Pricing optimization

Finding the ideal price for a product can be very challenging. There are many factors that can influence the price and the behavior can be counterintuitive as lowering prices can raise revenue and vice versa. Further, the ideal price can be influenced by alternative products (both within the company) and from competitors as well as your own marketing efforts.

Overview

Predict the sales volume for a given product and use that information to find the optimal price.

TARGET

Price for each product.

Challenge

While most of the data will come from the pricing and sales database, you will need to aggregate this at a reasonable (weekly or monthly) level and identify the average selling price and how many discounts were in place. Information on competitive products price and discounts and external events during the same time period needs to be added. To this, any marketing campaigns should be included. Finally, inventory information should be merged. All this data needs to be cleaned, joined and transformed into valuable ML features before going into model training. This pre-modeling prep process can be frustrating and time consuming. We are here to help.

Modeling techniques and libraries

Machine learning analysis

Build machine learning models to predict the target as a function of the independent variables. Use model interpretability packages to evaluate the impact of the independent variables on the prediction.

Packages:
  • Sklearn
  • ELI5
  • LIME
  • SHAP

Price optimization

Find the optimal product prices to maximize revenue.

Package:
  • CVOXPT
  • pyOpt
  • scipy.optimize

Data features

Competitor Ad Volume
Competitive Marketing
Data Type
Continuous
Target
No
Yes
Competitor GRP
Competitive Marketing
Data Type
Continuous
Target
No
Yes
Day of Week
Calendar
Data Type
Categorical
Target
No
Yes
Discounts
POS
Data Type
Continuous
Target
No
Yes
Event
Calendar
Data Type
Binary
Target
No
Yes
GRP for Ads
Marketing DB
Data Type
Continuous
Target
No
Yes
Holiday
Calendar
Data Type
Binary
Target
No
Yes
Price
Competitive Marketing
Data Type
Continuous
Target
No
Yes
Price
POS
Data Type
Continuous
Target
No
Yes
Purchase Price
CRM
Data Type
Continuous
Target
No
Yes
Total Sales Dollars
CRM
Data Type
Continuous
Target
No
Yes
Total Sales Volume
CRM
Data Type
Continuous
Target
No
Yes

Related accelerators

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