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Predictive analysis is a branch of advanced analytics that is used to forecast unknown future events. It is used to analyze current data and make predictions using a variety of approaches, including data mining, statistics, modeling, machine learning, and artificial intelligence. Predictive analytics models record relationships between various elements to quantify risks or opportunities for a specific set of conditions.
Reasons to Consider Predictive Analytics
Standard business information and reporting provide insights that are not immediately actionable; businesses must turn them into action with their analysis and judgment. On the other hand, predictive analytics is developed exclusively to provide decisive action imperatives. It helps organizations make well-informed business decisions without involving human judgment. Organizations can use predictive analytics to:
- Develop a competitive edge by leveraging meaningful business insights
- Understand customer journey and behavior and leverage this understanding to increase sales and provide excellent customer experience
- Recommend new products to customers based on their purchasing behavior or search patterns
- Analyze customers’ purchase capacity, needs, and other behavior, and evaluate opportunities for up-sell and cross-sell
- Deliver quick gratification to customers through personalized suggestions and recommendations
- Prevent fraud by anticipating possibilities of a security breach
- Read industry versus organization trends and make necessary adjustments to remain profitable
- Determine the likelihood of customer churn
The Added Benefits of Predictive Analytics
Apart from helping businesses predict outcomes, and therefore, making informed business decisions, predictive analytics also helps organizations improve their business operations and refine their marketing campaigns.
- Many companies use predictive models to forecast inventory and manage resources. For example, airlines use it to determine ticket prices, restaurants use it to predict daily footfalls and increase profit margins.
- Several businesses use predictive analytics to fine-tune their marketing campaigns. They recognize the most successful combination of product bundles, content, medium, and timing to target a specific consumer. These techniques help them attract, retain, and engage their most valuable customers.
Predictive analytics not only analyzes but also learns from client actions and habits. The data gathered from these predictive models, can also be refined to provide crucial parameters such as the day of the week on which consumers redeem a specific offer. Companies can offer highly relevant recommendations tailored to their customers’ needs thanks to the rich data predictive analytics offers.
How Synoptek Can Support Your Predictive Analytics
Synoptek has a highly skilled team with a broad spectrum of functional and technical knowledge related to predictive analytics. Predictive analytics is an offering under our Artificial Intelligence service.
As businesses seek to nurture more relevant and meaningful connections with consumers, our predictive analytics service, tailored to their individual needs, allows them to create and sustain long-lasting customer relationships.
Other related service offerings provided by Synoptek are:
To know more about Predictive Analytics, click here.