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The Future of Shopping: Natural Language Processing Applications in E-Commerce

NLP the “next frontier of e-commerce”

As brick-and-mortar stores continue to adapt to the rapid rise of e-commerce, many retailers are using cutting-edge technologies to enhance the online customer experiences and edge above the competition.

Natural Language Processing (NLP) is at the forefront of these adopted technologies. In fact, NLP is destined to become so crucial to the online experience that the head of AI at Capillary Technologies, Dr. Subrat Panda, described it as “the next frontier of e-Commerce”. Understanding the applications and uses of natural language processing and other AI-enabled technologies could be the difference between success and failure for modern retailers. AI in retail is an important trend for retailers to watch.

While physical stores provide retailers with plenty of opportunities to engage with customers and enrich the shopping experience, e-commerce requires a more creative and out-of-the-box approach to build brand loyalty. Not only does NLP offer exciting opportunities to bridge the all-important gap between in-store and online shopping experiences, it also helps to cut costs, increase basket spend, and boost customer satisfaction. This is especially important on big shopping days of the year, particularly Black Friday and Cyber Monday.

Join us as we explore the applications of artificial intelligence in e-commerce and how NLP innovations could shape the future of online shopping.

How Ai and Natural Language Processing Can Be Used in E-Commerce

Implementing NLP to improve the interactions between humans and machines presents retailers with exciting opportunities to capture the elements of in-store shopping that many customers desire.

While we’re yet to scrape the surface of how NLP applications could change the way we shop, some of the world’s largest online retailers are already exploring how they can combine AI-enabled tech to revolutionize online experiences.

Additionally, organizations that typically fall outside of the retail sector, such as IBM and Yahoo Japan, are investing in NLP technologies to ride the wave of e-commerce growth and tailor their services to help shoppers make better purchasing decisions.

So, let’s take a look at some of the most promising applications of AI and NLP in e-commerce.

Stop, Analyze, and Listen, AI’s Back with a Powerful Invention

One of the most significant drivers for brand loyalty in retail is the opportunity to create a sense of personalization for customers.

Whether it’s distributing old-school coupons to offer customers discounts on their favorite products or using targeted Facebook ads that strike a chord with specific age-groups, tailoring your interactions with customers is vital to making them feel understood.

Crucially, NLP presents retailers with a powerful analytical tool to build sophisticated representations of customers through social media listening. So-called ‘social intelligence’ in the context of NLP refers to understanding the precise needs and wants of your customers to deliver tailored communications that put them at the center of the equation.

The ability to interpret huge volumes of text and bracket customers into detailed customer segments opens doors to a world of opportunities for retail marketers to engage with customers and offer hyper-personalized communications that cement brand loyalty.

Ultimately, customers don’t want to feel like they need to search far and wide to find a brand that understands who they are and what they want.

AI in Online Shopping: Virtual Assistants & Chat-based Product Recommendations

While brick-and-mortar retailers can employ in-store assistants to answer customer queries and offer personalized shopping advice, most e-commerce sites lack the human interaction that many shoppers desire. NLP offers exciting opportunities to create life-like touchpoints that mimic human interactions.

Director of Machine Learning at DefinedCrowd, Christopher Shulby explains how “retailers can use analytics to understand customer preferences and provide personalized product recommendations within a chatbot window to increase basket spend and save customers valuable time.”

The ability to simulate similar sales tactics to those used in physical stores through virtual avatars or pop-up chatbots can help online retailers improve conversions and give customers a reason to shop at your site over competitors. As pricing becomes increasingly competitive in today’s online marketplace, offering unrivaled convenience or customer engagement can help you find your USP.

IBM’s ongoing research into the use of NLP to determine the quality of a seller is an example of how language processing can help businesses add value to online experiences and boost brand equity. IBM’s technology analyzes the sentiment and emotion of customer reviews to capture deeper insights on customers’ feelings about specific products.

Efficient Customer Support

Research suggests that a dissatisfied customer will tell between nine and fifteen people about their negative experience, while 13% will go the extra mile and tell over 20 people. Offering poor customer service in today’s cut-throat online marketplace simply isn’t an option if you want to build a trustworthy and reputable brand.

Offering positive customer support, therefore, is a powerful way to maintain brand affiliation, attract and retain customers.

Implementing NLP technologies to replace human support agents is an effective way to cut costs, avoid delays, and optimize the efficiency of your customer success operations. Instead of using rudimentary voice commands that can cause more frustration, the sophistication of modern NLP technologies can create intelligent chatbots that guarantee 24/7/365 coverage.

Crucially, a significant proportion of customer support involves providing information to solve a handful of common queries. NLP can help retailers process these requests with maximum efficiency and free-up valuable time to handle more complex queries.

Intelligent Search Functionality

Analyzing semantic patterns in search bars to help customers find exactly what they’re looking for is the most powerful application of NLP in retail.

Yahoo Japan is exploring a combination of morphological analysis and named-entity recognition to advance its text mining capabilities to create NLP libraries for information extraction and conversational processing.

NLP libraries are a collection of organized datasets that contain individual ‘corpus’ or multiple ‘corpora’. E-commerce retailers can use NLP to categorize products into highly-specific corpora to develop intelligent search bars that help customers navigate to the exact product they’re looking for.

Retailers can also combine this search functionality with product recommendations to incentivize additional spending and direct customers to products they might like.

Translation for Global Reach

Advances in Machine Translation (MT) opens doors for online retailers to expand into international markets and enhance the customer experience across multiple languages. For example, Alibaba Cloud has developed NLP and deep learning technology alongside it’s enormous repository of e-commerce data to provide accurate translation services to partners across the globe.

The ability to translate web content and advertisements with high accuracy is important to boost brand loyalty and make customers feel valued.

Natural Language Understanding & Bi-Modal Innovations

The key success factor for online retailers is the ability to understand the intent behind a user’s actions and tailor their experience to boost brand loyalty.

Specifically, Natural Language Understanding will play a pivotal role in creating intelligent systems that can make useful interpretations from a growing bank of customer data. Developers must develop domain-based architectures that can understand customer intent through a more general set of inputs.

While early-stage NLP technology requires relatively specific search terms or data to suit customer demands, sophisticated technologies will provide a natural UX that feels like you’re engaging with a human entity, not a computer.

Additionally, bi-modal applications of NLP that work alongside computer vision technology will help retailers create virtual experiences that radically change the way we engage with online content.

Bi-modal application is a particularly exciting way to help e-commerce businesses cater to the needs of the elderly and people with disabilities. Whether it’s integrating voice commands with search functionality or using computer vision technology to provide personal recommendations to visually impaired users, the possibilities are endless.

Harness the Power of NLP Technologies With DefinedCrowd

While the world’s e-commerce giants will continue to reap the benefits of the latest technological advancements, we’re committed to helping all businesses harness the power of NLP and build systems that will drive industry-wide innovation.

Our vision is to champion the evolution of NLP technologies with a quality-focused data platform that combines the best of machine learning and human intelligence.

We look forward to partnering with you on your NLP journey – find out more about our product offerings here.


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