Can Camcommerce create a deep impact in today's retail industry

Tech trends in retail change with seasons. After phygital, click & collect, conversational commerce and even video commerce, cameracommerce is the new kid on the block. Can this new process of click, look, buy change the future of shopping? Let's find out
Camcommerce: The new tech in retail

Images and Internet- what can they do? Or rather in this golden era of ecommerce, it’s suitable to ask-what can’t they do? Exploring the limitless possibilities of internet and visual discovery, a start-up in Bengaluru is defining the new age commerce- camcommerce. Riding on the philosophy that although mobile phone cameras are used to take thousands of pictures every single day, it is not monetized, the makers of the app are now bridging product selection (through image recognition) and online purchases.

“Instant gratification defines the era we live in and for the many millennial who want to buy then and there, CamCom enables to indulge in impulse buying or gifting. With this, there is no need for googling, mall surfing or browsing,” says AjithNayar, co-founder, CamCom.

While AI, machine learning and big data are playing significant roles in understanding customer behavior and enhancing customer shopping experience, CamCom uses AI and machine learning to understand the purchasing preferences of a consumer. If a consumer wishes to make a purchase, he/she has to click a picture of a product and CamCom analyses the image, classifies the product, and detects details about it. Through NLP (Natural Language Processing), product description is constructed and shown to the consumer and the merchant site to generate options and prices. The consumer can then choose from the options and buy.

AI as the game changer in retail
“Through visual discovery the entire globe becomes a store and the world becomes a product catalogue. You could be anywhere at any point of time in the world and if you want to buy something, CamCom gives you the opportunity. Imagine if you can just click, the app will immediately recognize a product and give you the price options and soon you can buy,” says Umesh, CEO, CamCom. He stresses that AI and machine learning will become the game changers in the future of retail.

From analyzing customer preferences to enabling them to buy and even plan the layout of a shop to make it customer-friendly, artificial intelligence has been a boon to retail. While it not only ensures in improved store operations, it also builds brand loyalty, says Rohan Mahadar, Product Head (Instore AI), Capillary Technologies.  “A lot of tedious jobs have been taken over by automation and AI is now providing the convenience consumers are looking for while shopping,” he says.

Explaining that AI will play a key role in personalization, convenience shopping and customer satisfaction, he says personalization in retail is still not well exploited. 

Way forward- personalization is the key
Although AI is an enabler, retailers must understand that micro segmentation of personalization is not well explored and there is a lot to achieve. “Five years ago, one could have not imagined that practically there will be an app for everything. An app to order food, to book a cab and another app to deliver goods at your doorstep. And customers are open to good value and personalized experiences. When customers are ready for such convenience, retailers must understand that quality of personalization drives sales. Each customer is different from the other and understanding the purchase pattern and accordingly making recommendations is a sign of good service,” he says.

Blend the data
A lot has been said and done about data and how it could drive sales, but Mahadar warns that no single data could help retailers if they don’t use the information to provide right recommendations. “Data will play a very big role and if you don’t make the right sense of captured data, there’s no use of data. When several data is blended to bring right value to the customers, it will help both the brands and consumers. Retailers should now learn to blend the available data for better consumer experience,” he says. 

 

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