What is NLP? And 7 Reasons why everyone in Retail should use it
Natural Language Processing (NLP) is one of the attempts of adding a ‘human touch’ in the computer-driven world. Frankly speaking, it worked out wonders so far. NLP technology falls under the umbrella of Artificial Intelligence (AI). NLP is coded to act like a human to communicate and respond to user’s query smartly to achieve better customer satisfaction or even get cart checkout conversion rates higher.
NLP is an inbuilt and powerful technology that helps users find the exact products on the shopping websites without having to choose from different options available from the static searches. Even a dynamic search that is provided on the website suggests the words even before we type may not be all that interesting with the coming age of Artificial Intelligence (AI).
Technology innovations in communication and interactions
NLP involves communication through speech and text. Speech communication is the recent innovation that includes chatbots and other voice-based bots. These are designed as human language personal assistant. You may be already familiar with the personal assistant found on iPhone’s Siri – a personal assistant that just communicates like a human and can assign her almost any task you wish to do. Instructions like calling a friend, find restaurants and events, check weather and so on. The list is endless. It may even tweet and update your status on facebook just like a human friend with incredible intelligence.
This technology binds human-computer relationship, and leaps and bounds benefit business houses. Although machine learning the natural language is far away from the dominating human realms, but human intelligence is exploring the new heights, and we may see the new age of Artificial Intelligence (AI) is getting closer in achieving perfection and in the near future we might see the dynamic use of NLP in various forms.
NLP has strengthened the interactions with the search engines that allowed the queries to be assessed faster and in an efficient manner. The most important part of it is, it understands the query given to it and fetches accurate results.
NLP has given rise to voice search that becomes increasingly popular these days. And Google study of 2014 reveals 55% of teens and 41% of adults in the US use voice search more than once a day. In 2016, Google announced that 20 percent of its mobile app and Android devices are voice searches. All these numbers are bound to increase drastically in the coming years. It is the increasing speed of computer processing that made the voice search a possibility and now an increasing popularity.
Searching for the perfect match
When people search for the product online, the exact and closest matches appear on the screen. The product description played a vital role in marketing the product and helps improve sales to a considerable ratio.
Now with the app world, everything is individualized. Preferences based on search history, recommendations based on sales history, notifications, etc., and give users a delightful experience. As the usage of smartphones and tablets increases day by day, mobile-optimized websites and apps are gaining momentum to give users online shopping experience a fulfilling one.
Challenges in Retail industry
E-Commerce sales in 2017 in the United States amounted to almost 453 billion US dollars, and it is expected to grow by 779.5 billion US dollars in 2021. The opportunities are wide open as people prefer online shopping more than the brick and mortar and that’s primarily because of the benefits available are plentiful.
Few challenges still remain unsolved though the issues are addressed, and improved considerably with the invention of latest technologies like the NLP. Below are some of the questions that come to us when we try to bridge customer expectations into an actual sale.
- How to convert the search ratios into actual sales?
- Do customers keep visiting the websites?
- How well your app and site respond to customer queries?
- Do the searches match the query?
- Does your search engine understand smartly enough to keep the customer engaging?
Not only these questions are addressed, but the solutions can be taken to the new level with NLP. Computers now can understand what exactly customers mean when they type a word or phrase or speak in the search field. Text processing is now more filtered, clean and noise-free so that it can be readily analyzable without having to go through a backhand processing. NLP helps the unstructured text data into a standardization form. This enables the search results to be swifter and with utmost precision.
7 different ways NLP can help retailers
1.Text Recognition
Recognizes the text, character and converts them into data and stores it in its database. The ability to read the text and converts into a machine-encoded text is one of the methods of language processing that is been used by search engines for many years. With the help of NLP, things are far easier than it was before in terms speed and accuracy. No more mere search results but it give you the answers to the question posed by the customers.
2.Semantics
We, humans, understand the word in the context of the sentence spoken or written and we do it more efficiently and effortlessly. But to teach the computer the context in which the sentence is spoken or written is quite a task. Machines do not understand what and the why.
As we all know that training makes us perfect in something we do, the same theory applies here as well to the computer world. They have been given a lot of unstructured data for semantic analysis and through powerful algorithms; computers are becoming more powerful and getting better at understanding the particular word in reference to the context or scenario to comprehend the phrase.
