Predictive Analytics is the process of dealing with variety of data and apply various mathematical formulas to discover the best decision for a given situation. Predictive analytics gives your company a competitive edge and can be used to improve ROI substantially. It is the decision science that removes guesswork out of the decision-making process and applies proven scientific guidelines to find right solution in the shortest time possible.
Predictive analytics can be helpful in answering questions like:
Who are most likely to respond to your offer?
Who are most likely to ignore?
Who are most likely to discontinue your service?
How much a consumer will spend on your product?
Which transaction is a fraud?
Which insurance claim is a fraudulent?
What resource should I dedicate at a given time?
Benefits of Data mining include:
Better understanding of customer behavior propels better decision
Profitable customers can be spotted fast and served accordingly
Generate more business by reaching hidden markets
Target your Marketing message more effectively
Helps in minimizing risk and improves ROI.
Improve profitability by detecting abnormal patterns in sales, claims, transactions etc
Improved customer service and confidence
Significant reduction in Direct Marketing expenses
Basic steps of Predictive Analytics are as follows:
Spot the business problem or goal
Explore various data sources such as transaction history, user demography, catalog details, etc)
Extract different data patterns from the above data
Build a sample model based on data & problem
Classify data, find valuable factors, generate new variables
Construct a Predictive model using sample
Validate and Deploy this Model
Standard techniques used for it are:
Decision Tree
Multi-purpose Scaling
Linear Regressions
Logistic Regressions
Factor Analytics
Genetic Algorithms
Cluster Analytics
Product Association
Source: http://ezinearticles.com/?Benefits-of-Predictive-Analytics-and-Data-Mining-Services&id=4766989
Predictive analytics can be helpful in answering questions like:
Who are most likely to respond to your offer?
Who are most likely to ignore?
Who are most likely to discontinue your service?
How much a consumer will spend on your product?
Which transaction is a fraud?
Which insurance claim is a fraudulent?
What resource should I dedicate at a given time?
Benefits of Data mining include:
Better understanding of customer behavior propels better decision
Profitable customers can be spotted fast and served accordingly
Generate more business by reaching hidden markets
Target your Marketing message more effectively
Helps in minimizing risk and improves ROI.
Improve profitability by detecting abnormal patterns in sales, claims, transactions etc
Improved customer service and confidence
Significant reduction in Direct Marketing expenses
Basic steps of Predictive Analytics are as follows:
Spot the business problem or goal
Explore various data sources such as transaction history, user demography, catalog details, etc)
Extract different data patterns from the above data
Build a sample model based on data & problem
Classify data, find valuable factors, generate new variables
Construct a Predictive model using sample
Validate and Deploy this Model
Standard techniques used for it are:
Decision Tree
Multi-purpose Scaling
Linear Regressions
Logistic Regressions
Factor Analytics
Genetic Algorithms
Cluster Analytics
Product Association
Source: http://ezinearticles.com/?Benefits-of-Predictive-Analytics-and-Data-Mining-Services&id=4766989
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