L M H

L M H       Data    Modelling

L M H Data Modelling provides customer response models for home shopping companies.  These include catalogue publishers, e-commerce marketers and multi-channel enterprises.

LMH models fall into the general category of RFM (recency, frequency and monetary value) models.  However, they are far more sophisticated than the normal grouping approach (e.g., 0-12 month multi-buyers, 13-24 month single buyers, etc.) used by most companies.  They rely on a complex, pattern-recognition algorithm that the founders of LMH invented and have developed over the last few years.  LMH models show significant net contribution improvements over traditional approaches.

The response models that LMH builds are based on prior transactions undertaken by customers.  Consequently, the models are highly dependent on consistent long-term data.  In essence, the more, the better.  LMH has generally found that it is difficult to construct reliable models for companies that have fewer than 100,000 customers and less than four years of consistent transactions history.

For a hypothetical example of how LMH Data Modelling works see the Example Tab

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