How does data help restaurants increase average basket size?

Increasing the average basket size is no longer based solely on intuition or field experience. In a context where margins are tightening and sales channels are multiplying, data is becoming a real strategic lever for restaurant owners.
Analyzing purchasing behavior, understanding customer habits, and adjusting the offer in real time makes it possible to increase revenue without necessarily having to attract more customers.

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Key points to remember to increase your average basket size

Increasing the average basket size requires, above all, a better understanding of sales and customer behavior.
Data allows you to identify what works, optimize the ordering process, and offer the right product at the right time on the right channel.

In summary:

• The average basket size is determined based on sales data.
• Digital tools facilitate the analysis and activation of commercial levers.
• Performance is based on targeted, measurable, and adjustable actions.

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Understanding the average basket size in the restaurant industry and the crucial role of data

Before optimizing, you need to know how to measure. The average basket size is a key indicator of a restaurant's performance.

Definition, calculation, and importance of the average basket

The average basket, also known as the average ticket, corresponds to the average amount spent by a customer when placing an order.

How to calculate the average basket size in the restaurant industry?

Average basket size = Revenue / Number of orders

Tracking the evolution of this indicator makes it possible to measure the impact of commercial actions and identify levers for increasing revenue without increasing traffic.

Data as the basis for optimization

Increasing the average basket size is not a matter of chance. Restaurant sales data provides a factual overview: the most frequently ordered products, common combinations, times of consumption, and high-performing channels.

Data thus provides a concrete answer to a key question: how can we increase average basket size in a sustainable way?

Collection and analysis of key data in restaurants

The relevant data can be found at each point of contact:

• order composition,
• schedules and peak times,
• sales channel (in-store, kiosk, click & collect, delivery),
• suggestion conversion rate.

Analyzing this information helps to understand behaviors and continuously adjust the offering.

“Thanks to Innovorder, my entire business is quantified. I constantly rely on data to make my decisions.” - Stéphanie Merceron, BChef franchisee in Cholet

Technological tools for exploiting data (POS, CRM, etc.)

To move from analysis to action, restaurants need tools capable of exploiting data in real time.
It is with this in mind that Innovorder has developed Atlas, an AI-native platform designed for the operational management of points of sale.

Unlike traditional reporting tools, Atlas does more than just display figures. The solution centralizes all restaurant data (sales, foot traffic, products, channels, VAT, locations) in a high-performance cloud architecture, then transforms it into concrete recommendations.

Thanks to artificial intelligence, Atlas automatically detects anomalies, identifies opportunities for optimization, and proposes action plans that can be implemented immediately to increase average basket size and improve profitability.
Managers and operators thus have a real data co-pilot at their disposal, accessible on both mobile devices and computers, capable of supporting day-to-day decisions, even during service.

👉 To go further: What if the data from your terminals were your best lever for selling more?

Data-driven strategies to maximize customer offerings and experience

Once the data has been analyzed, it is time to activate it. This is where the strategy comes into its own.

Menu customization and smart recommendations

By analyzing sales, restaurant owners can identify the most complementary products.
Automatically displaying a relevant drink, dessert, or side dish meets a key need: upselling without forcing the purchase decision.
The recommendation is then natural, contextualized, and more effective.

👉 Going further: Understanding upselling and cross-selling for your restaurant

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Implementation of promotions, packages, and additional sales techniques

Data reveals winning combinations. Duo menus, lunch specials, limited offers: every action is based on concrete figures.
These techniques increase the average ticket while reinforcing the customer's perception of value.

Examples of data-driven levers:

• Targeted upselling: +5 to +15% on the average basket 
• Personalized recommendation: +8 to +20% on average basket size 

Optimization of takeaway sales, delivery, and customer journey

On digital channels, each step of the journey influences the shopping cart.
Simplifying navigation, highlighting high-margin products, and tailoring suggestions to the channel can increase the average shopping cart value for click & collect or home delivery.

👉 To go further: 10 tips to boost the profitability of your dark kitchen

Development of loyalty programs and reduction of dropouts

Analyzing customer data helps identify drop-off points: abandoned shopping carts, decreased frequency, disengagement, etc.
Personalized loyalty programs encourage customers to increase their average basket size while strengthening retention.

👉 To go further: 8 tips to ensure your restaurant's profitability

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Successfully increasing a restaurant's average basket size is no longer based on intuition or commercial pressure. Data provides a detailed understanding of behavior, structures decisions, and transforms every customer interaction into a sales opportunity.

By leveraging tools such as Atlas, restaurant owners can manage their business with precision, optimize their offerings, and increase their revenue in a measurable and sustainable way.

In a competitive environment, data is no longer a bonus: it has become a real driver of performance.

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