The Importance of Scalability in Autonomous Store Networks

Autonomous stores are an emerging phenomenon on the retail map, and they’re getting more and more attention across the industry. The pandemic served as a significant catalyst for their creation, driving the need to limit interpersonal contact. And now, the trend towards fully automated outlets continues to grow.

In a fiercely competitive landscape, focusing on the scalability of autonomous outlets can become a critical factor in staying ahead of the pack. Retail businesses looking to capitalize on the rising demand for such stores should strategically consider how to effectively grow and manage multiple locations.

This involves orchestrating a calculated expansion that hinges on innovative technologies, strategic business planning, and a well-crafted roadmap tailored for growth. In this article, we’ll delve into understanding autonomous store networks and the many considerations when scaling this business.

Understanding autonomous store networks

Autonomous stores are fully automated outlets where no staff directly serve customers. The entire experience is managed by various sensor systems and applications, enabling customers to shop independently without any human assistance.

Entering the store requires a special app or payment card, and once inside, an advanced camera system tracks movements. These sensors determine the selected products and relay the information to a centralized data center that assigns prices, sends the bill to the customer, and processes cashless payments.

The procedure is designed to be as simple as possible to minimize time spent on certain actions (e.g., getting out cash or payment cards, weighing products, or placing goods on a cashier's checkout conveyor belt). By eliminating these steps, autonomous stores accelerate order processing and reduce the time needed for shopping.

Moreover, autonomous stores operate on the same principle regardless of the goods they offer. Autonomous store technology can be deployed by various types of retailers, such as groceries, clothing, hardware, electronics, office supplies, and convenience stores, among many others.

Autonomous stores are also known as grab-and-go stores, not to be confused with scan-and-go or self-checkout systems.

In a grab-and-go setting, shoppers can literally grab items off the shelves and leave the store, as cameras and sensors automatically detect the items taken and charge them to the customer's account. There’s no need for any manual scanning or payment processes, which fundamentally sets it apart from other models.

In contrast, scan-and-go stores require customers to manually scan items with their smartphones before placing them into their carts. Although self-checkout models minimize human interaction, they still require customers to scan, bag, and pay for their items at a dedicated kiosk. While these systems also aim to streamline the shopping experience, they are not fully automated.

Autonomous store technologies

More and more autonomous stores are appearing in various industries thanks to a mix of advanced technologies. These technologies work together to make the store run smoothly and improve the shopping experience for customers.

• Smart shelf technology: RFID (Radio-Frequency Identification) tags and sensors are used for tracking product inventory and movement. ESLs (Electronic shelf labels) display real-time pricing, promotions, and product information.
• Computer vision and cameras: High-resolution cameras and computer vision technology track customer movement and behavior within the store. Object recognition algorithms identify products picked up by customers and automate the checkout process.
• Sensor networks: Proximity sensors monitor customer presence and movement throughout the store. Temperature and humidity sensors maintain optimal conditions for perishable goods.
• Data analytics and AI: Machine learning algorithms analyze customer behavior, preferences, and buying patterns. AI-powered recommendation engines provide personalized product suggestions.
• Automated checkout: Advanced computer vision and sensor fusion technologies identify items picked up by customers and automatically add them to a virtual cart. Seamless integration with digital wallets ensures that payments are processed automatically as the customer exits the store.
• Inventory management systems: Real-time inventory tracking systems monitor product levels and automatically reorder stock when needed. Integration with supply chain and logistics software ensures efficient restocking.
• Security and theft prevention: AI-driven video surveillance systems feature object tracking and anomaly detection capabilities. Theft prevention technologies, such as smart shelves, trigger alarms if items are removed incorrectly, without being captured by surveillance systems.
• Mobile apps and digital interfaces: Store-specific mobile apps enable customers to access store information, navigate the store layout, and receive personalized offers. QR code scanning offers quick and contactless access to product details and pricing.

The potential of autonomous store networks

As this transformation unfolds, it’s crucial to delve into the promise of autonomous store networks, encompassing their advantages and potential hurdles for scalability.

