12-ways AI is revolutionising the entire eCommerce industry

12-ways AI is revolutionizing the entire eCommerce industry




Tired of hearing terms that you think make no significant difference? 

Well, they do. 

The way AI established its paws in every industry, you may only equate it to the way cellphones had made it to everyone. But why does AI as a concept sound so complicated? Because we have not been well acquainted with the analogies, algorithms that go behind, and the results they produce. 

So, to burst the bubble, we decided to dive into the nuances of AI technology in the eCommerce industry. For a major portion of the time, eCommerce stood alien to the concept of incorporating AI technology into their sites. It was when Google and Amazon started taking advancements with Snapshot or Google Lens to provide a better visual search experience. 

This is still from a mature year where eCommerce was taking major steps toward personalization. It is estimated that by the year 2021, eCommerce would result in a whopping $4.88 trillion business. 

So, why do we need to ignore the simple search and merchandising techniques for our sites? Because the AI concepts and use-cases in the eCommerce industry are still nebulous. To differentiate, AI is not only about automation but it is much more than that. AI uses its technology to read and analyze data using Machine Learning algorithms to detect problems, find solutions, and simplify the ways to curb them.

But how? 

Exactly what we have tried to understand and found 12-ways in which AI is going to revolutionize eCommerce search in 2021:

  1. The Personalization Game: The only missing part from the brick-mortar to click-buy journey was the personal touch of a sales concierge. So, eCommerce search inculcated AI techniques based on behavioral and transactional algorithms fed to them by machine learning algorithms. Based on such algorithms and clickstream behavior, eCommerce stores are more likely to provide personalized shopping experiences to their shoppers.

    For instance, Jake is searching for tools and parts for his newly bought Harley ‘Heritage classic’ model. He made a similar search on 4 websites but only purchased it from one of them. Why? Because the site had enabled personalization which welcomed Jake with an oil wrench for his Harley’s ‘Heritage classic’ model. He was sold at this idea itself. 

  2. Providing Recommendations: 31% increase in the no. of customers! Researchers found that just by integrating recommendations to their site there was a 31% increase in the customers by the year 2018. Recommending relevant products to shoppers along with the purchase journey about your customers’ preferences, improve the chances of getting more sales.

    Recommendations follow an interesting analogy behind the ‘Diderot’s Effect’. It is a term used in customer psychology stating that people tend to feel dissatisfied when they see a product alone and not the similar brand or product recommendations.
    Merchandisers with successful eCommerce sites started selling more through ‘Complete your Look’, ‘More like This’, or ‘You may Like’ for their shoppers’ search history, clicks, baskets, or queries. When AI started displaying recommendations, customers crawled toward buying more similar recommendations.
    For instance, Sandy searched for a pair of an overcoat when she zeroed down to one final product, the AI recommended a pair of brown boots to go with the coat. With Diderot’s Effect right in place, Sandy buys the boots to complete her look. Unbxd, as an eCommerce search provider, feeds the algorithms by tracking the shoppers’ data to recommend them personalized suggestions.

    The recommendations are based on the following scenarios:
    – Products previously bought by the customer
    – Products previously rated (products the customer likes)
    – When does the customer buy a product? – When does the customer rate a product?
    – When does the customer like a product?

  3. Better visual search: How many times have we crushed over a celebrity dress and searched for it online? But to no results, right? To solve this problem, the eCommerce industry adopted AI technology to understand consumer behavior even with visual searches.
    Amazon launched its AI-program ‘Shazam for clothes’ and ‘Stylesnap’ which is a fashion AI technology that displays results for a picture as a search query. Amazon joined the bandwagon later when sites like Screenshop and Google lens had already taken over the market. 2021 would bring better visual search technologies that would let you display a 3-D look of the products. The more visually appealing your products look, the more customer attraction you generate.

    Style.me, launched its 3-D look of the products which allowed the customers to try their clothes virtually. The body type, measurements, and styling are taken in as input and the final look is displayed to the customers.

  4. Effective Voice search: Alexa and Siri have disrupted the voice search market. Since then, a lot of viral content (podcasts, audiobooks) accompanied and the power of voice search slowly unpeeled. These are technologies embedded in minuscule tools, listening to your voice commands and acting upon them. Although the commands are not 100% efficient, voice searches have made searching for your favorite song, dress, or even reducing the volume or adjusting the lights to the mood, one command away.

    Even for the eCommerce industry, Walmart collaborated with Google Search Assistant to keep a track of the product stock or re-arrange them. Not so surprisingly,  the voice search market is all set to do $40 Billion in sales by 2021. Integrating voice-search broadens the ways you could listen to your customer choices.
    For that, Unbxd provides personalized answers for customers’ commands using the functional chatbots. A few tools that could help you build creative chatbots are Google’s Dialogflow, Manychat. They help simplify the process, prepare flowcharts to understand customer chats and automate the entire query resolution process.

  5. Adjust the Pricing based on Customer Behavior: Placing a static price for products refrains from knowing how effective dynamic pricing can be. To enable dynamic pricing, you need to apply machine learning algorithms to the customer data which includes a variety of sources like postal code and loyalty cards. By analyzing this data, you can extract which customer cluster will pay more or which will be more responsive to the offers.

