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Customer Segmentation @ AbsolutData
All the customers are not alike & have varying needs and wants based on their demographics, belief, attitudes, and behaviors. By understanding the different customer segments in the market place, marketers can develop customized Marketing and Communication Strategies to attract target customers.
AbsolutData offers multiple segmentation approaches to divide the market or the customer-base into meaningful and measurable clusters based on one or a combination of the given segmentation frameworks
1) Psychographic Segmentation
* Identifying Customers needs, wants & attitudes
* Based on market survey on subjective ideas
* Useful for co-relation with customer demographic & behavior
2) Demographic Segmentation
* Identify Where my Customers are, based on customers age, gender profession.
* Useless without co-relation with customer behavior
* Demographic Data - Not readily available and reliable
3) Behavioral Segmentation
* Identify Who are my Customers, based on customers usage data
* Immediately expandable for complete customer base
AbsolutData Segmentation Techniques:
* Hierarchical - Agglomerative & Divisive Methods: Merges the Sub-Clusters into desired number of clusters
* K-Means Algorithm: A non-hierarchical process following combined methods of parallel threshold and optimization techniques
* Two-Step Clustering: Divides the data into many Sub-Clusters
* Expectation Maximization Algorithm (Latent Gold): A probabilistic method of dividing the data into different clusters based on the maximum likelihood of each case belonging to a particular cluster
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