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Clarks implements in-store scanning app

By Retail Technology | Tuesday December 5 2017

Footwear retailer Clarks is improving in-store response times and assistant productivity with a new scanning app

The company has chosen Scandit  - a developer of next-generation mobile data capture solutions based on computer vision – for its  augmented reality and machine learning capabilities. 

Widely deployed across Clarks retail outlets throughout the UK, the Stock Assist app is available to sales teams on tablets and helps them quickly confirm if a customer’s choices
are in stock. 

Scandit Barcode Scanner SDK powers mobile data capture for Clarks’ Stock Assist, allowing 
store staff to quickly scan barcodes on display products to obtain access to stock records, product information, price, and product imagery. 

This lets sales assistants quickly inform customers if their selection is available, or allows them to suggest alternative sizes or styles.  

Simpler

The scanning function is also useful for backroom staff who can scan a shoebox to retrieve product information. 

“The app runs on the seven-inch tablets already used by our sales teams, and it makes their 
jobs much simpler and quicker,” said Rafal Hartzhorne, omnichannel transformation lead at Clarks. “They have found the Scandit Barcode Scanner easy to use in all conditions, whether on the sales floor or in the stock room, which is a key consideration for us when deploying technology in-store, and it has now become a key component of our Stock Assist app.”

Clarks is currently using the Scandit-powered app in over 500 stores in the UK, on approximately 4000 tablets, and has plans to roll out the app to 12 additional European
stores in the near future. 

The greatest advantage Stock Assist provides is faster speed of sales assistant response when dealing with customers, allowing them to be more productive and responsive to shopper needs. 

Clarks also benefits from the accuracy of the Scandit Barcode Scanner, which reads barcodes even if they have been torn, damaged, worn or are blurry. 


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