Being successful in business is about getting ahead of the curve. Cracking your knuckles, doing the research, and getting down to work making educated guesses about the future. This is an entrepreneur or marketer’s biggest advantage – being a step ahead. But how can any marketer do this when the future hasn’t happened yet? The simple answer? AI and predictive analytics.

It may seem like something out of a sci-fi movie, but businesses have been using predictive analytics for a long time. The predecessor of machine learning, predictive analytics, and artificial intelligence was a more humble form of data science. This was employed by Henry Ford who used data trends and predictive models while building Ford. As computers became more popular and accessible in the sixties, data collection and data scientists advanced.

Jump to 2022 and you can utilize data for B2B lead nurturing, refining content strategies and so much more. In fact, predictive AI has a market size of over $12.49 billion, making predictive analytics an undeniable phenomenon. In fact, it will reportedly get to $38 billion by 2028. Let’s explore.

Predictive analytics: What is it?

Before we can unpack the level of potential predictive analytics has for marketers, we need to get to the bottom of what it is. Simply put, it’s a process that uses artificial intelligence and machine learning to identify data trends and possible outcomes.

Predictive analytics can analyze your historical business data using advanced AI algorithms. This minimizes work for data analysts and enables you to improve the quality of business decisions. It can also elevate your current data by decreasing the risk of human error.

What can you do with this data? Identify trends, improve the accuracy of your forecasting, gain a better understanding of consumer behavior, and mitigate risk. But before we get into the application, there’s more to understand about the mechanics.

How predictive analytics works, in a nutshell

It all starts with raw data, which is unprocessed and usually includes a wide range of inputs (info). This data can come from a range of sources, such as sensors, databases, or user interactions. In the beginning, it’s often messy and unstructured.

This is why raw data needs to be cleaned and transformed into a usable format. Enter data reprocessing – combining, formatting, and cleaning raw data analysis results, for more usable inputs.

If your data involves text, like customer reviews or social media posts, Natural Language Processing plays a part. This is a subfield of AI that focuses on the interaction between computers and human language. It’s used to extract meaning, sentiment, and patterns from textual data, making it valuable for predictive analytics. This is especially true in tasks like sentiment analysis or creating chatbot responses.

Recurrent neural networks (RNNS) have a kind of memory that allows them to process sequences of data one step at a time. In doing so, they maintain information about previous steps as they move forward.

There’s more to the intricacies of how it works but these are the building blocks for predictive analytics.

Predictive analytics or generative AI models?

All clear so far? That’s good news but now the tough question: Where do AI models like Midjourney and ChatGPT come in? They don’t seem the same. This is because platforms like this are different from predictive analytics and focus more on content than data.

So let’s do a quick comparison. Predictive analytics and AI use historical business data to give you a glimpse into the future. This means predicting patterns, trends, and behavior. Generative AI is about creation. This could be creating images, text, sounds, and even code (with machine learning). Both need artificial intelligence to work, but their purposes are different.

With this in mind, you might use predictive analytics in industries like finance and market analytics. Generative AI models work better for creative and marketing industries.

Both of these AI approaches have their roles to play, and they’re gaining traction in various industries. In fact, experts project an impressive annual growth rate of 37.3% between 2023 and 2030.

But why? What’s so great about predictive analytics?

Because the benefits are becoming increasingly clear. AI, in general, is a time and money-saver but what are the more intricate benefits of predictive analytics?

1. Futureproofing your business efforts

Staying at the forefront of your industry is about having a competitive edge, and that’s precisely what AI tools like predictive analytics can provide. They let you harness past data to predict future trends and outcomes, empowering you to strategize ahead of time and take a proactive approach to your business’s future.

2. Enhancing efficiency

When your predictive data is on point and your forecasts are spot-on, it means fewer repetitive tasks and fewer errors, which in turn helps you simplify and streamline your business processes.

3. Quicker decision-making and execution

In the world of marketing, decisions revolve around data. The more precise your data, the smarter your choices become. Predictive analytics provides you with the right data precisely when you need it, so you can make quicker, more impactful decisions.

