Using Kiosk Analytics to Improve Business Operations

5 minutes
Morgan Petty

Using Kiosk Analytics to Improve Business Operations

5 minutes
Morgan Petty

From your favorite fast-food restaurant to the doctor’s office, interactive kiosks have become a familiar part of the scenery.

And while kiosks have become integrated into our daily routines, it’s easy to forget they also serve as powerful tools, capable of delivering valuable information that influences business decisions and elevates customer experience.

With kiosk analytics, businesses can access diverse data to inform their strategy.

How Are Businesses Using Kiosk Analytics?

Digital kiosks can provide businesses with insight into numerous areas, from sales transactions to customer interaction and beyond. Here are a few of the most common areas where kiosk data can be advantageous.

Tracking Transactions and Sales

Tracking sales will always be essential for businesses, so it’s no surprise organizations keep a close eye on transactions generated at self-service kiosks.

Many QSRs report notable uplifts in sales from kiosks compared to orders placed at a counter. And while sales lift may not be the primary goal of deploying self-order kiosks, tracking kiosk sales helps influence self-service strategies, investments in self-service technology, and an organizations’ broader operations decisions.

Studying User Interaction Data

Organizations looking to improve the customer experience and revenues are paying close attention to user interactions.

Research methods used to improve the ecommerce experience are now being applied to self-checkouts and self-service kiosks. Retailers, restaurants, hospitality organizations, storage industry leaders, and others are working closely to understand data points like how long customers are engaging at the kiosk, how they’re navigating the experience, interaction patterns, requests for support, and more.

This intelligence can then be applied to UI updates, re-engineering of customer-facing hardware as well as updates to employee roles or overall business strategy. In addition, businesses are able to compare in-store, ecommerce, and mobile commerce interactions to identify commonalities, gaps, and opportunities.

Personalizing User Experience and Creating Loyal Customers

Businesses have long focused on creating a 360-degree view of their customers. With more information about each unique user, they can aim to provide more personalized experiences and offers relevant to individual customers. The objective is to build stronger brand-customer relationships and win more business from loyal customers.

This type of customer-specific data isn’t limited to ecommerce, mobile interactions, and traditional checkout experiences. Organizations are integrating loyalty into the self-order and self-checkout kiosk process. If customers elect to identify themselves at kiosks with their phone number or by scanning a mobile pass, the operating business may collect information about product selection patterns, how the customer works through the experience, preferred payment methods, and more.

It's important to note there are key privacy compliance considerations to be made when requesting customers’ personal data at the kiosk, though. This is especially important as more organizations experiment with biometric identification methods or “pay with your face” experiences.

In these cases, it’s essential for key stakeholders to consider all applicable consumer rights and privacy laws. They’ll need to ensure there are strong security measures in place to protect customers, legally compliant consumer facing privacy notices, internal privacy polices and a firm understanding of who “owns” and “controls” the data.

Making Informed Decisions About Kiosk Design and Componentry

Organizations that rely heavily on self-service technology to operate are leveraging kiosk component data to make informed hardware decisions.

In close partnership with software and hardware partners, businesses can gain visibility into each electronic component’s performance and meantime between failure rates.

This information can be used to determine the true cost of kiosk componentry. While many manufacturers of electronic kiosk components report meantime between failure rates, the performance of these peripheral devices can be affected by specific environments and programmed settings. By having better insight into these components,parts can be intelligently selected. Informed selection of parts stands to improve performance and satisfaction with the kiosk experience while reducing service and replacement part costs.

Inform Infrastructure, Software, and Hardware Decisions

In addition to studying kiosk componentry, analyzing kiosk downtime can also help organizations understand issues and solutions better.

If poor network connectivity leads to system downtime, businesses can be prepared to update network infrastructure to reduce outages.

In addition, if cache heavy applications lead to regular crashes, hardware and software partners can be tasked to update hardware specs to accommodate heavy cache loads or software teams may re-engineer applications for efficient memory usage.

Capture and Analyze Theft Attempts with Computer-Vision-Powered Cameras

In recent years, retailers have been alerting to a theft epidemic. Reports of increased theft led many retailers to rethink or abandon self-checkout kiosks.

Rather than adopting the narrative that theft at self-checkouts accounts for significant shrink, many retailers are, instead, leveraging data to get a better grip on shrink.

Now, we commonly see self-checkout kiosks with computer-vision-enabled overhead cameras to capture footage from the self-checkout experience. This footage is automatically analyzed using AI-powered systems trained to identify theft attempts, improper product scans, and more.

With reliance on these data, retailers can base business decisions on real shrink numbers rather than assumptions.

How Do Businesses Access Analytics?

These data collection methods can be set up through the organizations themselves or through partners.

Businesses may rely on software partners, leverage the partnerships of their hardware suppliers, or seek support from third-party partners. This often depends on the number of internal resources, capabilities of internal teams compared to external partners, relationships with vendors, and the type of data analysis needed.

Using self-service kiosk data in effective ways often requires close collaboration between internal and external stakeholders. In an ideal scenario, both parties have easy, secure access to meaningful insight that can inform decisions.

Centralized platforms can be configured to not only pull and report useful data in real time, but to develop actions that can be pushed in specific recurring instances. This is true of remote monitoring and managing (RMM) platforms. They can serve as powerful data repositories and be used to push actions to kiosks and other store systems, including kiosks, traditional POS, cameras, digital displays, sensors, and more.

RMM platforms can be configured during the prototyping process. The platform is seamlessly scaled through installation of a software agent on kiosks at point of production. The agent may also be installed on other store hardware.

Conclusion

Having insight to the meaningful data from your self-service kiosks can identify operational bottlenecks, areas of growth, frustration points for users, loyalty program adoption, and so much more. And this is only the beginning.

With many options to access these analytics, your company can continue to stay competitive and responsive to your evolving customer needs.

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