The use of Ai for e-commerce and shopping assistance

Ai assistance shopping

Artificial intelligence continues to gain traction in the e-commerce industry, from its use on personalisation platforms, such as Recommend, to optimise e-commerce websites, data collection and analysis, to the application of its predictions in improving the customer’s shopping experience.

Through artificial intelligence, personalisation can be taken to a whole new level. Customers receive personalised recommendations beyond using their name in an email marketing campaign or their IP address when visiting a website. It is about making the shopping experience a personal and unique journey.

But how do they do it? Through machine learning, natural language processing, and cognitive computing –an automatic thinking system that emulates human thinking, to mention some of the possibilities of Ai applied to e-commerce.

In the case of Recommend, powered by AI, our solution analyses the information provided by your website visitors to track customer buying behaviour, determine browsing and shopping patterns, and offer suggestions to crafting or improving a brand’s marketing strategy.

What is conversational commerce?

One of the implementations of Ai in assisted purchasing is through conversational commerce. It is a type of e-commerce that uses means of conversation supported by AI to help users during their shopping journey.

It is estimated that voice-enabled purchases could represent 30% of all e-commerce revenue by 2030. This will go beyond desktop transactions. It is about access to virtual services, shopping assistants and chatbots at any touchpoint of the shopping experience.


conversational commerce



Advantages of using AI in e-commerce and assisted purchasing

The application of technologies powered by artificial intelligence algorithms collect data to make your marketing messages more relevant. This will improve the relationship that your customers have with your brand and with the overall online experience.

Thanks to AI, improving the shopping experience also means predicting customer needs. By analysing browsing and shopping behaviour, your site can show product recommendations and cross-sells that respond to users interests.

This same analysis improves marketing messages by determining how brands can interact more effectively with their audience, enhance messages and calls to action, the best time and channel to send a transactional message or a promotional campaign to maximise results.

Most importantly, from a business point of view, it’s about having more reliable data. This information allows you to predict patterns, optimise prices to maximise margins and make product recommendations based on profit  and ROI.

Also, by showing buyers relevant product recommendations, conversion rates increase. For example, in 2021, Recommend customers saw a 117% increase in assisted purchases. This indicates that users rely on recommendations and, most importantly, that personalisation works and is essential.


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