Ecommerce companies in the recent past had to rely on their own intuition to understand customer’s buying behaviour to make key business decisions. Even though companies were tracking historical data on the customer’s online journey, they didn’t know how to use this data to their advantage. Today, if your business is trying to gain a foothold at a time when even the smallest of companies are selling online, you will have to sell efficiently on the internet.
The real game-changer in ecommerce came with the recent rise in artificial intelligence (AI). AI has progressed to a point where it has become an essential part of this industry. AI technologies have the ability to demonstrate intelligence that involves emotions and consciousness. With the combination of machine learning (ML), businesses can use algorithms to find patterns in large amounts of data and improve the recommendation system on their website and thus, strengthen the customer experience.
Hyper-personalization with predictive AI based analytics
According to a study by Adobe, although 83% of marketers said that they were familiar with machine-learning solutions, the application remains low, with only 14% of respondents saying they were using them.
In general terms, personalization is another name for recommendations, however, there are a lot of possibilities in personalization. For example, an ecommerce website showing simply the customer’s name after login is one form of personalization. Another example is showing separate landing pages for men and women. While personalization might include a customer’s name in emails or online ads, hyper-personalization involves more parameters like browsing and purchase history and other real-time behavioural data which is more complex as it goes beyond basic customer data. For example, hyper-personalization would include ads showing trekking gear based on the exact location where it was last purchased including payment method, applied coupons, social media activity and more. AI based predictive analytics play a huge role in a customer’s interactive buying process, it also is the driving force behind relevant and lead-generating campaigns.
Let’s take a look at some other important uses of artificial intelligence (AI), and machine learning (ML) in ecommerce and their role in improving growth and personalization:
Drive product recommendations
The use of recommendation engines has become a significant part of ecommerce businesses; the best examples of a recommendation would be ‘customers also bought’ on Amazon or ‘people you may know’ on Facebook. This is possible with the help of a recommendation engine or system. A recommendation system is a tool used by companies to foresee a customer’s choice of product amongst a long list of suggested items. AI can deliver suitable suggestions based on a customer’s preference. AI, along with ML uses vast amounts of data to offer products they would be interested in, and data here encompasses a lot of things: images, clicks, numbers, words etc. Once all this data is stored digitally, it can be fed into a machine learning algorithm to generate suitable recommendations to the customer.
AI based chatbots for customer service
In an age of conversational commerce, any successful ecommerce business will most likely have AI based chatbots and voicebots on their online platform for driving sales and customer service. AI based chatbots and voicebots, which are powered by natural language processing (NLP), help in assisting customers at different stages of the sales and marketing funnel. To ensure a seamless customer experience, the integration of these assistants is essential for engaging customers. As per a report by Gartner, by 2021, more than 50% of enterprises will spend more per annum on bots and chatbot creation than traditional mobile app development. AI is capable of reducing the workload of customer service agents, as chatbots and voicebots can answer a majority of standard questions and increase the response time. They additionally aid in following a customer-focused approach. With accurate data and insights at their disposal, ecommerce businesses can understand the trends in sales and tackle issues such as abandoned shopping carts, collect first-party data, and notify about promotions and deals which help in humanizing the brand. From making initial contact to answering simple script based FAQs, these AI based agents add to the company’s credibility.
AI visual search and image recognition
A picture is worth a thousand words; an ecommerce product picture is perhaps worth millions to any ecommerce company. Many a time customers see a new product, however, when it comes to describing it they get stuck. Ecommerce websites have improved their interface with accurate text-based search, but many customers might not be aware of the vocabulary that adequately describes a product; we as humans are visual beings after all. It is for this reason that voice and image based search has picked up and will transform the customer experience of a company radically. According to a report by Gartner, ecommerce businesses that implement visual and voice search will increase their digital commerce revenue by 30%. With AI based visual search, customers can simply take a snapshot of the product and search online. The AI powered ecommerce platform can quickly identify the product and line up a list of similar products, turning the virtual world into a shopping catalogue. Visual search is capturing the customer’s attention slowly, as AI based visual search gains maturity, companies have started putting together a gallery of images to be at the forefront of the search engine results. Many ecommerce websites are using a customer’s product preference and with the help of AI, they are able to show a product the way a customer wants, with ease.
Catalog classification using AI and ML
Customer experience is the ultimate factor that separates successful companies. Having a simple ecommerce website will just not suffice. To ensure superior customer experience, ecommerce companies must provide an exceptional shopping experience. To accomplish this, the creation of optimized catalogs that cater to the exact needs of the customer is imperative. Buyers today research online, browse offline and purchase on a website that offers a seamless shopping journey. AI and ML advancements in retail cataloging help in the classification of catalogs based on-demand analysis, local preferences, buying habits and new trends. AI based product catalog management takes care of automating workflows such as product listing, product identifications, and price competition checks. By looking at historical sales, promotions, weather patterns and season, AI can help businesses create an optimized catalog by predicting future demand. The goal is to unify in-store and online.
The buzzword is AI. Soon, personalized online experiences powered by AI will become a basic expectation. Hyper-personalization is here and will remain. IGT has been helping top companies to drive success to their business by delivering a super personalized customer experience.
We have been creating opportunities by leveraging AI/ML to generate models to solve complex business problems with the right mix of robotics and humans. By augmenting decision-making based on vast and complex datasets, millions of variables/unstructured data and enormous distributed computational capacity, AI/ML plays a key role in providing new business outcomes. These technologies have disrupted the traditional way of marketing, customer insights and engagement.
Gurmeet Oberoi is a researcher and writer of change tactics and technologies in travel and other verticals, she frequently posts across the digital ecosystem. With 9-yrs of experience in communications and marketing, Gurmeet has a passion for travel and reading among other things. She can be reached at firstname.lastname@example.org