Benefits of autonomous stores for retailers

Grab-and-go stores have the ability to automate mundane tasks, glean insightful data, and personalize the customer experience. Here are the key benefits of autonomous stores for retail establishments:

• Operational efficiency: Autonomous stores reduce the need for extensive human staffing, resulting in lower labor costs. This efficiency is particularly significant for mundane tasks such as restocking shelves, inventory management, and checkout processes, which can be automated and streamlined. According to a 2022 McKinsey analysis, advanced tech-enabled checkout, talent management, merchandising and replenishment, and store environment maintenance can help grocery stores reduce costs by as much as 15–30%.
• Data-driven insights: Autonomous stores are equipped with advanced sensors and cameras that gather real-time data on customer behavior, preferences, and movement within the store. Retailers can use this data to optimize store layouts, product placements, and marketing strategies.
• Reduced theft and loss: Autonomous stores often incorporate sophisticated security measures, such as AI-powered video surveillance and automated theft detection systems. This can significantly reduce incidents of shoplifting and internal theft.
• Consistent, flexible, and dynamic pricing: Autonomous stores not only facilitate real-time dynamic pricing strategies but also ensure pricing consistency through electronic tagging. This solves the common retail issue of displayed prices not matching those in the cash register system. Advanced algorithms can adjust prices based on a myriad of factors – demand, time of day, competitor pricing, or special events – allowing businesses to capitalize on immediate market trends, maximize revenue during peak periods, and stimulate sales when demand wanes.
• Integration with omnichannel strategies: The technology within autonomous stores can be integrated with online platforms, creating a seamless omnichannel shopping experience. This connection bridges the gap between online and in-store shopping, offering consistency and convenience to customers.

Benefits of autonomous stores for customers

While the business advantages of autonomous stores are clear, the customer experience is at the heart of this retail revolution. The convergence of speed, comfort, accuracy, and personalization within grab-and-go outlets translates to an unprecedented level of convenience for shoppers. Here's how:

• Faster and frictionless shopping: Autonomous stores often feature advanced checkout systems that eliminate the need for traditional checkout lines. Customers can simply pick up the items they want and leave the store without waiting. This can also result in reduced crowding, which further enhances the overall comfort and appeal of the shopping environment, especially during peak hours.
• Accurate inventory and availability: Autonomous stores utilize real-time inventory tracking, ensuring that customers have accurate information about product availability. This minimizes the likelihood of disappointment due to out-of-stock items and enables customers to plan their purchases more effectively. In a pilot project in 2021, store robots spotted 14 times as many addressable out-of-stock items as hand scans, reducing out-of-stock instances by 20–30%.
• Personalized recommendations: Autonomous stores are equipped with cutting-edge technology that allows for the collection and analysis of rich customer data. By monitoring shopping behaviors, purchase histories, and individual preferences, the stores can create highly accurate profiles for each customer. This data-driven approach leads to personalized recommendations, offering tailored suggestions for products that align with individual tastes, dietary restrictions, and shopping habits.
• Integration with smart devices: The ability to link autonomous store applications with smart devices, such as smartphones or smartwatches, allows for a seamless connection between the physical store and the customer's personal technology. This integration can facilitate features such as shopping list synchronization, nutritional information access, and even augmented reality experiences, enriching the overall shopping journey.
• Flexibility and convenience: With the automation of various store functions, including checkout and payment processes, customers can shop at their own pace and on their own terms. The absence of traditional operating hours in some autonomous stores means that shopping can be done at any time, day or night, catering to the varied schedules and demands of modern life. From creating shopping lists to receiving electronic receipts, every aspect of the shopping journey is streamlined.

Potential obstacles to the growth of autonomous store networks

While the prospects are promising, the journey towards scalable autonomous stores is fraught with potential obstacles. These are the key risks to watch out for:

• Unsuitable technologies and integration challenges: Choosing unsuitable platforms and technologies can restrict the ability to scale autonomous stores. At the same time, complex integration with existing retail systems like supply chain management or customer relationship management (CRM) software can be costly and time-consuming. For example, selecting a system that fails to integrate with local payment methods could limit expansion into certain markets.
• Consumer acceptance and trust: Building consumer trust in fully automated shopping experiences may take time. Skepticism towards AI and concerns over job displacement might cause resistance among certain consumer demographics. On the other hand, if a highly publicized failure occurs, such as a significant error in billing or security breaches, it could harm the overall acceptance of autonomous store technology.
• Insufficiently refined UX: If autonomous stores are launched with poorly tested interfaces, customers might find navigation and purchasing cumbersome. For instance, autonomous systems that aren’t user-friendly will likely lead to frustration and the loss of repeat customers.
• Regulatory compliance: The legal landscape and regulatory approvals for novel technologies in autonomous stores can vary across jurisdictions, causing potential delays to expansion. Compliance with privacy laws regarding customer data collection, regulations governing AI usage in surveillance, and obtaining necessary approvals for specific technologies can be a serious concern.
• Incorrect estimation of market needs: Misjudging local supply or demand can lead to costly mistakes. Autonomous stores must adapt to local tastes and consumption patterns. For example, an autonomous grocery store stocking products that don't cater to local dietary preferences could find itself with excess inventory.
• Competition with traditional outlets: Autonomous stores might inadvertently compete with traditional outlets from the same retailer, leading to cannibalized sales. Balancing the number and location of autonomous versus traditional stores requires careful strategic planning. An example could be a large retailer opening an autonomous store too close to one of its existing traditional locations, dividing its customer base.

Factors influencing the scalability of autonomous stores

The scalability of autonomous store networks is pivotal to their success and growth. Numerous considerations weigh into the equation, from technological advancements to market dynamics. A careful analysis of these factors allows businesses to smoothly expand their autonomous operations.

• Access to appropriate technological platforms and emerging technologies: With advancements such as improved cameras for recording movement in the store, modernized interactive screens, and new software, the range of possible technical solutions expands. This, in turn, facilitates the construction of new outlets, enabling a more fluid adaptation to changing consumer demands and technological trends.
• Market conditions: Economic variables like inflation and recession play a decisive role in the scalability of autonomous stores. In financially stringent times, these stores become increasingly attractive for their lower operational costs. Consequently, the market situation dictates the pace and extent to which these outlets can scale, particularly when businesses are pressed to adopt more efficient models.
• Competition: The magnitude of competition directly affects the scalability of autonomous stores. A crowded landscape requires more calculated and strategic scaling, influencing the choice of locations, customer targeting, and brand differentiation. A competitive environment demands constant innovation, which triggers the need to scale autonomous outlet networks effectively.
• ROI from existing autonomous outlets: Profits generated from existing autonomous outlets provide critical insights into the viability of the investment. Evaluating the return on investment allows for an assessment of whether the concept proves profitable, informing decisions on scaling the network to higher levels.

Steps to scale autonomous store networks

Scaling an autonomous store network requires a meticulously planned approach, accounting for everything from unified user experiences to cutting-edge technology platforms. This involves a series of stages to ensure maximum efficiency. The following steps provide a basic framework for businesses aiming to develop a thriving network of autonomous stores:

1. Design a consistent shopping experience: A uniform user experience across all outlets is crucial for the seamless adaptation to an autonomous store network. This means the same tools for purchases and standardization of the assortment and technical aspects.

The technical maintenance should also be reduced to the necessary minimum, focusing on essentials like system updates and sensor calibration. This streamlined approach minimizes interruptions, thereby preserving the customer's frictionless interaction with the brand and also upholding operational consistency across various locations.

2. Develop comprehensive applications: The creation of a singular, multifunctional app tailored for the particular retailer is a critical step in scaling autonomous stores. This unified application is designed to guide customers through the entire shopping process, from entering the store to accessing information about promotions and sales.

These apps store essential data such as purchase history, bills, and user profiles, consolidating what might otherwise require multiple software tools into one seamless program. By encompassing activities like managing kiosks or "grab-and-go" functions, the system offers a streamlined and efficient approach that enhances both the retailer's operations and the customer's experience.

"In autonomous stores, the payment process stands as a key element of the concept. Adyen's solution facilitates this process by utilizing payment cards, a universal and widely accessible means of payment, enabling implementation across the globe. The solution enables customers to gain entrance to a store by placing or tapping the payment card on the terminal. This begins a pre-authorization process which enables automated payments later on. Moreover, a range of functionalities designed to bolster this solution allows for easy recognition of returning customers. Within autonomous stores employing the Adyen solution, the payment procedure seamlessly integrates into the shopping process, rendering the entire experience frictionless and allows easy scaling.”

