Contrary to popular belief and the buzz around it, AI has been around for ages. But it has had its highs and lows. At present, let us simply focus on the highs.
In 2017 alone, venture capital investment in Artificial Intelligence increased by 100% to $12 Billion. AI is going through something of a prolonged period of renaissance at this point, and as many have touted, entering its “Golden Age”. Calling it the “AI Spring” seems more appropriate because if what we’ve seen so far is only a fraction of the limitless possibilities of AI, then we have quite a long way to go.
Today, AI has infiltrated tech to an extent that has made it irreplaceable for upcoming tech development. Soon, it will be in extensive use by regular consumers when every object in your vicinity will be interconnected through the Internet of Things (IoT, another buzzworthy concept).
[addthis tool=addthis_horizontal_follow_toolbox]
The applications of AI are multifarious, but in this article, we will focus on innovative applications of Artificial Intelligence (existing or in development) that have had or will have a true impact on increasing the value of a company’s product/service to the customer:
Natural Language Processing
Natural Language Processing or NLP is a subset of Artificial Intelligence that is involved in the understanding of how human language (spoken or written) is interpreted and understood. So, NLP is what helps a machine or device understand what you have said after it has converted your speech into text. Virtual assistants such as Google Home, Siri, and Alexa use this technology to reply to you every time you ask it a question. As is obvious, NLP has made life very easy for consumers and the growing popularity of virtual assistants is a testimonial to the same.
Businesses also find a wide array of applications of NLP. Chatbots that use NLP can be used on websites of the business to help customers find exactly what they’re looking for or redirect them to a page that will solve their specific query. NLP also powers translation, which makes it easier for customers from anywhere in the world to visit a company’s website and find information in a language that they’re comfortable with. An app such as Inbenta provides multilingual support in 25 languages. Powered by NLP, it understands customer queries on the basis of meaning and not keywords. The use of Inbenta allowed Groupon to reduce email wait times drastically, and provide 1 million answers to its customers.
Read More: Quanergy Solid State LiDAR Wins Juniper Research Top Automotive Award
Read More: Deloitte Government Human Capital Trends Reveal Need For Greater C-Suite Collaboration
Deep Learning
Deep Learning is an AI function that imitates the neural networks of the brain to process data and create patterns which will be used for decision making.
Deep learning has most recently been in the news for its extensive, successful usage in image classification and image search, which is soon going to be a ubiquitous feature for most websites, especially eCommerce websites. Searching for products becomes easier for customers. They can search for products that they don’t even know the names of but deep learning- powered image search will facilitate the search for them. Companies can deliver much more effectively if they know exactly what their customer is looking for. Deep learning makes this a reality. A great example is Apptus, which combines big data and deep learning to determine which products might appeal to customers as they’re searching online. It makes recommendations on the basis of which the company can boost its sales.
75% of companies are using this subset of AI in order to enhance customer satisfaction, and a similar number of companies uses it to increase sales of new products and services.
Anticipatory Shipping
What’s the one thing that nearly every customer would undoubtedly wish for? Faster and more accurate deliveries. The Amazon Effect has left very few places on the planet untouched.
And like the true innovator it is, Amazon plans to use a technique called ‘anticipatory shipping’ to send out products/items that select customers are likely to order before their orders are even placed. No more delays in delivery and frustration over items that are out-of-stock.
Read More: Interview With Gabby Nizri, CEO And Co-Founder, Ayehu
Anticipatory shipping will involve the use of predictive analytics with Amazon’s massive tomes of data in order to cut down order fulfillment period and ensure faster delivery by sending the anticipated goods to warehouses that are closer to the recipients’ addresses.
Customer Relationship Management (CRM) Integration
Coming to the crux of the matter, in this case, AI directly leads to a better relationship between your company and your customers. A regular CRM system manages and analyzes customer behavior and interactions with the goal of improving their experience and their relationship with the company to encourage repeat business.
With AI integration, the capacity of a CRM software for lead management, driving sales, and customer retention is enhanced. AI-integrated CRM will have the ability to prioritize customers on the basis of the propensity of the customer to make a purchase.
An innovation worth mentioning here is the genesis of Genesys PureCloud which allows businesses to route their callers in a more efficient manner, by using AI. It integrates with Amazon Lex, a natural language understanding service, and helps businesses to decipher what customers really intend to say when they are speaking. Customer intent is made crystal clear, and customer service is, therefore, easily elevated. We have come full circle here with an AI innovation that makes the use of one previously mentioned ie Natural Language Processing.
Read More: Mensia Technologies Raises 1.3 Million Euro To Introduce Koala Neurofeedback In Europe
Final Words
The aforementioned applications of AI include some that have been undergoing development for a few years now (CRM integration, Deep Learning and NLP) and some that are still in development (Anticipatory Shipping).
Whatever the case may be, these innovative applications have one common purpose: to serve customers more effectively. It is obvious that these innovations are new. They would require a lot of trial and error to function smoothly and be widely adopted by companies. However, there has never been a better time to be an early adopter, especially for technology that could potentially transform the way business is done. These applications of AI have the ability to target very specific customer pain points, which could be resolved in a way that doesn’t squander away the company’s resources.
The ultimate aim of such innovations in AI is to enhance the customer experience. When customer experience is enriched, they will automatically engage in repeat business with your company. Conglomerates, such as Amazon, which are perpetually on the path of innovation, are excellent examples of this principle in action.
Comments are closed.