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Sandeep Singh Author's Perspective
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4 Minute read

The Significance of AI & ML in ecommerce

Artificial Intelligence (AI) is continuously impacting the world of online shopping. Today, AI is changing how ecommerce stores operate and provide services to their customers. Starting from virtual buying assistance to creating personalized shopping experiences, AI is refining online shopping experience for both retailers and customers. At the end of the day, achieving a highly personalized customer experience holds the key to the success of online markets.

Let us explore how AI is transforming ecommerce and analyze how things might change in the future.

  1. Personalized user experience with virtual assistance
  2. Gartner forecasts that 85% of customer interactions to be handled without a human by 2020. In a world where quick responses are coming under increased scrutiny, a growing number of retailers are looking for effective ways to provide rapid customer service while maintaining a high-quality customer experience.

    Cloud computing firm Oracle said, "A bot is essentially a robust, interactive FAQ – but a live chat option allows the customer service team to do what they do best."

    In physical stores, human assistance is typically in hand to direct us to what we want. In ecommerce stores, they can't replace a human assistant, but they can use AI and machine learning to boost their store searches so that they can understand both long search term and customer intent.

    Amazon Alexa is making use of AI and machine learning to drive their product recommendations and searches. Amazon further uses AI to enhance its logistical operations, as AI is responsible for reroutes, change in delivery arrival times, as well as other adjustments to assure accuracy and efficiency.

    Pinterest has further pushed the envelope with the recent update of its Chrome extension - this allows users to select items in any photograph online easily and present them with similar products for purchase, thus bringing social media and ecommerce a step closer.

    While bringing in AI to an ecommerce experience might take some time, but for enhanced user experiences, you can refine your search by keeping these notes in mind: 

    Make sure that your search box is easy to find, and certainly add an autocomplete feature. This improves the search experience because it limits the number of things a user needs to do to find what they want. It also prevents misspelling and missed opportunities for both the customer and the merchant. Let the user search within a particular department too, and improve your product labelling and metadata to boost the accuracy of search results.

  3. Get hyper personalized with product recommendations
  4. AI can crunch customer behaviour on any website using algorithms to make an accurate prediction about what products our customers will like. Based on this, it makes a recommendation that a customer is more likely to act on.

    For example, Amazon uses your browser history and your purchase history, to recommend more products that you like. It is a kind of hyper personalization that customers want in the future. Apart from the ecommerce sector, Netflix is another example of how AI-driven recommendations work. Using the customer's past behaviour and preferences, Netflix recommends more shows it thinks they will enjoy. 

    To improve your own store's recommendations, display a list of suggested products that are based on a customer's past browsing history. Add a "frequently bought together" feature, as well as a "related to items you've viewed" feature.

  5. Personalized touch with Chatbots
  6. Many ecommerce retailers are already becoming more sophisticated with their AI 'conversational commerce'. The use of artificial intelligence through the application of 'chatbots' is just one way to drive the conversation in this next era of conversational commerce. Here are multiple ways chatbots can help to influence your ecommerce:  

    - Chatbots can automate order processing and are an effective and low-cost way of providing customer service. With chatbots, you are always in 'available' mode to your customer enquiries, moving out from the traditional '9:00 A.M -9:00 P.M' mode.

    Often when customers are browsing online, they are already logged onto social platforms such as Facebook. With this in mind, there is an excellent opportunity to use messenger functionality to confirm orders or to provide instant online support. 

    Also, explore the feasibility to integrate chatbots with the shopping cart. Once the chatbot system is integrated with one of your shopping carts, it can work with all the stores based on the platform. The more shopping carts that your chatbots application supports, the more potential customers it has. 

  7. Empower Store workers
  8. While online retailers have experimented with chatbots, there have been some considerations of how to replicate the helpful experience in-store.

    Lowe, a home department store, is an excellent example of this implementation. Lowe introduced the first autonomous robot a few years back named LoweBot.

