Artificial Intelligence systems are growing at a fast pace. Experts suggest that in few years you will see AI in every business segment, including marketing and sales. Due to the high-importance of AI, many e-commerce businesses have already started integrating AI in their marketing strategies and sales methodologies. Here, we will share practical and powerful ways where AI can be used to make ecommerce apps better.
Custom centric search
Though technology plays an important role in our lives, we still love the human element in everything we do. A large number of people abandon e-commerce experiences because the results displayed in search are not relevant. AI can be used to improve e-commerce search and tackle this problem. According to experts, machine learning can be leveraged to help AI software automatically tag, organize and visually search content by labeling the features of video or image. Ecommerce companies need to build bespoke systems which can be used to teach Artificial Intelligence software any concept, no matter whether it’s product, logo, or aesthetic.You can use these models to search media assets using tags or visual similarity. The AI powered visual searches are enabling online shoppers to discover complementary products that have similarity in color, size, shape, fabric, or even brand. With AI integrated in ecommerce apps, customers need not search by typing keywords but they can use visuals/images to find something similar in e-commerce stores. For example, if they like their friend’s dress or shoes, they can find something similar for them in e-commerce stores.
Retarget potential customers
According to a leading research, 33% of leads are not followed successfully, and a large number of pre-qualified potential buyers fall through the cracks of the sales funnel. Today, businesses are overloaded with customer data, but that is seldom put to good use. The data is a goldmine of intelligence that can be used to enhance sales cycle. For example, if a customer spends a notable amount of time browsing through a certain category of products, that information can be used for their next visit. When the consumer opens the ecommerce app next time, the e-commerce stores can flash special offers on the category of items based on customer’s dwell time.
Create efficient sales process
Today’s customers are heavily influenced by different streams of media and you need to understand your customer better before offering custom-made solutions. You can embed AI in ecommerce apps in order to ask right question to the customers. For example, if the customer is looking for a jacket, AI can be used to frame questions like where and when the customer will be using the jacket. Based on real-time customer research and weather conditions, the AI can list suitable jackets that will help the customer take the right purchase decision in lesser time. AI can be used to ensure the customer is always shown appropriate products and customers don’t spend time and energy in irrelevant searches.
Create a personalized experience with mobile devices
Today’s customer uses multiple channels to complete a purchase. For example, the customer may browse the products on a larger screen (desktop or laptop) and complete the purchase on mobile device. Ecommerce companies need to embed AI in every platform to ensure a consistent and personalized experience for the customer. They need to use the AI engine to monitor customers on all platforms, devices, and channels, create a universal view that will help in delivering seamless experience to customers. For example, if a customer is browsing iPhone cases on your website, you can send a push notification on the mobile informing about a flash sale for iPhone cases. This will remove several steps in the sale process and enable the customer to complete the purchase faster.
AI can be used to predict a customer behavior by scanning the browsing data. It can be used to make meaningful, relevant, and helpful recommendations. This can help in personalizing experience for the customer. The AI algorithm uses a variety of inputs including user preferences, account information, purchase history, contextual information and data from 3rd parties to deliver more personalized suggestions.
AI tools available for mobile apps
There are several machine learning APIs that can be integrated into mobile platforms and reap the benefits of AI. Here is the list:
The popularity of virtual assistants has made voice recognition technology more relevant. The AT&T speech API delivers speech recognition capabilities to the mobile app. It is powered by AT&T Watson speech engine which is natural language understanding and speech recognition technology. The AT&T speech API has the capabilities to convert voice into text and vice-versa that further refines the custom centric search and deliver relevant results.
IBM Watson is a combination of machine learning with cognitive computing. IBM offers a range of APIs that can be utilized to embed machine learning capabilities in mobile apps. With IBM Watson API integrated, mobile apps will have the capability of natural language processing, prediction, and computer vision. The IBM Watson API suite includes speech to text and vice-versa, personality insights, question and answers, trade-off analytics, visual recognition and tone analyzer.
The Google Prediction API gives access to machine learning capabilities including recommendation engine, prediction, pattern recognition, and natural language processing. The Google Prediction API comes with getting started page, code samples, client libraries, and API documentation guide.
Who is already using AI in ecommerce?
Large ecommerce retailers like Amazon are using AI in different ways to boost e-commerce and make it safer. Amazon uses machine learning in making recommendations based on browsing pattern. The global retailer also uses AI to know whether the customer will become a paying customer based on their activities during the first week/month. It also uses AI to detect spammers, bots and fake users based on their activity records.
Netflix also uses AI to know what you want to watch before you watch it. The AI algorithm used by Netflix learns from user actions. For example, imagine you watch the first video of a series but you don’t like it. You are generally asked to give your feedback after watching content on Netflix. If you rate it low, Netflix draws a conclusion that you won’t be interested in watching the second episode and you don’t like that kind of shows. Hence, it will keep such shows far away from your recommendation list.
There is no doubt that Artificial intelligence is allowing ecommerce businesses to provide more personalized experience to customers. AI has made it possible for businesses to analyze millions of customer interactions on daily basis and to give personalized services to prospective customers. It has also helped businesses engage customers at the right time by delivering the right message. AI technology is likely to have a tremendous impact on e-commerce in near future. It will play an important role in helping customers find the best products online. As a professional mobile app development agency, we at Promatics Technologies Private Limited have delivered AI-based solution for ecommerce and other apps and have seen a tremendous increase in user satisfaction.
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