How Predictive Analytics Helps Businesses Grow Faster
Predictive Analytics is the future of data analytics. It helps businesses to grow faster by predicting future outcomes based on historical data.
Businesses use predictive analytics to discover hidden patterns in their existing data, which they can then apply to make informed business decisions.
Predictive analysis uses statistics, modeling, machine learning, and artificial intelligence techniques to analyze current data and historical facts and make predictions about future or unknown events.
What is Predictive Analytics?
In simple words, predictive analytics is a branch of advanced analytics which is used to forecast unknown future events. For that matter, predictive analytics uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data and make predictions.
Furthermore, predictive analytics relies on the availability of historical data or transaction data. This data also helps in building predictive models which are then used to predict future events.
However, predictive analytics is not only about predicting the future; it also helps in understanding the past and present scenarios better by analyzing historical and transactional data.
The predictive analytics process for businesses usually follows these steps:
- Define the business problem and objectives
- Data Collection and Preparation
- Data Modeling
- Prediction and Evaluation
Noteworthy, Predictive Analytics can be used in many business areas such as:
- Marketing
- Retail
- Banking
- Finance
- Insurance
- Telecom
- Utilities
How does the Predictive Analytics process work?
Predictive analytics starts with data collected from various sources, including social media, CRM software, mobile apps, etc. The data is then analyzed using various statistical methods, including data mining, predictive modeling, machine learning algorithms, and artificial intelligence. The insights derived from the analysis are used by businesses to predict future trends, outcomes and results.
Altogether, Predictive analytics is broadly used in marketing, science, and technology. Its main purpose is to allow businesses to make confident decisions that can help their growth.
Using predictive analytics for business can help you:
- Choose the right customers to invest in;
- Improve operational efficiency;
- Identify profitable revenue opportunities;
- Forecast demand as per factors, such as seasonality, holidays, and secular trends;
- Understand risks and take preventive measures to minimize business risks;
- Gain insights into customer behavior to improve customer experience;
- Helps banks, credit card companies, mortgage lenders, and other financial institutions to identify fraudulent transactions and offer their best rates to customers;
- Predict churn rate, customer lifetime value, and set other KIPs;
- Collect and analyze flight data concerning each route distance and altitudes;
- Find the fastest routes considering traffic congestion, distance, weather, and delivery points.
And just like that, Predictive analytics offers various benefits for nearly all industries.
3 Areas Where Predictive Analytics Is Most Used
- Customer Retention: Imagine being able to predict when customers are likely to churn. Knowing this information, companies can take steps such as offering special incentives or discounts to keep them on board for longer.
- Fraud Detection: Predictive analytics can help detect fraud such as credit card fraud by monitoring transactions for suspicious patterns and behaviors that indicate fraud.
- Marketing Campaigns: Predictive analytics can help marketers plan campaigns based on the likelihood that customers will respond positively or negatively to various offers.
Conclusion
We have already seen how Big Data has had a huge impact on our lives and businesses around the world. And now there’s even more advanced technology out there, right at the tip of everyone’s tongue. We call it Predictive Analytics.
The predictions made using predictive analytics are often based on statistical analysis. But machine learning techniques that examine historical data to identify trends and patterns within it can also be used. Besides, predictive analytics helps businesses make better decisions about everything from product pricing to staffing levels.
So, when are you planning to leverage Predictive Analytics?