The e-Commerce boom has catalyzed the process of ‘evolution and reinvention’ within the international retail industry. Euromonitor International has predicted that Internet retailing is the fastest growing global channel through 2022.
Retail is one of the flagship sectors where big data plays a vital role, and technologies powered by artificial intelligence, machine learning and deep learning bring in a huge scope for efficient and cost-effective business operations.
According to a recent study, 45% of retailers plan to adopt artificial intelligence in the next three years to enhance their customer experience. While retail giants like Amazon had initiated the use of these technologies, more brands are steadily incorporating AI-powered services to enhance their customer experience.
Here are some of the retail business processes where the new-age tech can drive growth:
Understanding consumer behavior through query: The retail industry is a highly competitive and an evolving industry. With the rise of e-Commerce sites, there is an increasing need to understand consumer behaviour, preferences and changing demands at an individual level. Machine Learning can assist retailers track a consumer’s regular shopping pattern, understand their choice and make it easier to read a consumer’s requirement by providing that service or product.
Using AI, machine learning and deep learning technology, a retailer can also detect suspicious behavior, gather broad information about demographics and behavior patterns in-store.
Predicting future demands, pricing and maintenance of stock:
AI helps in social media listening which is significant for e-retailers who want to understand consumer shopping habits, predict product demand or monitor trends.
Machine learning allows retailers to deploy sales and customer service staff where they will be most effective. They can further assist in optimizing pricing strategy taking into account key variables like supply, seasonality of demands, and inventory adjustments.
Deep learning techniques also has the potential to change how retailers buy, stock and sell products by accurately predicting the item a customer wants, and in turn, could greatly improve efficiency in the online retail environment.
Unstructured Data to Value Assets: Free-form messages and search queries come in huge volumes. A new IDC study, 80–90 percent of all digital information comes in the form of unstructured data, which are sources of invaluable insights as far as business intelligence in concerned.
With the rate at which the volumes of unstructured data are rising in the market, it is wise to convert those into assets which can further be used to have more conversions. With the help of AI, Machine Learning and Deep Learning Techniques this is a task made easy. As per data, 89% of retailers are now using social media comments as a critical customer satisfaction measurement, up from 59% last year.
Customer Service Using Virtual Assistants & Bots: Conversation interfaces like chatbots and intelligent virtual assistants, helps in personalization, consumer engagement, and provides 24-hour-service.
Empowered with Natural Language Processing, chatbots have human-like understanding and behavior which can help customers get easy, uninterrupted customer service while providing retailers with reduced average handling time and eliminating customer call wastage process.
Virtual Assistants like RINA iva are trained to understand customer behaviour and patterns to provide human-like assistance.
Web-content optimization: The rise of the Internet and social media has drastically changed the way consumers shop and interact with brands. The sheer scale and intensity of customer communication can be overwhelming.
E-commerce companies enjoy a large base of customers who increasingly express their needs, attitudes, preferences and frustrations online. The machines powered by AI and Deep Learning can personalize online experience of users taking into account factors like consumer location, purchasing history, and demographics. This can optimize and narrow down search results for users. They can help retailer segment potential customers through behavior analysis.
The retail business, as an industry, is predicted to contribute nearly one-third of the growth of the text analytics market. This is due to high rate of consumer interactions involved in retail. Add to that the rise of e-commerce and social media, coupled with AI, Machine Learning and Deep Learning, the scope is huge for retailers to enhance business, enhance customer satisfaction and maintain their bottom-line.