Via my friends at VisualIQ, this wonderful post from Avinash Kaushik on doing multi-channel attribution and mix optimization in the real world. Plus a really rich set of conversations in the comments. My summary of his advice (reassuringly consistent with my own experiences with "pragmalytic" approaches):
- Start by solving for specific attribution / optimization use cases you face in the real world, not the more general form of the challenge. He names three dominant ones he sees: "O2S -- Online to Store", "AMS -- Across Multiple Screens", and "ADC -- Across Digital Channels"
- Use multiple analytic techniques to compensate for imperfect data that any one technique might rely on. For example, if there are holes or quality problems with your data, supplement it with controlled tests
- Don't cop out, but accept that there are no perfect answers, just better ones, and that you should bias toward acting on acceptably imperfect information and learning and improving based on actual experience
Absolutely terrific stuff here, gets even better on the third and subsequent reads.
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