4. It’s easier to identify and work with patterns

Have you ever thought about using your own data to uncover hidden patterns that can help you spot opportunities, tackle challenges, and find solutions? Well, that’s precisely what predictive analysis does. It taps into the power of machine learning to spot these patterns and provide valuable guidance.

5. Forecasting trends and planning for new threats and opportunities

Your data is like a goldmine of insights, and predictive AI is here to tap into that wealth of knowledge. It does this by crunching numbers, harnessing machine learning, and digging deep into your data through methods like data mining.

The result? Predictive analytics can anticipate customer behavior, upcoming events, and emerging trends. This is what makes it such a powerful tool in digital analytics.

Applying predictive analytics models

One of the exciting things about predictive AI is its adaptability. It’s like a Swiss Army knife for improving productivity, increasing earnings, and making everything run smoother. Predictive analytics has the potential to positively influence a wide range of industries, including:

Retail

In the world of retail, predictive AI is like your shopping companion. It’s always there to track market trends and your customers’ buying habits, following their journey from start to finish. The retail industry moves at lightning speed, and that’s where AI truly shines. It’s like having a smart assistant that can analyze, adapt, and respond in the blink of an eye. Wondering which products will fly off the shelves or which promotions will seal the deal? Predictive models have insight into the answers.

Healthcare

In healthcare, there are plenty of opportunities to gather data from patients and medical centers worldwide. With the capabilities of AI models and predictive analytics, algorithms can step in to recommend treatments, provide personalized care, and even foresee potential epidemics. This is how AI steps in not just to enhance diagnoses but also to play a vital role in saving lives along the way.

Mechanical and automotive

With the help of machine learning, predictive analytics can spot manufacturing issues before they happen. And, looking ahead, predictive AI could take it a step further by aiding in the development of cutting-edge automotive tech and self-driving cars, all based on a deep understanding of how drivers behave.

Financial services

Predictive analytics and the financial industry make a dynamic duo. When it comes to spotting trends and using machine learning on financial data, they’re a good match. It’s fast, accurate, efficient, and has the potential to enhance innovation in finance.

Real-world predictive analytics tools

There are already a range of predictive tools on the market. Let’s take a look at two examples:

1. Predict AI

What’s useful about Predict AI is its foundation – a hub of eye-tracking data collected from over 120,000 people, along with 100 billion brain response data points.

With these neuroscience insights as its backbone, Predict generates creative insights quickly. This not only boosts conversions but also predicts human behavior with good accuracy.

Thanks to Predict’s AI tech, you can gain a deep understanding of how and why customers respond to your brand and advertisements.

2. Dragonfly AI

Although it may have started out as an app, today the Dragonfly AI platform is known for its emphasis on content performance.

With a full product suite focused on visual predictive analytics, Dragonfly’s Studio desktop solution offers a range of AI tools. They were created to help you increase your ROI, test your performance, A/B test your work, and streamline your design process.

With a mobile app for iOS and a browser extension, it’s versatile and flexible, and leverages AI technology well. All so that the right messages reach the right customers at the right time.

Is predictive analytics a good fit for your business?

Predictive analytics takes the intricate and tedious work out of data analytics to some extent. This gives businesses like yours the chance to apply more resources to implementing business logic.

Machine learning and artificial intelligence aren’t just futuristic dreams; they’re our current reality. And they’re only getting smarter with time.

The question is, are you ready to let your competitors get ahead in foreseeing market trends and understanding customer behavior? Or will you take the plunge into the world of predictive AI and discover its potential for yourself? If you’d like to find out more about how predictive analytics can benefit your business, take a look at the original post here.

YDA can help you make the most of predictive analytics in your business

At YDA, we understand the potential of tools like Predictive AI and Neurons. In fact, we use these tools in our design process to give our clients the best foundational data. Together we can implement an efficient, AI-powered data analysis in your business. Set up a call with us to find out how.