{"id":19172,"date":"2024-07-11T12:29:21","date_gmt":"2024-07-11T16:29:21","guid":{"rendered":"https:\/\/illumin.com\/?p=19172"},"modified":"2025-01-30T06:04:07","modified_gmt":"2025-01-30T11:04:07","slug":"predictive-ai-an-introduction","status":"publish","type":"post","link":"https:\/\/illumin.com\/insights\/blog\/predictive-ai-an-introduction\/","title":{"rendered":"Predictive AI: an introduction"},"content":{"rendered":"

Predictive AI gives marketers the ability to boost performance, mitigate risk, and optimize processes. But what is predictive AI and how does it work?\u00a0<\/span><\/p>\n

Also sometimes referred to as enterprise machine learning, predictive AI is a go-to for boosting performance and efficiently planning future campaigns. While this technology is often used in manufacturing, fraud prevention, and supply chain management, it can also be used in advertising. However, its use in the industry has yet to reach its full potential.\u00a0<\/span><\/p>\n

What is predictive AI?<\/span><\/h2>\n

Predictive AI forecasts future events by identifying patterns and making appropriate decisions based on past behavior. It does this by using advanced statistical models and machine learning algorithms.<\/span><\/p>\n

The predictions of this tech can drive millions of decisions a day, processing data to create meaningful and educated guesses as to what a consumer will do next. This information can then be used to plan campaigns and effectively target audiences \u2013 cutting out time and effort and driving efficiency.\u00a0<\/span><\/p>\n

What are the benefits of predictive AI?<\/span><\/h2>\n

Predictive AI has a great number of benefits for advertisers. It improves efficiency and provides them with accurate information for improved planning.\u00a0<\/span><\/p>\n

AI models speed up decision-making with accurate and informed predictions by analyzing patterns and identifying anomalies in data. It extrapolates what might happen next to enhance planning and speed up forecasting activities.\u00a0<\/span><\/p>\n

Marketers spend countless cycles researching and tracking consumer behavior to plan their next campaign. Predictive AI cuts this time down and gives them time back in their day for other crucial marketing activities.\u00a0<\/span><\/p>\n

Predictive AI also gives marketers high returns while making it easy to provide improved customer experiences. It is estimated that UPS <\/span>saves $35 million each year<\/span><\/a> by using predictive AI to optimize its delivery planning. Advertisers can leverage this same power to predict which customers are more likely to buy and when.\u00a0<\/span><\/p>\n

What are the uses of predictive AI?<\/span><\/h2>\n

Fraud detection\u00a0<\/span><\/h3>\n

Predictive AI analyses patterns to identify potentially suspicious activity sooner. A good example of this is flagging access from new locations or from a new device. This helps advertisers mitigate risk by flagging potentially fraudulent purchases or hacked accounts.\u00a0<\/span><\/p>\n

Forecasting\u00a0<\/span><\/h3>\n

Predictive AI models use historical data to set a precedent in trends, risks, and opportunities. It then forecasts future activity with improved accuracy, augmenting decision-making with reliable, efficient data analysis. This is a great way for advertisers to plan ahead.\u00a0<\/span><\/p>\n

Behavior analysis<\/span><\/h3>\n

Predictive AI can also use data sets to predict customer behavior. This data can include purchase history, shopping patterns, and devices used to predict where and what potential and current customers will look for next. This can help advertisers plan and target campaigns.\u00a0\u00a0<\/span><\/p>\n

Machine Learning is at the center of predictive AI<\/span><\/h2>\n

Machine Learning is the base on which predictive analytics are built. This subset of AI lets computers learn from data and make decisions according to past information. Machine Learning lets computers act without being specifically programmed for tasks. These capabilities are the foundation of predictive AI, which grows as it processes large datasets.\u00a0<\/span><\/p>\n

An AI algorithm analyzing website visitor information and differentiating between bot and human traffic is an example of Machine Learning in action. Likewise, these algorithms can analyze past consumer behavior and predict future visits and purchases.<\/span><\/p>\n

Predictive AI relies on pattern recognition<\/span><\/h2>\n

Predictive AI works by recognizing patterns in past behavior and using those patterns to make an educated guess about what actions will follow. From complex patterns with hundreds of variables to simple consumer behaviors, predictive AI can break down and analyze data efficiently for effective decision-making.\u00a0<\/span><\/p>\n

Using advanced analytics, predictive AI lets advertisers make informed decisions about their ongoing and future activities. Understanding potential future events makes it easy for advertisers to choose where and when to buy ad space and where to save their ad spend for the highest impact and highest efficiency.\u00a0\u00a0<\/span><\/p>\n

illumin\u2019s AI algorithm can highlight the most cost-efficient route to conversion and give you insights into the entire consumer journey. illumin\u2019s <\/span>Pathlight analysis<\/span><\/a> will help you optimize your media mix and ad frequency while also saving you time by generating, analyzing, and exporting your data for you.<\/span><\/p>\n

By using a wide range of data from various sources, including interactions, device information, cookies, hashed email addresses, hashed phone numbers, and more, Pathlight analysis creates a holistic and accurate representation of user identities across multiple devices and platforms.\u00a0<\/span><\/p>\n

Predictive AI is the new frontier of forecasting. It is the most efficient way to understand future trends and behaviors. By leveraging machine learning techniques to digest data, this AI makes educated predictions about future behaviors to help marketers make informed and impactful decisions.\u00a0<\/span><\/p>\n

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