Jakub Czerwiński VP CEE, Adyen

4. Leveraging scalable technological platforms: This involves leveraging a readily accessible technological platform, such as Microsoft Azure or AWS, offering unlimited scaling. These cloud-based platforms provide flexibility and computing power suitable for any size of business, from single-shop initiatives to thousands of correlated facilities. Moreover, infrastructure or platform as a service (IaaS, PaaS) solutions offered by cloud computing companies include highly developed technical and consulting support for partnering businesses.

Based on these four fundamental pillars, store management software can be developed to continually improve and expedite processes. Such a design not only enables customers to make the most of autonomous outlets but also ensures the stability of the services offered.

Successful examples of autonomous store networks

Amazon pioneered the scaling of autonomous store networks, launching its first such facility, Amazon Go, for its employees in 2016. Two years later, the store opened to a broader customer base, and the company expanded to new locations in the United States. In 2021, Amazon's autonomous stores reached the UK, operating under the name Amazon Fresh. Currently, the company oversees more than 40 autonomous locations across the US and the UK, including London.

Following Amazon's lead, the Polish grocery chain Żabka made its own foray into this innovative retail space. The company unveiled its first grab-and-go outlet, Żabka Nano, in Poznań in 2021, expanding to 24 additional locations in six Polish cities within the same year. Since then, the total number of autonomous stores in Poland has exceeded 50, making their network the largest of its kind in Europe.

In Asia, this idea is picking up pace, with major players like Chinese giant Alibaba entering the grab-and-go market. The ecommerce giant unveiled its Tmall Future Store, which uses computer vision, gravity sensors, and built-in cameras to identify goods and add them to virtual shopping carts. These technologies have been shown to increase sales in Alibaba’s ventures. For instance, by moving to an automated framework, they’ve increased annual turnover by 75% in their Alicool souvenir shop, and a renovation of the Zhida Bookstore raised daily turnover by 78%.

The future of autonomous store networks

Emerging technological advancements and business strategies are paving the way for a scalable, efficient, and customer-centric model for autonomous store networks.

Improved and accurate sensors will permit more customers to shop simultaneously while maintaining separate sessions, eliminating the risk of paying for another customer's purchases. Imagine a bustling city center store where hundreds of customers can browse, select, and pay for items without any interference from others – a seamless experience that feels like shopping online but in a physical space.

Further, dynamic scalability will provide the ability to efficiently open or close stores based on profitability, seasonality, and other external factors (e.g., expiring lease agreements). Consider a pop-up retail model where autonomous stores could be deployed seasonally in tourist hotspots or at special events, allowing retailers to capitalize on temporary market opportunities.

Lastly, the introduction of more seamless payment methods and applications will appeal to a broader demographic, increasing the customer base. We can expect the integration of payment technologies that use smart carts, facial recognition, and palm-scanning. These advancements will enable retailers to provide personalized, secure, and frictionless payment experiences that cater to various customer needs. This convergence of AI-driven personalization with cybersecurity measures will be essential for gaining customer trust while simultaneously elevating the shopping experience in autonomous stores.

Navigating the transformation of autonomous stores

Autonomous stores position the consumer at the center of a reimagined shopping experience. Time-saving, convenient, and efficient – these intelligent stores resonate with the changing lifestyles and expectations of the modern customer. The technology that powers this revolution, from advanced sensors to intelligent computer vision, continues to evolve, setting the stage for wider adoption.

However, success in this uncharted territory will not come without challenges. The race to win consumers' attention requires a deep understanding of their behavior, clever marketing strategies, and a resilient infrastructure that guarantees a seamless experience.

While autonomous shopping is still gaining momentum, the necessary preparations, investment, and technology can make businesses cautious when contemplating further automation. In an industry often criticized for its resistance to change, the rise of autonomous stores heralds a welcome disruption, promising not just efficiency and convenience but a redefinition of what retail can be.