"Predictivepredictive" Example Sentences
1. The use of predictive analytics helped the company to make accurate predictions of customer behavior.
2. The predictive model provided by the software proved to be very effective in forecasting market trends.
3. He presented his findings to the team and emphasized the importance of using a predictive approach to make informed decisions.
4. The scientists used a variety of predictive algorithms to analyze the data and make predictions about future outcomes.
5. The company invested heavily in developing a new predictive system that would give them an edge over their competitors.
6. The report showed that the predictive power of the model was much higher than previously thought.
7. The data analyst used a combination of statistical methods and predictive modelling to make forecasts about future sales.
8. The software relied on predictive learning algorithms to identify patterns in the data and make predictions about future trends.
9. The predictive value of the test was proven to be very high in identifying people at risk for developing the disease.
10. By using predictive analytics, the team was able to identify potential problems before they became major issues.
11. The predictive algorithm accurately predicted a spike in demand for the product, allowing the company to adjust their inventory accordingly.
12. The predictive capability of the system allowed the team to make informed decisions about where to allocate resources for maximum impact.
13. The data scientist used a range of predictive tools to develop a model that accurately forecasted sales for the quarter.
14. The predictive power of machine learning algorithms has revolutionized the way we analyze and interpret data.
15. The predictive model was refined over time as new data came in, allowing for greater accuracy in forecasting future outcomes.
16. The company utilized predictive analytics to improve their marketing strategy and target customers more effectively.
17. The predictive value of the test for diagnosing the illness was found to be very high by medical researchers.
18. The team relied on the predictive insights provided by the software to make decisions about resource allocation in different markets.
19. The predictive model was built using a wide range of data sources, including customer feedback and historical sales data.
20. The predictive algorithm took into account a variety of factors that could impact the outcome, including weather conditions and consumer behavior.
21. The predictive capabilities of the system allowed the team to accurately forecast demand for the product and adjust their production accordingly.
22. The report highlights the importance of using predictive analytics to anticipate changes in the market and stay ahead of the competition.
23. The predictive value of the test was found to be very useful in identifying individuals at risk for developing the disease.
24. By utilizing predictive algorithms, the company was able to improve their supply chain management and reduce waste.
25. The predictive model was trained using a large dataset, allowing it to accurately forecast outcomes even in highly complex situations.
26. The predictive capabilities of the software allowed the team to quickly identify anomalies in the data and take corrective action.
27. The data analyst used predictive modelling to forecast future revenue streams for the company, allowing for better financial planning.
28. The predictive model was designed to take into account unexpected events, such as natural disasters or changes in consumer behavior.
29. The software provided predictive insights that helped the team to optimize their website for better user engagement and conversion rates.
30. The predictive value of the test was found to be very high in identifying early warning signs of the disease.
Common Phases
1. Predictive analytics can anticipate future events; predictive maintenance can detect impending equipment failure.
2. Predictive modeling uses statistical algorithms to forecast outcomes; predictive marketing analyzes consumer behavior to inform advertising strategies.
3. Predictive policing utilizes crime data to preempt criminal activity; predictive healthcare uses medical data to anticipate health issues.
4. Predictive weather forecasting predicts atmospheric conditions; predictive inventory management forecasts product demand.
5. Predictive hiring assesses job candidate suitability; predictive fraud detection flags potential financial scams.