David Loshin

Customer Analytics: Classification vs. Segmentation

More than five years’ experience blogging for the Data Roundtable’s predecessor blog, the DataFlux Community of Experts, gives David an edge when it comes to knowing his audience well; he has a knack for addressing technical issues that resonate with readers.

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Posts by David Loshin:

Customer Analytics: Classification vs. Segmentation

Customer Analytics: Classification vs. Segmentation

Jun 18, 2013 by

Last time we looked at a starting point for a classification model for determining the “goodness” of customers, based on some selected dimensions of value, measures, weights, scores and classification levels and thresholds. That being said, these classifications divide your customer based on your criteria.

 

Ideas for Addressing Customer Classification

Ideas for Addressing Customer Classification

Jun 11, 2013 by

Last time we started to look at methods used in setting product prices, and I asked whether knowledge of customer type would contribute to the determination of a “fair” price for an item that might change in relation to customer type.

 

Pricing and Decision-Making

Pricing and Decision-Making

Jun 04, 2013 by

I have been thinking a lot about customer analytics recently, especially in the context of value pricing, and perhaps more pointedly, the determination of the right price to charge for an item. I am in the middle of reading an interesting book about the theory of prices called “Priceless: The Myth of Fair Pricing,” which describes some interesting concepts regarding anchoring that are used to set the context for establishing prices in a somewhat arbitrary manner.

 

The Advantage of Understanding Spheres of Influence

The Advantage of Understanding Spheres of Influence

May 28, 2013 by

In my last set of posts I discussed developing a graph/network representation of the entities that act within a community and the relationships between and among those entities. The objective, though, is to understand the different influences exerted by key individuals within the network and employ that knowledge in communicating a message (such as “buy my product!”) across that network.

 

The Customer Network: Spheres of Influence

The Customer Network: Spheres of Influence

May 21, 2013 by

In one of my previous posts, I introduced the idea of customer connectivity in the context of archetypical roles that Malcolm Gladwell describes in his book “The Tipping Point,” namely the connector, the maven and the salesman. And last time I introduced some concepts associated with the graph abstraction for representing relationships among a community of actors. Customer connectivity, as reflected in the many different types of actors and relationships, can be modeled as a social network graph.

 

Modeling the Types of Customer Connections

Modeling the Types of Customer Connections

May 14, 2013 by

Your community of customers, like any other community, consists of a collection of individual parties that can also be referred to as “actors” who are related to one another. These relationships can be modeled using the graph abstraction, in which every actor is represented as a node, and every connection between two actors is represented as a link or an edge between two nodes.

 

Customers and Connectivity

Customers and Connectivity

May 07, 2013 by

When you consider the development of strategies for integrating customer centricity into the breadth of business applications in different business functions, one emerging analytical focal point is social media analytics.

 

The Next Step: Enhancing the Master Data Via Data Warehouse Consolidation

The Next Step: Enhancing the Master Data Via Data Warehouse Consolidation

Apr 30, 2013 by

Last time we looked at how the tools and methods incorporated within a master data management system can contribute to ensuring the satisfaction of the success criteria for data warehouse consolidation. MDM provides some valuable capabilities that will simplify the consolidation processes.

 

Leveraging Master Data Management as a Tool for DW Consolidation

Leveraging Master Data Management as a Tool for DW Consolidation

Apr 23, 2013 by

In the past few postings we looked at some of the issues that emerge as a result of uncontrolled creation of data warehouses and data marts. I suggested that the goals of a data warehouse consolidation project should not only include the creation of a new data asset that accommodates the users of the “to-be-consolidated” warehouses and marts, but that those systems should be retired and replaced by the new asset.