The concept of Artificial Intelligence is almost six to seven decades old but has gained immense popularity in recent years. And the experts explain here the major factors behind this.
You might be stunned to know that limited data was one of the main reasons that delayed the success of Artificial intelligence because AI needs an enormous amount of data to predict accurate results, which was not present earlier. And the second one is low computing power.
In the last two decades, social media has changed the whole scenario. This massive revolution has rapidly increased the number of internet users and the rapid enhancements in CPUs and GPUs have enabled the companies to handle huge amounts of data.
Hence, with high-end computer power and advanced neural networks it has become easy now to deal with enormous amounts of data.
Artificial Intelligence Is Not Rowing the Growth Boat Alone!!!
Big Data Extends Its Helping for Strategic Decision Making
Big data can be defined as huge chunks of data sets - both structured and unstructured while AI is a technique that enables machines to act like humans or replicates human behavior. Thus the combination of both technologies systematically analyzes the data and reveals hidden patterns that provide better insight into customer behavior and leads to strategic decision making.
Artificial Intelligence and Machine Learning
Machine learning is a subset of Artificial Intelligence which is all about creating self-learning algorithms. It is a scientific study of statistical models and algorithms that equip the computer systems with the ability to learn from sample data without being programmed.
As per Arthur Samuel “Machine learning algorithms enable the computers to learn from data, and even improve themselves, without being explicitly programmed.”
Behind the Closed Doors
You are well acquainted with these technologies and have explored all its potential to the fullest. But it is also in the closed doors of your office. Have you tried moving out of the closed doors? Yes, specifically getting in the market and taking reviews from your customers, potential customers, and others. Taking strategic decisions behind closed doors with just the market details won’t help you mark your presence in the domain anymore. With predictive analysis joining hands with Artificial Intelligence and Big Data businesses have come a long way and so have the data analysis methods.
Machine Learning, Predictive Analytics, and Big Data
Predictive Analytics, a branch of machine learning which is a statistical technique used to examine huge sets of data to discover patterns, reveals new information that predicts failure points and future outcomes. When predictive analytics is used with big data, it helps business leaders to make data-driven decisions
Moving Out of Closed Doors with Predictive Analysis
Predictive Analytics is a roadmap to make strategically sound business decisions. To provide accurate and reliable predictions, predictive analytics integrates a number of techniques, for instance, AI, machine learning, data mining, modeling and statistics to process and examine stacks of data. Let’s learn the impact of using predictive analytics in business.
› Better Insight into Customer Behaviour
Predicting human behavior is the biggest challenge for any business. But with the power of analytics, businesses can influence customer behavior and predict their purchasing patterns. Knowing in advance what your customer wants and when to approach them can help retailers predict demand so that they can maintain the right inventory level which improves customer retention. Data can be collected through social media, CRM data, customer reviews, complaints, and customer queries. It also predicts the most promising leads so that businesses can focus only on those leads that bring the highest ROI.
› Significant Improvement in Supplier’s Network
Nowadays, the supply chains are very complex, wide-ranging and more multi-tiered than ever. Supply chain management is a continuous process and failure at any point can cause inefficient execution. Predictive models are based on historical data that forecast future demands, production requirements, logistics requirements and provide greater visibility throughout the supply network. Hence, it mitigates business risk by predicting future demands in a cost-efficient manner. With predictive analytics in e-procurement, business professionals can gain a better understanding of market requirements which reduces risk concerned with demand and supply, and can easily introduce new suppliers. It also leads to better compliance management.
› Easy Identification of Fraudulent Activity
Whether a company offers financial services or it is a healthcare provider, or any government agency, fraudulent activity certainly affects the integrity of the organization and adversely affects the profitability. Using fraud detection analytics enables businesses to discover potential fraudulent action before it even occurs. This technique uses the available data to identify the fraud patterns and spot fraudsters by applying predictive models to large volumes of streaming data. Keeping a check on suspicious behavior and malicious activity leads to the early detection of preparators before it causes any damage. Thus, it helps businesses to focus on core business practices so that they can provide better customer services.
› Affirmation to Improve Operation and Reduces Risk
In any manufacturing industry, the effective functioning of equipment plays a very integral role in the successful running of any business. But we cannot deny this fact that every machine needs maintenance during its lifespan. However, if it is planned, it can prevent unexpected downtime.
Predictive analytics and big data are used by hundreds and thousands of industries and businesses to bring more efficiency in operations. This technology ensures a seamless production process by monitoring, managing, and tracking the equipment/sub-systems and ensures the accomplishment of business goals. It is important that your business uses feedback and other data to improve the operations and bring better results.
› Highly Optimized Market Campaigns
Predictive analytics enables businesses to plot, create, direct, and implement future marketing campaigns effectively. All the marketing decisions are based on thoroughly analyzed data hence allow campaigns to target the right group of customers. It increases customer engagement, purchasing power, retention, and helps businesses predict and prevent churn. Sounds Interesting?
› Build Better Customer Relations
What about personalizing chats with your clients? It is a great idea!
This is an easy way to impress your customers to make them feel a little connected to your business. Breaking the shackles of traditional marketing is now the need of the hour. Just ads and campaigns won’t help, let your audience review your products, have an insight into your workspace, and let them suggest. Make them a part of the business so that they identify with it and feel an emotional connection.
This would help you build an empire that is not just difficult to conquer but to forget too.
And Closing the Story!
When you decide to take the big leap of using predictive analysis better in your business, be sure that you understand how it works. Not just this, you need to make this shift, that many businesses are still struggling with where they need to transform from being business-centric to audience-centric. The shift may be tough, but realize it is important to move with the trends.
Just be ready to let technology take you to the zenith and bring unimaginable profits!
