Top 10 Uses of AI in E-Commerce
The growing popularity of artificial intelligence technologies in e-commerce is not surprising. The number of buyers is growing, their requirements and requests are becoming more complex, and it is becoming more and more difficult to maintain a consistently high customer satisfaction rate. Therefore, modernizing and automating most e-commerce processes has become a necessity. The good news is that 35% of retailers plan to invest more in artificial intelligence for their e-commerce operations this year and the International Data Corporation forecasts that spending on AI technologies across industries will grow to $97.9 billion in 2023.
Since investments in AI for e-commerce are growing we need to understand how online retailers are using these technologies and the benefits they offer. Today we will tell you about the top ten use cases for AI in e-commerce.
1. Providing Personalized Recommendations
Personalized recommendations are very effective in driving overall sales. In fact, if we look at the success Amazon has had with its AI-powered recommendations, they rely on their algorithm to drive 35% of total sales. The reason this is so effective is because these recommendations personalize the entire shopping experience making it easy to find the products people are looking for faster.
Such AI algorithms require a significant amount of data annotation since the system needs to understand which criteria or features it needs to look for in the data. Therefore, human data annotations would need to prepare the training dataset by labeling all of the data the system needs to learn.
2. Helping to Fight Fake Reviews
Customers rely on online reviews from real customers to make a purchasing decision about a product, but, unfortunately, a lot of scammers place false reviews that often trick the consumer. They can also spread false information about the product as well, which can cause monetary and reputational damage. This is why many e-commerce platforms use AI algorithms to identify such fake reviews and take them down.
3. Last-Mile Delivery of Products
Last-mile delivery is about optimizing time and itinerary for the final step of the supply chain. AI has the power to collect and analyze the mapping and geolocation to provide the most efficient, convenient, and the quickest way for transport. However, AI can go a level beyond and power robots to deliver products without human assistance. We are already seeing companies like Nuro and Amazon experimenting with such robots at limited locations around the US.
4. AI Chatbots
There are many reasons online retailers love chatbots. First of all, chatbots help business managers cut operational costs by 30% and 34% of retail customers prefer a chatbot to a human agent. Also, chatbots are always available, they never get sick and don’t need to take a break. They use machine learning to identify communication patterns. Through constant interaction with people, they learn to imitate real conversations and respond to verbal or written requests, helping to find answers. Because chatbots use artificial intelligence (AI), they understand language, not just commands.
5. Extracting Insights From Data
While you may have lots of customer data, you need to be able to extract the needed business intelligence from it. This is where AI can be of great assistance since it recognizes patterns that would otherwise go unseen by humans. It can also analyze large volumes of data to make forecasts and improve decision-making.
6. Auto-Generated Product Descriptions
Creating content is a very challenging and time-consuming process, but fortunately, AI can help out here as well. In fact, it takes about 18 months to complete 10,000 descriptions while AI content generation tools could do it in a few hours. Also, it can also analyze the content of product descriptions of the most widely sold items and come up with a perfect description to address the interests of the buyer.
7. Enabling Visual Search
A lot of times customers see an item on social media or another website that they are interested in, but they don’t know the name or how to search for it. Even if they did, it would be difficult to find a store that sells that particular item. With the help of AI-powered visual search, customers can search for items by uploading an image. Amazon has already added such a feature called StyeSnap which recognizes photographs with artificial intelligence.
8. Virtual Try-On
With personalized items such as clothes and makeup, it can be difficult to make a purchasing decision without trying them on. Many retailers are using facial recognition and other technology to detect facial features and allow them to try on the product in AR. The same is possible with clothing and shoes as well.
9. Warehouse Automation
When online retailers receive an order, this sets many processes to fulfill the order. Fortunately, AI can help with many warehouse processes such as simply removing items from the shelves and detecting any damage or defects. This also allows retailers to better manage their inventory and make sure that they are able to deliver orders on time.
10. Marketplace Moderation
Just like you need to make sure that people are not posting fake product reviews, you also need to ensure that only real sellers are posting fake or unsafe items. This is actually a big problem many websites are grappling with. In fact, a Wall Street Journal investigation found 4,152 items for sale on Amazon.com Inc.’s site that have been declared unsafe by federal agencies, are deceptively labeled, or are banned by federal regulators—items that big-box retailers’ policies would bar from their shelves. They also identified at least 157 items for sale that Amazon had said it banned, including sleeping mats the Food and Drug Administration warns can suffocate infants. Therefore, you always need to moderate the marketplace to make sure that only safe and authentic products are being sold.
Trust Mindy Support With All of Your Data Annotation Needs
Pretty much all AI technologies mentioned above require one form of data annotation or another. However, we understand that this is a very time-consuming task, which is why you should consider outsourcing this work to Mindy Support. We are one of the largest BPO providers in Eastern Europe with more than 2,000 employees in six locations all over Ukraine. Our size and location allow us to source and recruit candidates within a short timeframe and we will be able to scale your team quickly without sacrificing the quality of the data annotation. Contact us today to learn more about how we can help you.
June 18th, 2021 Mindy News Blog
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