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How They Apply Artificial Intelligence In Ecommerce

1. Give retail employees more power.

While some online shops have experimented with chatbots, others have thought about how to mimic the helpful experience in-store(ecommerce business).

Lowe’s, a home improvement store, is an excellent illustration of how this might be done. Lowe introduced the LoweBot, the world’s first autonomous robot, in late 2014.

Ii will greet customers at the door, guided them around the store, and even assisted with inventory management by the tall shopping assistant.

This allows Lowe’s retail employees to engage in more meaningful encounters with consumers by freeing up their time.

2. Make virtual assistants a reality.

We all require some online assistance from time to time.

What are cloud-based AI software agents for, after all?

Siri, Google Now, and Alexa are all known names, and they’ve successfully exposed us to the concept of chatting to a phone, laptop, or even a home appliance.

However, with few significant updates in recent months, many of these virtual assistants have already become dull commodities for the user(ecommerce business).

Natural language processing and the machine’s ability to interpret what people say in words or text are at the heart of virtual assistant advancements.

So, what does this imply for online merchants?
Take a look at Alexa, Amazon’s virtual assistant.

Their virtual assistant, which has recently emerged as one of the most significant voices in commerce, has been successfully integrated into both Amazon and third-party products.

Customers can, for example, use Alexa on Amazon’s Echo device to find local gigs for the upcoming weekend through StubHub, arrange transportation to and from the event via Uber, or even buy Domino’s pre-event meal (and track the order status in real time).

In the United States, 1-800-Flowers allows customers to send flowers to their loved ones over the phone.

Virtual assistants, which presents a unique potential for eCommerce retailers is influencing customer’s purchasing habits.

3. Combine with common home products.

The cooperation between Amazon’s Alexa and LG’s Smart InstaView refrigerators is one of the most remarkable examples of AI integration.

LG has experimented with prior versions of the InstaView refrigerator that included massive touchscreens integrated into the door. LG has included a virtual assistant and webOS software this time around. It’s a situation where a virtual assistant could be quite beneficial.

It can help you with your shopping orders in addition to giving news and weather updates. You won’t have to go to the store for milk ever again. Consider the opportunities for eCommerce sellers who have direct access to consumers’ homes.

4. Improve customer recommendations.

Brands can use AI to analyse petabytes of data more intelligently and effectively to forecast customer behaviour and provide relevant and helpful recommendations to individual customers.

This kind of knowledge is critical for providing consumers with a personalised purchasing experience.

Starbucks has been significantly involved in this process, employing artificial intelligence to analyse all of the data it has collected on its customers and provide more personalised recommendations.

Starbucks, for example, recently unveiled ‘My Starbucks Barista,’ which uses artificial intelligence to let customers to place orders through voice command or SMS.

Algorithm use the input of account information, customer preferences, purchase history, third-party data, and contextual information.

This enables the coffee behemoth to provide more tailored messages and recommendations to its clients.

Dynamic industry of eCommerce

In our mobile age, the dynamic industry of eCommerce has altered the way consumers shop. Many eCommerce companies want to bring the best of an offline shopping experience to the online world by giving customers a seamless approach to find things they’re looking for.

There is a lot of emphasis on we can help on  ‘hyper customisation,’ by understanding real-world consumer behaviour and creating predictions with massive amounts of data acquired from user actions on smartphones, tablets, and PCs.

eCommerce retailers frequently use the recommendation process to assist clients in finding the best solution.

Amazon, for example, provides recommendations to users based on their online behaviours and previous purchases.

Netflix recommends TV shows and movies based on how users engage with different categories, such as drama, comedy, and action.

While eBay gathers user input on products by hand in order to propose things to customers who have shown similar tendencies.

And it’s still evolving, with a variety of permutations and combinations in play. They are already using AI to provide subscribers with personalised recommendations based on their tastes, and we expect this to grow rapidly over the next year.

Source: ecommerce business , ecommerce store

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