Relationship of predictive analytics with other terms

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Increase the effectiveness of advertising campaigns . Predictive analytics allows you to forecast which advertising campaign will be most successful for a certain target audience, helping to reduce expenses on unnecessary advertising and focus on the most promising segments.
Identify market trends . Marketers can predict changes in consumer preferences and trends, which helps companies adapt to changes in advance and offer relevant products or services.
Predict customer churn . Using predictive models, you can identify which customers are most likely to churn and take steps to retain them in advance, such as offering discounts or personalized offers.

Predictive analytics is closely related to a number of other iceland phone number list concepts in analytics and marketing:
Descriptive analytics . This type of analytics focuses on what happened in the past. Unlike predictive analytics, descriptive analytics analyzes historical data, and predictions are based on forecasts for the future.
Prescriptive analytics . Prescriptive analytics goes further than predictive analytics by offering specific recommendations for action. While predictive analytics answers the question, “What will happen?”, prescriptive analytics answers the question, “What do we need to do to achieve the desired result?”
Machine learning : This is the key technology behind predictive analytics. Machine learning algorithms can learn from data, improving their predictions as new information is received.
Big data . Predictive analytics requires a huge amount of data, called big data, to work effectively. It is because of such data and powerful processing technologies that it is possible to make accurate forecasts.
Criticism of Predictive Analytics