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Robotic Automation Options for Brick-and-Mortar Retailers

This article taps into discussing problems met by retailers and ways in which they can be solved with robotic process automation.

The Causes of Ongoing Problems for the Retailers

A store’s success depends on customer satisfaction and convenience while alleviating staff’s frustration with repetitive, monotonous tasks. Retailers see in-store inventory and price management in need of optimization and improvement to deliver the convenience customers are asking for.

Shopping experiences poisoned by the inconvenience of inaccurate labeling and missing products lead to loss of business, which is never desired. Retailers have the responsibility to monitor if products are precisely named, marked with the correct price or if the right promotions are applied, and if the product has on-shelf-availability. Those processes are defined by a long communication chain that is prone to errors and delays.

Solutions that solve problems of the supply chain are starting to get to the heart of the retailer. Even though they approach shelf gap detection and in-store inventory data, monitoring on-shelf-availability needs a more robust solution that tackles these issues holistically.

Electronic Shelf Labels (ESL) as a Solution for In-Store Price Inconsistencies

Electronic Shelf Labels are small units using e-Ink paper to display product data from price and name to stock availability or applied promotions.

ESLs have replaced repetitive tasks with others of the same nature. Labels are not scanned by hand, but that doesn’t prevent malfunctions of the electronic price tags. The printing and individual placement of paper tags is changed with a tedious battery or device replacement process, slowed down by difficult installation operation and expensive infrastructure costs. Additionally, as the store integration process of ESLs is highly dependent on the company they’ve been acquired from, so is the maintenance process.

Shelf Camera Features for Monitoring In-Store Inventory / OSA

From an operational point of view, shelf cameras do an excellent job when it comes to product and stock detection, compliance with product placement strategies and data collection (inventory updates, shopping patterns). However, with shelf gaps being only one side of the problem, the retail shelf cameras build to high expenses and reliance on long communication chains prone to human error. Passive monitoring of OSA does not refill shelves, solve labels’ accuracy issues or their replacement.

Maintenance processes and costs for hundreds of devices do not justify the need for total, constant surveillance of products. The surge in product demand remains unpredictable and concentrated under the peak traffic periods of the shopping day or promotional campaigns. Having its focus only on shelf availability and out of stock situations, shelf cameras are a solution that although popular still struggles to have its cost versus benefits validated by retailers.

Covering both price and inventory issues, autonomous robots have brought a new level of efficiency to in-store tasks as well as new problems and complexities that retailers have not been prepared for.

The Complicated Transition to Autonomous Retail Robots

Autonomous robots are used and are known for scanning a store for price tag inconsistencies, on shelf inventory and stock issues. Although bringing efficiency to OSA and price tag detection related tasks, in-store problems are still not solved in their integrity (communication chains are still long and error prone). Issues are detected and signaled but to actually replace a price label or replenish on-shelf stocks are actions still dependent on staff as well as long, error prone communication chains.

The consumers have had trouble adapting to the self-roaming robot attacking, getting scarred by or being hurt by its ROI issues, high acquisition and maintenance costs, together with the registered malfunctions, make retailers question fully autonomous solutions.

Building bridges between solutions that are outdated, incomplete and heavily reliant on staff intervention (ESLs and shelf cameras) and the farfetched, costly autonomous robots, semi-autonomous robots are collaborating with humans to deliver the best of both worlds.

A Semi-Autonomous Robot Solves Multiple Problems

With a semi-autonomous robot, the workforce required to execute tedious retail operation tasks is reduced to one staff member who oversees guiding the robot along the aisles and reviewing the output results of scanning sessions. The same operator can take action to resolve or communicate in-store pricing mistakes or out-of-stock issues.

Introducing ERIS, the Semi-Autonomous Retail Robot

ERIS completes the functionalities of shelf cameras through additional capabilities and use cases that treat OSA issues globally not partially. By being able to detect and scan both paper labels and e-ink electronic tags, the semi-autonomous robot makes the task of monitoring labels, including ESLs malfunctions, easier. As the shelves are scanned, when price tag issues are detected, the operator can print the correct labels and replace them on the spot or send alerts about the electronic tags that need to be updated.


In-store pricing accuracy and on-shelf inventory issues are on top of retailers' minds when it comes to delivering convenience and satisfaction to customers. ESLs, shelf cameras and autonomous robots have been overviewed as some of the most popular solutions considered by retailers. However, they have their own shortcomings when comparing the delivered results to the overall investment.

Putting it into perspective, the semi-autonomous robot eliminates risks and concerns brought by its fully autonomous competitors while being a more complete solution than electronic shelf labels and shelf cameras. Human operated robots like ERIS not only does it sponsor a better ROI, but it is also easy to integrate, maintain and get accustomed to solution.


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