Thursday, May 24, 2018

15 - Analytics 101 for the Marketeer- Modeling :The Balancing Act

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I will digress a bit here to reiterate the Pooling aspect of the framework specifically the data model –I do see that as a “LPHV” ( Lowly Prioritized High Value) Item. There are three fundamental modes of managing data and processes between in house CRMs and external marketing platforms unless of course, you are Amazon and have your internal campaign management & marketing platforms. The data model is pivotal to every integration, Plug and Play solution to deploy to enhance your marketing automation.
  1. Segmentation intelligence on an external tool and ESP functioning as a Plain Jane cross channel “blasting engine” .
  2. ESP hosting transactional and aggregated information for segmentation and personalization.
  3. A hybrid mode incorporating a bit of Options 1 and 2.
 The decision around these options are critical and will certainly influence campaign performance, scalability and a marketeer’s capability to bolt on analytical solutions on to the platform like Send Time Optimization (STO), Behavioral Clustering, Market Basket Analysis ( MBA) and so on. Well, all the arrows in the quiver may in reality be “un-deployable” if a sub optimal approach is chosen, leaving a stunted data mart in place.Here are some of the information elements that a typical first degree database typically holds.



Managing a fully functional Marketing database is a challenge primarily due to the usage patterns that it needs to cater to.    Some of the Use cases a cross channel marketing database needs to exhibit are.
  • Online Transaction Processing - for opt-in Management , preferences and Transactional Messaging.
  • Data WareHouse
    • Extract, Load and manage millions of demographic, transactional and behavioral data
    • Manage and Effectively Utilize Event Data for segmentation and reporting.
    • Merge and Query Massive data sets for Effective Targeting.
  • Reporting -Campaign Stats & Trends
 The four sources of information need to rationalized from a data design perspective in order to expedite the Campaign Build Process and there is generally a contextual trade off between normalization and using wide columns views. There is a plethora of areas available to tweak and rationalize the structures that can provide high returns. Some areas that that can directly benefit the campaign build process are listed below.

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