How Retail Companies Can Benefit from Natural Language Processing
Natural Language Processing (NLP) comes under the Artificial Intelligence (AI) umbrella. Using NLP technology, languages are translated into commands that computers can understand and process. This powerful technology reduces the distance between humans and machines.
Thanks to NLP, the retail sector has been going through an immense transformation over the past few years. Organizations are using the benefit of new technologies to gain a better understanding of their customers and to offer personalized engagement.
Unstructured data, such as customer feedback, emails, pop-ups, social media posts, etc. provide rich insights into customer perception of a business. Therefore, NLP becomes an obvious way to analyze the data and gain critical insights from both text and voice-based inputs.
NLP is the technology behind virtual assistants, chatbots, online translation services, and much more. Virtual assistants, like Siri on the iPhone, are now able to handle instructions such as calling a friend, checking the weather, or finding a restaurant.
Voice search has become increasingly popular, and voice search-related statistics accentuate it further. Various statistics show that 55 percent of teens and 41 percent of adults in the U.S. use voice search more than once a day.
1. Ways retail businesses can benefit from NLP
- Cost-effective: Training an entire workforce in new technology and its dynamics can be expensive. By using NLP, automated platforms are provided to gain industry-related knowledge, and this makes retail businesses more cost-effective over the long term.
- Time-saving: The process of understanding market trends through customer behavior and preferences tends to be a time-consuming and energy-sapping process. NLP can save time and effort by quickly absorbing user intent through omnichannel platforms.
- Accurate results: As NLP networks are always being trained on user intent, vocabulary, grammar, new content, document analysis, etc. it becomes possible to understand the emotions of customers and offer them the best answers to their queries.
2. Applications of NLP in Retail Businesses
Customers who enjoy a positive brand experience stay loyal and even help to promote a brand among family and friends. Here are some applications of NLP that help to enhance customer satisfaction and lead to more profits.
a) Text recognition and Semantics
Understanding language requires understanding not only words but the context in which they appear. Teaching this to a computer is not easy.
This is why NLP is based on many applications such as entity recognition, topic extraction, automatic text summarization, sentiment analysis, and speech tagging.
Computers have plenty of data for semantic analysis, and by using powerful algorithms, they are becoming increasingly proficient in understanding a particular word in its context.
Without using NLP, search engines are not able to understand the context and exact intent of a customer searching on an eCommerce website.
For example, if a customer types in “black shoes for evening wear,” a search engine not powered by NLP would probably show images of regular black shoes and evening wear in various colors.
With NLP, the traditional search process is continuously trained and improved to provide the customer with an exact answer to a specific search query.
b) Sentiment analysis
Customer feedback, answers to queries, likes, dislikes, choices, preferences, and expectations about products and services provide vast amounts of unstructured data.
Sentiment analysis helps with understanding how customers feel about a product or brand. NLP engines retrieve data, analyze it, and assign a value to it, such as positive, negative, or neutral.
The latest advancements in NLP technology can even identify emotions such as anger, happiness, or sadness.
c) Personalized bots
With personalized bots, shopping can be more fun than ever. Bots can keep shoppers interested and bring to the screen exactly what they want to see. Analyzing recent searches and past purchase behavior helps to ensure a seamless shopping experience.
With NLP making it possible for machines to talk to humans and understand the intent and nuances of a request, Chatbot technology is being used by retail businesses to deliver personalized conversations to resolve customer issues.
Chatbots can even show empathy, use the opportunity to meet brand promises, and accurately interpret requests.
Extracting information from past data can also help with making future business decisions. The insights delivered by chatbots may help with forecasting revenues based on statistical data and enable more accurate decision-making.
d) Customer service
Customers often complain about traditional call centers, saying that they are left on hold, have to press multiple buttons, and often need to explain a problem numerous times, using call centers that operate automatically without needing human agents could solve such problems.
With the help of embedded intelligence like NLP, multiple calls can be attended through a single server. It fetches a query and responds to a customer or transfers a request to the correct department. Customers are attended to 24/7, and an issue can be instantly resolved without having to send an email to say it will be addressed.
NLP helps advertisers to identify potential buyers of products by analyzing purchase behavior, social media posts, etc. NLP broadens the range of channels for placing ads and allows companies to target potential buyers and spend their ad budgets wisely.
f) Market Intelligence
Retail businesses always need to stay informed about the latest behavioral trends as well as competitors and their strategies. They need advanced tools to analyze available data on websites, social media posts, and blogs.
NLP allows them to remain up to date with current trends etc. so they can refine their marketing and sales strategies.
NLP won’t replace human ingenuity and perception shortly, but it has excellent value as a tool for gaining more insight into customer perceptions and behavior.
This, in turn, leads to more customer satisfaction and increases in revenue. As NLP continues to advance, it will be interesting to observe how much it transforms retail businesses in the future.
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