Predictive analytics targets data to predict if ATL advertising is more effective than BTL advertising and to target customer segments and characteristics.
2. A company can determine the influence of the marketing
and advertising campaigns on sales and identify whether
marketing expenses are effective for the business and
optmize the marketing budget to increase sales or ROI.
Marketing Optimization
Sample Application
Description
5. To solve this problem, we first need to identify the
relationship between advertisement expense and sales
using a correlation algorithm. Correlation is a statistical
measure that indicates the extent to which two variables
fluctuate together.
• A positive correlation indicates the extent to which those
variables increase or decrease in parallel.
• A negative correlation indicates the extent to which one
variable increases as the other decreases.
Algorithm(s)
Marketing Optimization
Sample Application
9. Once the relationship is identified, we can further predict
sales using regression algorithm.
• Multiple Linear Regression is a technique that attempts to
explore the relationship between two or more
independent variables and one dependent variable.
• The higher the R-square value of a model(>=0.7), the
better the accuracy of the model.
• A lower R-square value of a model(<0.7) means the model
needs to be rebuilt using different input parameters or the
input dataset doesn't exhibit a structure suitable for
regression.
Algorithm(s)
Marketing Optimization
Sample Application
18. Marketing Optimization
Predictive Analytics Use Case
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Smarten – Marketing Optimization Use Case - 2019