Ecommerce is a rapidly growing industry, and with the incorporation of AI and NLP technologies, businesses are able to optimize their processes and enhance customer experience like never before. According to a report by Aimultiple, 78% of ecommerce brands have already implemented or plan to implement AI in the future.
One of the most significant applications of AI in ecommerce is Natural Language Processing (NLP). NLP is a subfield of AI that deals with the understanding and processing of human language, enabling computers to understand, interpret, and generate human-like speech and text. This technology is used to build sophisticated tools and processes that can understand customer behavior, search queries, sentiment analysis, and more. It can also be used for customer service chatbots, product recommendations, and personalized marketing campaigns.
According to a report by MarketsandMarkets, the NLP market is expected to grow from $4.65 billion in 2020 to $16.07 billion by 2025, at a CAGR of 29.7% during the forecast period. This growth is driven by the increasing volume of unstructured data, the growing need for automating business processes, and the increasing use of NLP in various industries such as healthcare, finance, and e-commerce.
Additionally, as per a survey by Salesforce, 80% of customers expect companies to understand their needs and provide personalized experiences. NLP can help e-commerce businesses to provide personalized experiences to customers by analyzing their previous interactions and search queries, which can lead to increased customer satisfaction and ultimately increased sales.
An overview of Natural Language Processing (NLP)
Natural Language Processing (NLP) is a subfield of Artificial Intelligence (AI) that deals with the understanding and processing of human language. It enables computers to understand, interpret, and generate human-like speech and text. NLP is used to build sophisticated tools and processes that can understand customer behavior, search queries, sentiment analysis, and more. It is a powerful technology that can be used in a variety of industries, including ecommerce, healthcare, finance, and more.
The incorporation of NLP in ecommerce can bring significant improvements in various areas such as search, customer experience, customer support, language detection, sentiment analysis, and targeted marketing. For instance, semantic search uses NLP to understand the intent behind a search query and return more accurate and relevant results. Similarly, NLP-powered chatbots and virtual assistants can improve customer support by providing accurate, natural language responses. NLP can also be used for sentiment analysis to understand customer opinions and feedback, which can be used to improve products and services.
Transformational use cases of NLP for e-commerce
Natural Language Processing (NLP) has the potential to revolutionize the way ecommerce businesses operate. Here are some of the ways businesses have realized the use cases of NLP in the ecommerce sphere:
Mastering Search with Semantic Search
Semantic search is a technique that uses NLP to understand the intent behind a search query, rather than just matching keywords. This allows for more accurate and relevant search results, even when the query is phrased in a natural language. In ecommerce, semantic search can be used to improve product search, making it easier for customers to find what they are looking for.
An example of how semantic search can be used in ecommerce is on a fashion retail website. A customer may search for "black dress" but they may also use variations of the query such as "little black dress" or "LBD." With semantic search, the website can understand the intent of the query and return relevant results even if the customer uses different terminology. This can lead to a better user experience and increase the likelihood of the customer making a purchase.
According to a study by Capgemini, 68% of consumers are more likely to buy from a website that offers personalized search results. Implementing semantic search using NLP can improve the customer experience by providing them with more relevant search results, ultimately leading to increased sales.
Voice-Enabled Shopping: Revolutionizing Customer Experience
Voice search and assistance are becoming increasingly popular, and NLP is crucial in making this technology work. NLP is used to understand the intent behind a voice query, and generate a natural language response. In ecommerce, voice search and assistance can be used to improve customer experience, making it easier for customers to find products, get information, and make purchases.
For example, a customer could use a voice assistant to search for a specific product, such as "I want to buy a new pair of running shoes." The voice assistant, powered by NLP, can understand the intent behind the query and provide a list of relevant products, such as "Here are some options for running shoes that we have in stock." This can make it easier for customers to find what they are looking for and make a purchase quickly and conveniently.
According to a study by Gartner, 45% of all searches will be done without a screen by 2025. The increasing popularity of voice assistants and the use of NLP in understanding and generating natural language responses can improve the customer experience and increase sales.
Automated, Intelligent Customer Support: The Future of E-Commerce
NLP is used to build chatbots and virtual assistants that can understand customer inquiries and provide accurate, natural language responses. This can significantly improve customer support, reducing the need for human customer service representatives. In ecommerce, chatbots and virtual assistants can be used to provide product information, track orders, and assist with returns and exchanges.
An example of how chatbots can be used in ecommerce is on a fashion retail website. A customer may have a question about a specific product, such as "What is the material of this dress?" With an NLP-powered chatbot, the customer can get an accurate, natural language response, such as "The dress is made of 100% cotton." This can provide customers with the information they need and improve their experience, reducing the need for human customer service representatives.
