It may not be true in all industries, at least not yet, but countless businesses across all sectors are finding use cases for emerging technologies like predictive AI. With predictive AI, it’s possible to analyze massive data sets, finding patterns that can help identify future events. It has become a way for companies to improve the customer experience, make educated decisions, improve their operational efficiency, and so much more. The best way to better understand what predictive AI can do is to look at some of the specific use cases.
Forecast Customer Demand
With predictive AI, companies can gather huge data sets, including recent market trends, historical sales, and seasonal trends, to generate accurate forecasts about what customers will want in the future. By identifying patterns that might go unnoticed by humans, it uncovers deeper insights into the drivers of demand. For example, a business can combine data about economic shifts, customer sentiment, and social media trends to predict the popularity of certain products. This allows businesses to be proactive when it comes to meeting customer demand, giving them a leg up on competitors.
Customer Personalization
Modern customers crave a personalized experience in which companies treat them as individuals, not just another customer. That’s possible with predictive AI, which can look at the trends of individual customers. Based on that information, companies can predict products they will like or marketing promos that fit them. Few industries have done this better than online casinos, which commonly use emerging technologies to improve the customer experience. Online casino platforms can look at the games customers have played in the past and their playing habits to recommend new games they might enjoy. Given the wide selection of casino games available these days, players often need help identifying the games they’ll enjoy most, which is where predictive AI comes in handy.
Supply Chain Management
Managing supply chains has never been more challenging. There is growing complexity, making disruptions harder to anticipate. Naturally, those disruptions can be harmful since today’s customers are less patient than past generations. This is where predictive AI can be useful in analyzing both historical and real-time data about logistical trends, shipping routes, and even the performance of certain supplies. Given all of this information, predictive AI can identify possible bottlenecks in advance, allowing a business to plan ahead and make the necessary adjustments to avoid the massive waste of time and money that comes with supply chain hiccups.
Prevent Customer Churn
We mentioned using predictive AI to predict customer behavior and improve the customer experience, so it makes sense that it can also be used to prevent customer churn. AI models can detect patterns that indicate customers are unhappy and more susceptible to churn. Rather than customer service employees poring through all of this data, AI can spot negative interactions, reduced engagement, or a lack of customer activity. To go one step further, AI also helps uncover the underlying reasons behind customer churn. This insight enables companies to take action that can address past problems and the reason for potential churn to help save the relationship with that customer.
Fraud Detection
This might be the most important use case for predictive AI. Businesses can get into a lot of trouble if they allow their customers to become the victims of fraud or allow sensitive data to be leaked. Luckily, predictive AI is well-suited for enhancing cybersecurity, thanks to its ability to detect suspicious activity in real time and adapt to evolving fraud techniques. It can continuously monitor data for anomalies like unusual login locations, sudden account changes, or atypical transactions. Predictive AI can understand both historical incidents and new threats to give any business a head start on dealing with any potential fraud, reducing the risk of such an event having negative consequences for a business.
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