There are many ways to analyze customer data. We present here the approach that may be taken with the tools that are available with Cortana Intelligence.
- Do some basic business analysis - get to know the customer, get to know the data, do some simple charts to see how revenue changes, margins change, what products sell the most etc.,
- Then do customer segmentation to group similar customers together and away from other groups,
- Then identify some segments that are more price conscious than others,
- Develop a machine learning model that calculates price elasticity
- Identify high selling products (X), that most customers buy
- Use this ML model to estimate price elasticity per segment for high selling products
- Then find a couple frequently bought together products (Y) with each of the high selling products using FBT model
- Find a couple recommended products (Z) for each of the high selling products using recommendation machine learning model
- Take X,Y,Z together and estimate cross-price elasticity using price elasticity model; so you can say what happens to demand for Y and Z when price for X is lowered
- Then predict demand for X,Y,Z using demand forecast model that takes into account price elasticity and cross price-elasticity
- Now you know how much of each is likely to sell for different price points of X, so now calculate revenue, margin (assuming you have costs)
- Offer this to a price professional who has the knowledge & authority to decide which price to chose for which segment of customers for next promotion
- Go next step, and use some optimization capability to automatically optimize, but in our experience, pricing experts want to have control so they are not looking to automate this step
- Run the actual promotion, collect actual sales data and feed it to all the models so they stay current
- In the end, use customer churn machine learning model to find customers at risk, see what segment they belong to, estimate if price is putting them at risk, evaluate if they should be offered something exclusively in next promotion run
You will see some of the elements above in the series of posts in this blog.
Now, let's get to know the company we are going to work with.