Top down or bottom up

George Day (1980) presented model of segmentation as the top-down approach:  A person starts with the total population and divide it into segments.

 He also identified an alternative model which he called the bottom-up approach. In this approach, a person  starts with a single customer and build on that profile.

This  requires the use of customer relationship management software or a databas in which profiles of existing customers along with their different  demographic, behavioral, and psycho graphic patterns will be created and analyzed. This process is sometimes called database marketing or micro-marketing.  McKenna (1988) declares that this approach treats every customer as a "micro majority". Pine (1993) used the bottom-up approach in what he called "segment of one marketing". Through this process mass customization is possible.


Organizations apply segmentation to improve their customer retention programs which ensure that they are:

 Focused on retaining their most profitable customer  and employing these tactics most likely to retain these customers
The basic approach to retention-based segmentation is that a company tags each of its active customers with 3 values:

Tag #1: Is this customer at high risk of canceling the company's service? (Or becoming a non-user)
One of the most common indicators of high-risk customers is a drop off in usage of the company's service. For example, in the credit card industry this could be signaled through a customer's decline in spending on his card.

Tag #2: Is this customer worth retaining?
This determination boils down to whether the post-retention profit generated from the customer is predicted to be greater than the cost incurred to retain the customer.

Tag #3: What retention tactics should be used to retain this customer?
For customers who are deemed “save-worthy”, it’s essential for the company to know which save tactics are most likely to be successful. Tactics commonly used range from providing “special” customer discounts to sending customers communications that reinforce the value proposition of the given service.

Process for tagging customers

The basic approach to tagging customers is to apply  historical retention data in order to make predictions about active customers regarding:

* Whether they are at high risk of canceling their service
*  Whether they are profitable to retain
*  What retention tactics are likely to be most effective

The idea is to match up active customers with customers from historic retention data who share similar attributes. Using the theory that “birds of a feather flock together”, the approach is based on the assumption that active customers will have similar retention outcomes as those of their comparable predecessors.

From a technical perspective, the segmentation process is commonly performed using a combination of predictive analytics and cluster analysis.

Price Discrimination

Where a monopoly exists, the price of a product is likely to be higher than in a competitive market and the quantity sold less, generating monopoly profits for the seller. These profits can be increased further if the market can be segmented with different prices charged to different segments (referred to as price discrimination), charging higher prices to those segments willing and able to pay more and charging less to those whose demand is price elastic. The price discriminator might need to create rate fences that will prevent members of a higher price segment from purchasing at the prices available to members of a lower price segment. This behavior is rational on the part of the monopolist, but is often seen by competition authorities as an abuse of a monopoly position, whether or not the monopoly itself is sanctioned. Examples of this exist in the transport industry (a plane or train journey to a particular destination at a particular time is a practical monopoly) where Business Class customers who can afford to pay may be charged prices many times higher than Economy Class customers for essentially the same service. Microsoft and the Video industry generally also price very similar products at widely varying prices depending on the market they are selling to.