How AI improves the retail UX
It is no longer new that artificial intelligence has greatly changed how people go about their day to day affairs, it is changing many industries and the retail industry is not left out .
Artificial intelligence in retail entails the use of data, automation and technologies like machine learning algorithms to achieve customized shopping experiences to consumers e.g a virtual assistant gives shoppers a personalized recommendation on pricing based on their purchase history etc.
UX (User experience) refers to an individual's experience with a product, service, etc.
The main objective of UX is to analyze the responses made by users to the use of a product to improve its ergonomics, facilitate its use, make it more intuitive, as efficient as possible. It is about making a product, through its design, its architecture, its interactivity, etc., as pleasant as possible for a user to use.
AI and machine learning are usually used interchangeably by people but they are two different concepts. Machine learning is a part of artificial intelligence that enables computers to make predictions using historical data without being programmed while AI is a branch of computer science that deals with making computer systems that can mimic human intelligence, they use algorithms that can work with their own intelligence .
Over the years AI has helped businesses understand their customers preferences and reservations through their shopping history, their shopping patterns, social media behavior, it has informed businesses on ways to serve their customers better by meeting their precise needs e.g favorable pick up locations with the city, preferable flavor, most convenient price etc.
Chatbots are virtual assistants found on websites, they work round the clock attending to websites visitors . Chatbots may lack some human touch because they have no feelings and lack intuition , however they can handle customer requests instantly without sentiments or bias.
Providing personalized products recommendations creates an attachment between customers and a brand. This can go a long way to keep customers glued to a brand and help them maximize returns.
It can be very boring and time consuming for customers going through numerous pages in search of a particular product on a website, providing a high quality recommendation helps customers track their desired products swiftly and also stand a chance to spend more time shopping if they keep seeing the things that interest them. This swift experience can be achieved with a product recommendation engine. This engine is a system that uses algorithms to endorse products that can compel a customer to execute a purchase.
Re- targeting strategies is a way of keeping track of customer's web searches and using that information to remind them of things they may be interested in when they are online . Enhancing this strategy is a good marketing technique that can compel customers to buy their desired product from you.
Using AI to study customer behavior through their search patterns , their frequently visited sites and online interest helps businesses know what appeals to customers and ways to serve them better.
From the write up above it can be seen that AI has several benefits in the retail industry ranging from:
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Human intervention in the development of AI, the concept of Human-in-the-Loop.
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