    Dynamic Pricing Strategies predict customer behavior, current prices, and competitive prices as well to dynamically set the price of products. This way the AI tech also helps to keep stock management of the products automating the demand and supply cycle. This is going to be another game-changer for eCommerce stores to stay ahead of their competition. Better AI, would then mean better services, and better customer acquisition.

  6. Sniff the bad guys: The eCommerce industry suffers the wrath of security breaches. Reportedly, it is estimated that by the year 2023, 33 billion records would be breached and it takes almost 196 days to recover the breached data. Surprisingly, this number is for the US alone and not many companies can afford this number of breached records which is a serious concern in the eCommerce industry.

    In such cases, Zimperium and MobileIron announced a collaboration to help organizations adopt mobile anti-malware solutions incorporating artificial intelligence. The need to handle millions of customer data including their personal details, payment information, and already fed sign-up details becomes a responsibility for the eCommerce merchandisers. The probability of losing out on data could prove hazardous. So, AI technology brings in its ways to conform to the security norms. AI tech closely analyzes data and makes decisions in real-time by calculating the risk score.

  7. Hyper-automation: The eCommerce industry can make the best use of the AI tech by hyper-automating the entire warehouse. For instance, Amazon alone has 175 fulfillment centers globally, where millions of orders are ordered, placed, and shipped. For such a big store to function, decision logics and optimization algorithms are put in place to track the orders received every second.

    All such scenarios are addressed by machine learning algorithms which make the entire process easier. Every order is tracked from source A to source B using machine learning algorithms. AI has made the entire inventory update journey as simple as it is for customers to buy the products.
  8. Feedback and reviews via chatbots: Do you remember the last time you enquired about your order via a chat system on a site and received an instant reply?
    Sarthak from India was ordering his food online via a local app Swiggy. His order took almost 1 hour for the order to deliver. In such a case, Swiggy’s chat assistant (chatbot) took Sarthak’s query in and updated him with the order arrival time along with the GPS location tracker. We have slowly abandoned the entire chat system where people needed to wait for a human customer support person for a single query.

    You can create chatbots using tools like Google’s DialogFlow or Manychat and integrate them with your site. In fact, the AI-powered prompts resulted in a 61% uplift in the prevalence of suggested topics in customer reviews.

  9. Push the product even before the customer searches for it: Potential customers are targeted when the AI technology tracks the user personas and displays the ‘most likely to be bought’ products. It is almost like you searched for ‘Sunglasses’ and all the potential social media websites start showing results related to sunglasses.
    Coincidence, isn’t it?
    It is actually the AI tech at work that is handling the entire tracking and providing similar results on all the social media platforms. As eCommerce merchandisers, try to build a strong customer relationship by leveraging NLP algorithms to cater to them wherever they go.
  10. Future sales prediction: Imagine an upcoming discount sale that might see an incredible hike in sales. Irrespective of the demand, keeping up with the inventory is a merchandiser’s nightmare.

    During sales, it is difficult to track the approximate sales of a product during season or peak time. AI helps in tracking customer behavior which could predict their chances of buying a product and increases sales. According to data, AI made around $47 billion in 2020 and is expected to reach up to $49 billion by 2021. If the AI community brings in such results, why not leverage it now for your eCommerce business?

  11. Automated product descriptions: Filling in the correct product details is the way to build a proper eCommerce website. But often the product descriptions set unrealistic expectations because of the error-prone detailing.

    According to Neilson Norman Group’s eCommerce report, 20% of the product failures happen because of insufficient product detailing, misleading information, or no product description. To build a good product description, you need to have:

  • a precise description
  • brand name for multi-brand retailers
  • the model name 
  • the Category and Subcategory of the product (to fall down to the niche)
  • any key attribute
    The hardest part of writing product descriptions is the efficiency to look over if all the points have been covered. AI tools like Quill, Content Spinning Software, automate the entire process of creating product descriptions using NLP algorithms. Read here how AI can change the entire product discovery game.

12. VR and AR tech: Imagine, entering into a site with “Try before you Buy”.  The chances that shoppers would abandon the site without buying any product declines sharply. Virtual reality and augmented reality are the two new lenses in the eCommerce industry. They make eCommerce sites display products in 360 degrees, with more clarity, and in real-time to test out.

AR and VR provide a different way to let the customers into the entire process of online buying. 78.65% of customers abandon their cart even before placing their order which speaks a lot about the changes needed. So, AR and VR took over and AR glasses were priced at $1.2B in 2018. 

For instance, IKEA started product displays using VR technology which allowed customers to test out products in real-time. Dave was amazed at how he was able to test out the mattress before buying it from IKEA online. Many fashions, furniture, and marketplace people started using AR/VR tech to display their products from every angle. Customers trust you more and would buy often. 

With Covid situations in place, people will flock for a virtual shopping experience more than ever. Many companies like Style.me, Zeekit (in Israel), BrandLab have started providing virtual shopping experiences and gaining profits through it. Since major companies like Arcadia are set to cut down almost 500 jobs due to the pandemic, the opportunity to manifold is now. Even though stats like these don’t define the exact picture of retail business but it definitely is going uphill. So, the early adoption of AI technology to create a store for your customers would go a long way. Let your customers feel the product with utmost details, 3-D visualization, and maintaining stocks. 

The year 2021 is a lot about personalization, let’s make more out of it! If you feel lost about where to start from, contact us at Unbxd! 

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