3.Sentiment Analysis
When do you know what exactly means ‘happy customer experience’ is, which is very much subjective. Even, if we find out the ways to get into it, how to teach the systems to understand the emotions of the text? Yes, things are still in the primitive stage to evaluating the customer views that may be made available to us through our research team. Customer feedbacks, answers to queries, their likes, and dislikes, their choice and preferences in the coming festival seasons, holidaying trends, better product ideas, their expectations with regard to the product and services, etc., will amount to a huge unstructured data.
To analyze the enormous amount of unstructured data and interpret the outcome of such reviews requires huge manpower. But with computers now tuned to AI, customer’s emotional responses, analysis, and findings are marked as a positive, negative or neutral outcome. It would be easier for the computers to understand the simple answers or interactions. However, complex responses complicate the whole comprehension of machine learning. But there are several methods to segregate the complicated words from complex sentence patterns to determine the exact meaning of the sentences. Natural Language Processing implementation can be complex, often requiring collaboration between data scientists, machine learning engineers, and domain experts. Thus, this further provides a high level of accuracy in predicting the ambiguous phrases in simpler ways.
4.Personalized Bots
An organization may reap maximum benefits using NLP in designing personal assistants. Shopping can be more fun than ever. These assistants have the ability to keep the customer interested and bring on their screen exactly what they require to shop. It analyses recent searches you made, past purchase behavior to bring out seamless shopping experience.
NLP would be able to make machine talking to a human in the easiest possible way. Chatbots technology may be used in business houses to extract information from past data that might help taking big business decisions. The powerful technology also helps you forecast the revenues based on the statistical data in a flash. The insights delivered by the chatbots may transform your business into a formidable platform to find the right answers to leap into the future.
5.Customer Service Centers Dynamics
Automation is the mantra for transforming call centers without a need for a human agent. AI is making the pathway to the future for handling customer interactions. All those forward-thinking b-houses can be benefitted through real-time dynamics that efficiently improve loyalty and brand name and its reputation to new heights.
Several thousand or more or even infinite calls can be attended through a single server that fetches the query in a flash and responds to the customer or transfer calls to the respective departments with the help of embedded intelligence such as NLP. There will be no more hearing such as ‘press 1’ ‘press 2’ etc.
AI aims to improve the customer service reputation and reduce dissatisfaction among customers. Only AI has the speed and power to boost purchasing cycle as it sends alerts and, intriguing offers based on the certain patterns that are highly valuable to retain customers and urges them to revisit the apps time and again.
Social interactions, messaging can be made fully operational through chatbots leveraging the time and space. These interactions can be made 24×7 and even be designed to solve issues instantly rather than sending an email requesting to process the issue within 2 business working days. These are challenging but creative that is sure to win customer support in an attempt to reach out to them to provide unmatched service.
It is worth reading the Zendesk survey that illuminates us how interaction with customer ending on a happy note has a great impact on purchase behavior. This impact is purely based on the past interactions. If there is a negative response, 95 percent of those unsatisfied customers are likely to share their bad experiences. Another drawback of traditional call centers revealed as 74 percent of the people complained that they have to explain their problem multiple times as the call center calls are not diverted to one single person. More shocking is one bad customer service interaction can cost you a customer as 66 percent stopped buying after one bad experience during customer service interaction.
6.Cost Effective
Imagine if your entire workforce needs to be trained to the new technology and the dynamic of it can significantly have an impact on business operations, then you ultimately end up paying 1000s of dollars to let the technology do the talking. But if the new technology that brings in with it the intelligence that has the automation platforms programmed to own industry knowledge, why not implement them. That business intelligence requires training once as and when the upgrade is released. It is a powerful feature that every business houses need to own.
7.Information Discovery Magician
Business constantly requires updated information’s about the customer reviews on their products, their behavioral trends, fair ratings of their recently launched products etc., can illuminate the management to get things going their way. Information gathered through poll surveys, emails pop-ups, social media posts, blog posts, phone calls and comments about products on different web interfaces are managed by applications powered by AI. The quest for knowledge never ceases and information gathered is analyzed and interpreted in an accurate manner.
Conclusion
Businesses would be greatly benefitted from these in-depth insights that are powered by AI are surely find customer satisfaction ratio in the upward curve leading to the increase in revenue curve as well. More of NLP innovations are about to transform business operations. We just wait and watch how the AI unfolds in the coming years.
