How These 6 Ecommerce Companies Use AI To Power Their Sales

158

Whether you want to streamline your sales process, capitalize on business leads with on-point marketing sequences, or spot the next consumer trends as they develop, the capacity of artificial intelligence to facilitate core business strategies is immense.

It is predicted that by 2020, over 85 percent of business interactions with customers will be handled entirely by AI, yet this is far from the only application of intelligence algorithms in ecommerce. After all, the value of AI lies within its ability to efficiently and accurately complete tasks that would be extremely complex and time-consuming if handled manually.  

Predictive analytics enable businesses to develop proactively rather than reactively, by identifying shifts in buyer behavior. Meanwhile, machine learning systems are able to optimize the consumer experience by building detailed taste profiles and delivering highly personalized marketing communications. Even Microsoft lists AI as its top priority, replacing mobile. 

This technology can also be used to conduct smarter searches, improve transaction security, and provide meaningful insights based on your business analytics. The list goes on, but here are a few of the ways that six online enterprises incorporate AI technology into their business models.

1. Shop Direct

With the help of IBM’s famous cognitive system, Watson, Shop Direct became the first UK retailer to launch customer service platform powered by a conversational user interface  (CUI). This technology is the foundation of an AI-powered customer service platform, intended to operate as a fully automated, natural language, support system.

Often termed “chatbots”, these systems are able to communicate effectively with customers, answer their queries, and offer a range of support services. Using machine learning to develop increasingly more sophisticated conversational capacity, chatbots have become one of the most popular forms of AI to be embraced by online businesses. Here’s what bots can (and can’t) do for your online store 

In addition, Shop Direct also uses intelligent algorithms to detect waning consumer engagement, track individual preferences, and pick up signs of fraudulent activity by tracking patterns within their transactional data.

2. Netflix

While many businesses use recommendation algorithms to drive consumer engagement, Netflix applies this technology with particular effectiveness. Recommendations are interspersed with items outside the user’s known preferences, allowing the system to gauge interest in previously unrated genres, and make more accurate predictions. On top of offering smart recommendations, Netflix uses image recognition and video encoding solutions to enable to enable quality video streaming even at lower bandwidths. This technology, dubbed the Dynamic Optimizer, individually compresses each video frame just enough to allow it to stream more smoothly, without degrading the quality of the image.

This also improves streaming quality on mobile devices, and caters to audiences who may be subject to data caps, giving the company access to a much wider market, and building its reputation for quality of service.

3. Amazon

In addition to being another ecommerce business that benefits from the use of recommendation algorithms, Amazon has also embraced natural language processing (NLP) and machine learning technology to create Alexa. Like many virtual assistants, Alexa can respond to questions, act on voice commands, and even place fast food orders. Other functions include music streaming and home automation.

AI also powers the company’s drone initiative, Prime Air, and their new shopping initiative, Amazon GoVia a combination of deep learning, computer vision, and sensor fusion technologies, consumers are able to browse and collect products from a physical store, without needing to go through a checkout. All items are tracked in a virtual cart, and the buyer’s Amazon account is charged for the appropriate items after they leave the store.

4. Rakuten Using the Qlofune AI engine, Rakuten’s AI customer service solution, Rakuten Card, offers 24/7 responses to customers with queries about their credit or debit cards. With a combination of machine learning and comprehensive databases, the customer service solution can handle all major queries, including answering questions about card limits, and providing advice on the actions to take if a card is lost or stolen. Rakuten has also teamed up with IBM Japan to develop  the Rakuten AI Platform, an intelligent customer support system, using chatbots powered by APIs from IBM’s Watson.

5. Stitch Fix The broad expertise of their data scientists enables Stitch Fix to continuously explore new applications for their developing technologies. They describe their use of intelligent algorithms as “empiricism woven through the fabric of an organization”.

This online styling service uses a range of sophisticated AI technologies to power each area of their operation, from human computation and algorithmic fashion design, to inventory and resource management, and targeted recommendation systems.

This combination of tools enables the business to automatically select and deliver items to customers, which they then have the option to purchase or return. The selections are carefully targeted according to individual Style Profiles, initially completed by the customer, and then developed according to their browsing and buying habits.

6. ASOS Online fashion  retailer ASOS has taken cues from recent advances in computer vision technology, to develop a visual search feature for their mobile app. Having determined that the majority of their sales and orders came from mobile devices, the company has integrated new functionality that allows users to upload photographs as search queries.

Using feature recognition to identify key characteristics such as color, style, and pattern, the app then searches for items that match or are similar to the item pictured. By facilitating the search process, and eliminating the challenge of describing an item in text form, this technology encourages buyers to compare potential purchases with items available through ASOS. Not only does this drive sales, but also increases consumer confidence by providing a greater sense of agency over their purchase choices.

New advances in AI technology are being made all the time, so the capacity for businesses to tune in to consumer needs will continue to grow. Of course, the same can be said for customer expectations; as quality recommendations and sophisticated chatbots become the norm, AI optimization could become a critical part of business development strategy.

Nevertheless, as the development and integration of intelligence technology becomes more readily accessible, this does not mean smaller businesses will be left behind. In fact, there are already many widely available tools, from fraud-prevention algorithms to recognition enginesoffering sophisticated AI solutions for businesses of all sizes.

  • By Victoria Greene, an ecommerce consultant and freelance writer.

Learn more at Victoria’s blog VictoriaEcommerce.