For those enterprises already in the AI fray, top-performing companies said they are more than twice as likely as their peers to be using the technology for marketing (28% vs. 12%). Unsurprisingly, analysis of data is a key AI focus for businesses, with on-site personalization the second most commonly cited use case for AI. (Source: Adobe)
As the COVID-19 hit our lives, businesses have had a lashing impact on them and have transformed from the usual to virtual. In these times, they are leveraging technology to overcome the everyday challenges, to provide quality services to the customers, and to gear up for the future with future business solutions. Yet, the digital transformation has been amazing over the times and even so Businesses are eager to use AI and ML to the best of its capability to increase efficiency and productivity.
The AI infrastructure
The advancements in artificial intelligence has opened the doors for development and innovation. It is contributing multifolds to improvement in production and quality work by precisely discovering opportunities, patterns and themes in real time with large amounts of data and input sets. Of course with the speed at which these AI algorithms operate, they are paving the better ways of getting business done.
There are large amounts of data generated everyday that gives us a great deal of information about our customers preferences. Having said that, businesses understand the need to rely on the modern methods to drive growth. Intelligent computer softwares and actionable insights drawn from customer’s data help boost revenue, increase productivity, improve customer experience, and drive growth. Let’s see how.
Approximately 70% of buying decisions are made based on how clients feel they are being treated, superior customer service has the power to turn any company into an industry juggernaut. (Source: Salesforce)
Companies have started taking utmost care of their customers by putting effort into giving them the best experience with their services.
For instance chat-bots allow the customers to interact with the company in real-time so that their complaints are resolved, queries are answered, and other information is shared quickly and seamlessly. Artificial customer support helps give faster answers by handling commonly asked questions through live chat experiences which is available 24 hours a day providing continuous customer support. On the other hand, customer support teams spend a lot of time researching the answers to the customer’s questions increasing the wait time for the customers. AI can save these answers and use them for the frequently asked questions that customers have.
AI leverages information from CRM solutions and highlights the key customer details so that the approach towards the customer’s is intelligent and AI-powered. With predictive insights, AI is able to suggest products to the customer based on their previous experience and the product’s availability in the inventory. And, sentiment analysis helps the customer executives by categorizing the tickets raised by customers into different categories like neutral, positive, or negative. This helps the agents understand how to prioritize their work. Artificial intelligence makes the work for the customer’s more incisive and responsive. Strategic and smart work.
AI-powered natural processing language and automated predictive insights are doing wonders for businesses. Employing AI in business intelligence is turning into everyday business with many adopting the technology. The plethora of data and the need to understand that data are the factors that are contributing towards the growth of Business Intelligence. This is a system that is designed to structure the large volumes of data that is collected, processed, and analyzed so that the data can be used to strengthen their business processes by making smart business decisions. Then again, digital AI amplifies the functionality of Business Intelligence by splitting large chunks of data into detailed insights that could be used in advantage for their business.
With benefits of Machine learning coming into the scenario, the issue of real-time insights was able to be resolved by ML algorithms predicting trends and generating real-time insights. This has influenced the value of Business Intelligence in a constructive manner.
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AI-driven personalized and targeted marketing
To be able to communicate with the target markets is extremely essential for every business and AI helps you do just that. It is behaviour-based algorithms and predictive analysis that brings together all the data that makes this communication possible. Also, there are several AI-powered intelligent multisensory systems that monitor different types of sensors in an environment and accordingly interpret the activities that are taking place in that monitored environment. This monitoring and interpreting has come together as a solution to several challenges. They help businesses learn about their customers’ requirements and expectations which helps them provide the best services possible.
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The other facets that come with integrating AI into brand marketing is Ad targeting that are Ads that target specific users based on their previous online shopping behaviour. To serve these various purposes, there are advertising intelligent apps like Match2One, ReFUEL4, and others that prospect and retarget customers. Then there’s personalized messaging that again uses behavioural data to send messages to the customers that are of some relevance to them. Yoochoose, Dynamic Yield are some of the companies that use data to provide the customers with personalized emails and messages.
AI-enabled product recommendation and predictive analysis
Product recommendations engines are leveraged by companies to improve customer’s experience. There are many AI development companies that offer AI-enabled products and services and advertise more and more products in front of the customers. The fundamental point is to put out the right product in front of a customer and that is how AI recommendations work. The scads of customer data like the customer’s profile, product metadata, the products purpose, etc. that is present on the internet is used by the AI system (machine learning algorithm) to predict and match products for the customers that are most likely to be purchased by them. Well, there are a number of popular recommendation approaches that subsist. Most of the product recommendation operates on predictive analysis that helps train the algorithm with all the product and customer data. The relevant product ads then appear to the customers on the sidebar, top banner, and other areas of the retailer’s choice through designated channels.
Blockchain and AI development
Blockchain and AI development individually are preeminent technologies across almost every industry and also together they are proving to be quite an influential duo. Integration of Artificial intelligence in Blockchain is imperative as they both deal with data and value and they collectively improve the capability of a machine learning algorithm. Not to mention that Blockchain ensures secure storage and exchange of data and AI analyzes and draws insights from the data to derive value. Both the technologies mutually benefit one another and enhance each other’s capabilities which multifolds the grade of efficiency, security, and accountability for business processes.
Natural language processing
What this means is the capability of an AI system to read, understand and recognize several human languages and an NLP technique converts the written or spoken language into a form that computers will understand. In business, the NLP technology is put forth using sentiment analysis that helps the businesses earn a broad public viewpoint on their products and services. A few applications of NLP technology are Email filters that are used to stop spam emails from entering their inbox, smart voice driven interfaces to understand and take better care of user’s concerns and queries, extraction of information from texts, infographics, and images (unstructured data) to understand human conversation and improve the ML program. There are some popular NLP softwares and tools like Amazon comprehend, Gensim, Google Cloud translation, IBM WatsonTone Analyzer, and others that are used to build chatbots, voice assistants, predictive text applications, python programs and libraries, cloud based solutions to work with human language data, etc.
The number of AI-powered voice assistants is forecast to reach 8 billion by 2023—a 146 percent increase from 2019’s 3.25 billion. (Source: Oberlo)
For those not in the know, one such company that provides AI solutions to businesses is Logic Simplified, an artificial intelligence development company in India. We understand the importance of data processing in AI for businesses and its capability to solve long standing business challenges. Every business is different but some of the challenges that they come across are age old and quite common among all. And, the team of AI developers at LS are well-positioned to bring to you AI-enabled solutions and approaches that are effective and capable of allowing businesses to manage data, satisfy customers, improve customer interactions, ensure secure transactions. For the most part, make business highly productive. For more information get in touch with us or email at firstname.lastname@example.org