According to a study by Oracle, 80% of businesses plan to use chatbots by 2025. Implementing NLP-powered chatbots can improve customer support and increase efficiency, ultimately leading to increased sales.
Analyzing and classifying products through descriptions
Users who search for products on an ecommerce site come with a higher intent for purchase.In fact, over 87% of online shoppers consider product descriptions essential while making purchase decisions. Even so, 46% of ecommerce stores do not support thematic queries such as "summer jackets" or "pink prom dress". And over 32% fail to support abbreviations and common symbols for even basic units. This makes it difficult for site search engines to accurately classify and identify products.
NLP can be instrumental in building this search functionality by understanding the structure and meaning of text. It can help ecommerce businesses automatically categorize products, extract key information, and even generate new product descriptions.
In addition to reducing the amount of manual work required to categorize products, NLP can also help to improve the accuracy of classification. By understanding the context of words in a product description, NLP can more accurately identify which products belong in which category. Say you have a clothing store with a large inventory. You could use NLP to automatically assign tags to each product, based on its description. So a dress might be tagged as “formal wear,” “black,” “size 10,” etc. This would make it much easier for shoppers to find what they’re looking for – they could simply search for “black dresses” or “size 10 dresses” and get relevant results.
Decoding Mixed Language and Incorrect Scripts: The Key to Better Search
NLP can be used to detect and correct errors in language, such as incorrect spelling, grammar, and syntax. This can be particularly useful in ecommerce, where customers may not always use correct language when searching for products or asking questions. NLP can also be used to detect synonyms and variations of words, allowing customers to find products even when they use different terminology.
An example of how NLP can be used to detect and correct errors in language is on a travel website. A customer may be searching for "hotel" but they may accidentally misspell it as "hotal." With NLP, the website can detect the error and correct it, providing the customer with the correct results. This can improve the customer experience and increase the likelihood of the customer making a purchase.
According to a study by Google, 29% of queries contain a spelling error. The use of NLP in detecting and correcting errors in language can improve the customer experience and increase sales.
Understanding Customer Sentiments: The Power of Sentiment Analysis
Sentiment analysis is a technique that uses NLP to determine the sentiment or emotion behind a piece of text. This can be used to understand customer opinions and feedback, and to improve overall customer experience. In ecommerce, sentiment analysis can be used to monitor customer reviews, social media posts, and other customer feedback to understand customer opinions and to improve products and services.
An example of how sentiment analysis can be used in ecommerce is on a fashion retail website. The website can use NLP to analyze customer reviews of a specific product, such as a dress. The sentiment analysis can determine if the reviews are generally positive or negative, providing valuable feedback to the website about the product. This can be used to improve the product and the customer experience.
According to a study by Newvoicemedia, 67% of customers are more likely to purchase a product if they can see customer reviews. The use of sentiment analysis in ecommerce can provide valuable feedback and improve the customer experience, ultimately leading to increased sales.
Targeted Marketing: Reaching the Right Audience
NLP can be used to understand customer behavior and preferences, which can be used to target marketing efforts. In ecommerce, NLP can be used to analyze customer interactions and purchase history to understand their interests and preferences. This information can be used to personalize marketing efforts, such as product recommendations and targeted ads. This can also be used to create personalized product bundles or loyalty programs, which can increase customer retention and sales.
An example of how NLP can be used for targeted marketing is in an e-commerce website selling electronic gadgets. By analyzing a customer's purchase history, the website can make recommendations for related products that the customer might be interested in. This can improve the customer experience by providing relevant recommendations and ultimately increase sales.
According to a study by Epsilon, personalized emails have an open rate 29% higher than non-personalized emails. Further, 80% of the consumers are more likely to make a purchase when brands offer a personalized experience. The use of NLP in targeted marketing can improve the customer experience, making it much more personalized, thereby increasing overall sales.
When are you taking the NLP route for your e-commerce store?
The use cases of NLP in ecommerce are evidently wide-ranging, from improving product search and customer support to targeted marketing and advanced personalization. With the growing popularity of NLP, ecommerce businesses have an opportunity to improve customer experience and increase sales by leveraging the power of NLP technology.
At Zevi, we specialize in NLP and machine learning technology and our cutting-edge technology can help businesses in optimizing their processes and enhance customer experience. Take the first step to experience the benefits of NLP for yourself by booking a demo with us today! Don't miss out on this opportunity to see our technology in action and understand how it can benefit your business. Contact us now to schedule a demo and see the potential of NLP for yourself.