enough to collect a useful number of orders. A low-volume restaurant may need a longer observation period than a busy quick-service location.

Step 4: Evaluate the results and operational impact

Imagine the restaurant records the following results:

Hypothetical example for illustration.

The add-on attach rate increased by 6 percentage points, representing a 30% relative increase. Average order value also improved modestly, while recorded complaints stayed unchanged.

Those results are encouraging, but the operator should still check whether other conditions changed and whether the extra orders affected ingredient costs or preparation time.

An increase in sales isn't worth much if it creates substantial waste, order errors, or kitchen delays.

Pro Tip: Decide what would make you reverse the change before starting the test. For example, establish an acceptable limit for order corrections, complaints, or service delays based on your restaurant's usual performance. Don't wait until the test ends to decide whether the problems are serious.

Restaurants can also use inventory management software to monitor ingredient usage and costs when testing changes that could affect demand for particular menu items.

Step 5: Keep, revise, or reverse the change

After reviewing the results, decide whether the new setting deserves a permanent place on the ordering menu.

Keep the change if it improves the primary metric without causing unacceptable guest or operational problems.

Revise it if sales improve but customers struggle with the ordering process, or if the added preparation work outweighs the benefit.

Reverse it if the change creates confusion, complaints, or significant costs.

Even a successful test should be monitored after rollout. Results from one location or ordering channel may not carry over to others.

What about restaurant loyalty programs and repeat orders?

Ordering defaults aren't the only reason restaurant reports can be misleading.

Loyalty programs create another measurement challenge because frequent customers may already be more likely to enroll.

According to the National Restaurant Association's 2025 research on loyalty programs, more than three-quarters of customers said earning loyalty points could make them more likely to visit a restaurant, even when it was less convenient.

That shows the importance consumers place on rewards. It doesn't establish how much additional spending a particular restaurant's loyalty program generates.

If loyalty members spend more than nonmembers, check their purchasing history where possible. Were they frequent customers before enrolling? Did their visit frequency change afterward? Are promotional discounts reducing the value of those visits?

Comparing behavior before and after enrollment can provide useful context, although other factors may still explain the difference.

Operators with limited digital ordering volume may find these retention measures more useful than modifier-level analysis. Our restaurant CRM software guide covers tools for managing guest information, loyalty, and repeat visits.

Last bite

Digital ordering data can show which items customers buy, how much they spend, and how often they return. It doesn't always explain why they made those choices.

Before changing menu defaults, review the ordering experience, identify which customer interactions your systems can measure, and test one adjustment at a time.

A higher attach rate or larger order value is a useful signal, but it should be evaluated alongside profitability, operational demands, and customer complaints.

The best ordering settings make it easier for guests to get what they want while giving restaurant owners clearer information for making decisions.