Predictive AI (predictive analytics) has the lowest barrier to entry of any artificial intelligence technology. It is a proven use case that makes introducing AI into your organization seamless and more likely to succeed.
The predictions made by predictive AI drive millions of decisions every single day. This technology can quickly process data and give marketers accurate and meaningful predictions about consumer behavior. Marketers can use this information to easily plan and adjust campaigns, reaching their target audience effectively and efficiently.
The Machine Learning used in predictive AI speeds up decision-making by providing marketers with accurate and informed predictions. It does this by analyzing patterns in data and identifying anomalies. Predictive AI algorithms can then easily extrapolate the most likely future behaviors of one’s target audience.
Predictive AI may not command the same buzz as other forms of artificial intelligence, but it is by no means irrelevant. The predictive AI market is growing, and fast, with forecasters estimating it will reach $64 billion in 2025. Predictive AI is where the money is – it is a proven use case with a lower barrier to entry than most other tech and AI.
This technology is both proven to work and easy to adopt, it makes it a no-brainer for a first step into the work of artificial intelligence.
Predictive AI in advertising
In advertising, predictive AI has the potential to rapidly increase efficiency. Advertisers spend a lot of time and resources researching and tracking consumer behavior – time that can be spent better elsewhere in their process. By using predictive AI, advertisers can cut this time down and redistribute resources to more interesting and impactful tasks like creative planning.
So how exactly can marketers leverage this technology to improve performance? Two main uses for predictive analytics in advertising are:
Creating personalized experiences:
Predictive AI can be used to track and predict user behavior, making it easier to provide them with seamless, custom experiences like personalized discounts and homepages.
Marketers can use customer data to better understand what customers are looking for next, and plan custom experiences accordingly. If a customer typically shops for clothes during specific times of the year, predictive analytics can forecast when they are likely to shop next. Marketers can then use this information to send personalized discounts to encourage that customer to make future purchases.
Improved targeting:
Predictive AI can also be used to effectively forecast future customer behavior. By tracking and predicting future interests and buying patterns, advertisers can plan, create, and place better-targeted ad campaigns.
By processing customer data with predictive analytics technology, marketers can understand what customers are going to be watching in the future, rather than solely relying on what they’ve watched in the past. This information can then be used to place ads in the most effective way possible.
Predictive AI gives advertisers a significant advantage by letting them easily forecast and plan. It lets them leverage data and the power of machine learning for pattern recognition. This opens up new opportunities and gives them crucial time back in their day for roles that require an essential human touch (such as brainstorming and creation).
With data and sophisticated forecasting at their fingertips, marketers are empowered to make informed, data-driven decisions without sacrificing time and resources they don’t have. Predictive AI is not only tried and tested, but it is also easier to adopt into organizational practices without disturbing existing workflows – falling seamlessly into place and supporting existing roles.
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