Natural Language Processing For eCommerce: Everything You Need To Know

Alexa - Natural Language Processing

Natural Language Processing or NLP's primary goal is to build a tool or a machine that better comprehends and responds to voice data or text, similar to how human beings think and respond. It's a branch of artificial intelligence that gives computers the capability to understand human language, both written and spoken.

Some examples of NLP include digital assistants, voice-generated systems and chatbots. NLP enables a computer to translate and summarize text and answer voice commands. It also plays a significant role in business as it allows companies to streamline their business operations, generate more revenue and increase productivity. We'll talk about natural language processing in this article, its applications and how it can help e-commerce companies grow their business.

How E-commerce Uses Natural Language Processing

If you're running an e-commerce business, one of your goals is to analyze the behavior of your prospects and current customers. With natural language processing, you would be able to determine what words or phrases your customers use when searching for or talking about particular products or services. You can use this data in improving your marketing strategies to create awareness for your brand, generate more revenue, improve products, and grow your business. 

Smart Recommendations

E-commerce businesses use keywords when showing product recommendations. If you type in handbags or shoes, the search results will show all of the handbags and shoes. This can be overwhelming to the customer especially when you have hundreds or thousands of handbags or shoes to choose from.

You can remedy this problem with natural language processing. NLP can consider other factors to determine which type of products to recommend to the customer. Using NLP for your e-commerce business can help you recommend the right products your customers are likely to purchase. This can reduce site abandonment and increase your sales as a result.

Efficient Customer Support

Poor customer service can severely hurt your business. When the problem isn't addressed, you will start losing customers and brand credibility. Implementing natural language processing technologies can provide you with faster customer support. Some customers don't like to wait for a human support agent. By taking advantage of NLP, you'd be able to reduce problems and save money in the long run.

Sentiment Analysis

Sentiment Analysis is the process of knowing whether a customer review or comment is positive, negative or neutral. It uses natural language processing technology and machine learning techniques to assign sentiment scores to a piece of writing, usually within a sentence or phrase. By analyzing customer sentiments using artificial intelligence, data analysts can better understand customer experiences, monitor brand reputation and conduct market research.

Yogi online review analysis platform uses deep learning based natural language processing to extract actionable business insights for eCommerce products and brands. Unlike competitors, whose algorithms are based on word frequency, Yogi uses a unique method of AI-powered NLP called K-Means to build a contextual understanding of what customers are talking about.

This enables customers to leverage Yogi's proprietary models for AI-powered NLP to gain unparalleled visibility into unstructured customer feedback such as online ratings and reviews, an inherently messy and nuanced data source. This is impactful because the robustness of Yogi's algorithms provides a level of speed and accuracy that allows organizations to gain rich insights faster than ever before.

How it works:

When a customer comments on a product or service, the technology breaks up the piece of writing into phrases, sentences and other components. It will analyze each component and assign scores to every component. The scores come from the sentiment library, which is an enormous collection of words or phrases.

When a customer types in a bad or worse experience, the weighted sentiment depends on the corresponding score of each word or phrase.

A set of rules of also used to evaluate the sentiments expressed toward the noun or pronoun, based on how close it is to a positive adjective or adverb. Parts of speech tagging are also used to identify each element of the document, such as the noun, verbs, adverbs or adjectives.

While rule-based sentiment analysis is a good option for scoring, it requires tedious labor. Rules may also not be able to keep up with how the human language evolves. If you're a business owner, choose the right platform to help you sift through and analyze customer Reviews and Ratings to improve your products and customer experiences.

Yogi's sentiment analysis algorithms act like humans, using context clues and other phrases in reviews to determine emotion versus assigning values to words. Humans are generally 85% accurate when it comes to sentiment analysis. Based on recent testing, Yogi is currently 82.4% accurate, surpassing the competition which ranges from 72% to 76% accuracy.

Benefits of NLP

Natural language processing does more than just help e-commerce businesses gain more customers. On a large-scale analysis, NPL technology can analyze and process online reviews, social media data and even internal systems in a matter of minutes or seconds, as opposed to waiting days or weeks to manually analyze data. Imagine how much it would cost you when you do everything manually. With NLP, you only have to choose the right technology for a seamless business operation.

Improve Customer Satisfaction

With NLP, businesses can automatically analyze customer service tickets or social media reviews and comments. They can sort these by intent, urgency, topic, sentiment, etc and route these concerns to the right department, to ensure the problem is addressed promptly. While it's still possible to do these things manually, it will take time. It wouldn't be ideal especially when you're running a medium-sized or a large company.

Customer relationship management or CRM is a technology that can assist with this. As a result, you get to improve customer satisfaction and gain more loyal customers.

Understand Your Market Better

Knowing your audience's wants can improve your marketing strategies and help you better position your products and services. With NLP, you'll be able to understand your customers' pain points and resolve their issues better.

Accurate Analysis

When you manually analyze data, it's likely for you to make a mistake. Humans are prone to making mistakes and may have inherent biases that can affect the results. You can avoid this with the right natural language processing technology.

Instead of asking your employees to manually analyze data, they can focus more on improving their productivity and helping your business grow. NLP can also remove repetitive and tedious tasks that might result in fatigue or stress.

Other Natural Language Processing Applications

Below are the ways businesses can use natural language processing:


A chatbot is a computer program that simulates and processes written or spoken human interaction. It lets you communicate with digital devices in the same way you are speaking with a real human. Powered by NLP, chatbots are everywhere — on social media, websites and other apps. They offer convenience to customers and bring cost savings to companies. Chatbots let companies resolve common issues and queries while reducing real interaction.

With a chatbox installed on your social media platform or website, a business doesn't have to hire a human to take care of the chats. Your goal as a business owner is to lower your expenses and you can achieve this by having a chatbot installed.

Two types of chatbots
Task Oriented:

Declarative chatbots mainly have one major function — to generate automated responses for common user inquiries. Structured and highly specific, they are most useful in support and service functions. Some companies use these types of chatbots as a replacement when there isn't a real human being available.

Conversational and data-driven chatbots:

Also referred to as digital or virtual assistants, these types of chatbots are more interactive and sophisticated. Compared to task-oriented bots, data-driven chatbots have more advanced natural language processing and machine learning technology. Some examples of data-driven and consumer-oriented chatbots include Apple's Siri and Amazon's Alexa. Over time, they learn and monitor intent, start conversations and even make recommendations.

Speech Recognition

Thanks to NLP, data analytics tools now have the ability to comprehend natural language. Also known as automatic speech recognition or speech-to-text, this program has the capability to process human speech into a written format.

Advanced speech recognition applications use advanced NLP by integrating syntax, structure, grammar and composition to better understand and process human speech. Some systems let businesses customize the technology to their specific requirements.

How the Yogi AI Platform Can Help

Do you need assistance in analyzing customer reviews? Yogi can help! Using our platform you can get actionable insights from ratings, sentiment analysis, thematic breakdowns, NPS, and more to improve your messaging and products to boost sales. Our ratings and reviews platform can aggregate reviews from both public and private sources, properly organize them and analyze them for you. The results can help you improve your product pages, improve your services, increase conversions and grow your business.