Customer Analytics - Relative Price as Data Point

Relative Pricing in Customer Behaviour Analytics

We had some discussion on Price Sensitivity earlier. This was used for determining the Right Price of offer for that customer. However, the price sensitivity is more related to Demand Elasticity

Relative Price is the price of a product/service with respect to another product/service. The latter one is usually termed as the base product/service.

How to use Relative Price to understand Customer Behaviour

Relative price provides very much useful insight about the customer's behaviour. The following would be the typical values for Relative price

• High
• Medium
• Low

The relative price is applied to each item based on a base item from that category. For example a segregating a customer based on the
different price preferences (Twinnings Tea might be a High valued one, while Tetley might be Medium priced; depending on the purchase behavior of each individual across category the following Relative Pricing Table is created)

Cust ID	Category	Premium	High	Medium	Low
RF0000123	OVGT120980	0	6	16	0
RF0000227	OVGT120980	11	3	2	0

Relative Pricing Customer Table

)Looking at the above table, one could distinguish between the customers - (for a particular category) - the second customer mostly shops for Premium items, while the former is a bit conservative.

The above methodology can be used and the following can be used as Segmentation variables

• No of High Value Items
• No of Medium Value items
• No of Low Value items

Please try this out and let us know the difference it brought to your segments

How to measure effectiveness of Switcher Campaigns in Retail 

Switcher campaigns are the one that disrupt brand loyalty and tease an otherwise loyal customer to switch over to the competitor. Tetley and Brooke Bond are competitors - what would be the impact of providing an offer on Brooke Bond tea for a Tetley fan.

dunnhumby's analysis on offers finds Switcher campaigns are always the worst performing. According to the reporthouseholds tend to buy more of their favorites, such as Coke products, or a new Coke product, if offered an incentive rather moving to Pepsi for example

Customer Attrition Modeling (Analytics)

Churn or Attrition Modeling

Customer is the key for any business. As Don Peppers once said - the only value that a company adds during the lifetime is the Customer.

Losing customer is losing business. But, how to avoid them moving away?

How to measure Customer Attrition

How to know if the customer is leaving . Probably if he/she is not shopping / visiting / interacting / subscribing like the past, it is an indication that he/she might leave.

Good datamining should measure the customer attrition easily. Predicitve models can be built on data for Customer attrition.

The key data points to be considered for Attrition modeling are the Recency, Latency, Average Spend per Visit, Average Time spent on Website, Duration of Visit (Website) etc

The predictive model then attaches a probabily score to each customer. The least churner to the most ..

How to retain the customer?

Starbucks has its own Loyalty program -My Starbucks Rewards™ . One in four customers use the Loyalty card, which provides a wealth of data for Starbucks analyitcs team. The customers are then analyzed and segmented. The customers who are more Loyal are ignored! Yes, the ones who are about to Churn are Rewarded with appropriate offers. The offers are based on the past purchase history!