    The tall shopping assistant greets customers at the door, guides them around the store, sources relevant product information and even assists employees with inventory management. This helps Lowe to free up their experienced store workers to engage in more meaningful interactions with their customers.

  9. Build an 'assortment intelligence' tool
  10. Customers are forcing retailers to change their pricing strategies. Therefore, it is imperative that multichannel retailers apply flexibility when it comes to their price structure. Retailers are turning to assortment intelligence, a tool that facilitates an unprecedented level of 24/7 visibility and valuable insights into competitor's product assortments.

    A business can monitor their competitor's product mix, which would be segmented by product and brand as well as the percentage of overlap. This intelligent tool then provides businesses with the ability to adjust their own product-mix and pricing with high accuracy quickly.

  11. Bridge the gap between personalization and privacy
  12. Whenever it comes to discussing personalization, there is often a trade-off about user privacy. User privacy has been a hot topic in recent years, with its importance considered stronger than ever.

    Brands are actively striving to take transparency, security and honesty to an entirely new level. To achieve this, brands cannot afford to abandon user personalization, given its critical role in any successful ecommerce venture.

    Users are a little more comfortable with sharing their details on the promise that they are getting something precious in return.

    For example, if we give access to Google Now to our account, it will sync with our calendars, emails and search habits. Similarly, Amazon Alexa applies the same magical approach to daily life. The modern shopping assistant puts the day-to-day routine first. Amazon added intelligence in Alexa to buy on your behalf.

    So, AI enables retailers to provide outstanding experiences throughout a user's day, even if they are not physically browsing the ecommerce store. For such an experience, users are happy to share their precious details, an excellent example of how AI is bridging the gap between user personalization and privacy.

    Let's take a look at the current work some of the companies are doing using AI in ecommerce:

    WayBlazer

    WayBlazer: This is a travel start-up, which uses an intelligent AI system that delivers contextual, personalized insights and advice for travellers, using deep learning algorithms. The company assists numerous B2B companies who plan small outings, manage hotels bookings, arrange tours, etc. They also provide this service to companies that generate revenue through travel bookings.

    USAA

    USAA: This financial services company utilizes AI to identify inconsistencies in business transactions by tracking client behaviour and identifying hidden patterns. They make use of thousands of factors to determine customer behaviour.

    UNDER ARMOUR

    Under Armour: This is a sport and fitness apparel company, which uses IBM Watson AI system. The company creates an app which keeps track of a person's health and fitness. In the future, this system aims to offer the user with individual training advice and personal nutrition information.

    knorr

    Knorr: Being a food brand owned by Unilever, Knorr uses AI application to develop recipes based on the ingredients available to the user. The application provides relevant hints to user and the company with information about what the customer needs or is looking for.

    NETFLIX

    Netflix: This is a well- known online video and media streaming website. Netflix uses AI to provide their customers with personalized recommendations. These recommendations will be usually based on what a user has watched or the online video ratings.

    Alibaba: AI is an integral part of Alibaba's daily operations and is used to predict what customers might want to buy. With NPL, a company automatically generates product descriptions for the site. Another way Alibaba uses AI is in its City Bran Project to create smart cities. The project uses AI to reduce traffic jams by monitoring every vehicle in the town.

    Amazon: Amazon uses AI to ship things to you before you even think about buying it. They collect a lot of data about each person's buying habits and have such confidence in how the data they collect helps them recommend items to its customers and not predict what they need even before they need it by using predictive analytics.

    There is another store concept called Amazon Go. Unlike other stores, there is no checkout required. The store has AI that tracks what items you pick and then automatically charges you for those items through the Amazon Go app on your phone.

    An increasing number of players in the ecommerce industry are looking at the robust and practically helpful solutions based on AI and ML technologies to reach and influence more customers, enhance the efficiency of the sales process and offer customers a high level of personalization.

Sandeep Singh
Sandeep Singh Commerce Practice Lead


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