Master Data Management

Product recommendations using NLP

Product recommendations are a critical aspect of any retailer’s ecommerce strategy. Smart recommendations help customers find relevant products at lower costs. A product recommended at the right time can influence buying of a product over another. All organisations collect and store huge amounts of data during customer interactions. Natural Language Processing (NLP) uses algorithms to analyse and understand these large quantities of unstructured data and recommend products to each customer. Product recommendations can help boost sales and, thereby, profits too.

Natural Language Processing (NLP) is an AI-based solution that helps computers understand, analyse, and take action on commands triggered by human language. It is a powerful, machine learning tool that helps computers understand human speech and written text.

Why is NLP so important in the online retail industry?

All shoppers expect search engines in ecommerce sites to understand exactly what they want and make the perfect recommendations. Naturally the phrase, or even an idea, used to search for a product will differ vastly among shoppers. Hence, the search requires speed and scale that is impossible for humans to tackle without help. A bad search engine and poor navigation can turn away shoppers very fast. Here’s where the power of NLP comes into play.

Every organisation collects and stores copious amounts of data. It will include search phrases, feedback, suggestions, tracking details, product reviews, social media posts, emails, and more. This is a lot of unstructured data. For example, Walmart collects over 2.5 petabytes of data every hour from its customer interactions.

NLP uses algorithms to transform this huge amount of data into machine language. NLP augments human capabilities and gives organisations a competitive edge in terms of speed and quality.

Smart product recommendations

Ecommerce businesses must keep customers interested long enough for purchase decisions to be made. They must make suitable recommendations to keep customers interested. In fact, smart recommendations can stimulate impulse purchases too.

A study shows that product recommendations account for one-third of online revenue and can reduce cart abandonment by 4.35%. Leading ecommerce sites acknowledge that over 30% of their revenue is earned from purchase of recommended products.

Earlier, products were recommended based on keywords, but retailers today use search history search, previous purchases, context, and other factors to enrich product recommendations. All of this is possible because of NLP.

Elements of NLP in ecommerce

Syntax and semantics are two important elements of NLP. While syntax helps break up sentences and uses words and grammar rules to understand a piece of text, semantics extracts the actual meaning. It uses word categorisation tools, word meaning databases, and context to understand the intent. And that is how a computer understands human requirements. 

Semantic-based search

Compared to sites with text-based search bars, those with semantic-based search bars are known to have much lower cart abandonment rates. It works because such a search is very intuitive, and shoppers find relevant products even when they use unique search phrases. Semantic-based search can quickly find products located very deep in the website’s product catalogue. This helps sense exactly what the customer wants, more or less like a sentient machine.*

It’s no surprise that NLP in ecommerce is widely used by businesses to make product recommendations. In this innovative world, time-pressed shoppers just want to purchase quickly. Businesses must get it right the first time or face the risk of losing customers. 

* For organizations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organizational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organizations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organizations that are innovating collaboratively for the future.

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