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Storm Attribution

The Storm Platform implements tailored attribution models that automatically attributes sales and actions for more than £3Bn in sales across 10Bn touch points every month.

Over the past 7 years we have developed the Storm Platform to support 2 different approaches to attribution; rules based models and more advanced statistically derived models.

The Storm Platform is configured for each client following an Attribution Modelling project which defines how to configure the software and set weightings and coefficients. Refinements and additional learnings are applied to the model on an on-going basis.

Attribution Rules Framework

The Storm Platform has a comprehensive rules framework for defining how a sale should be shared across the path to conversion.

Storm can set weightings on the key metrics:

  • Brand or non-brand – Visits that reflect that the user knows the brand name of the website can be treated differently from those that don’t.
  • Marketing Channel – Weightings can be changed based on the marketing channel that brought the visit.
  • Keyword Grouping – For visits from paid and natural search, the weightings can be based on groups of keywords that can be defined using free text matching.
  • Position in the path to conversion – Once a set of visits has been identified; weightings can be set for visits based on the position of visits in the path to conversion.

Bespoke Statistical Model

The Storm Platform supports the deployment of completely tailored statistically derived attribution models. The models are developed by DC Storm's Analysis and Insight team in an approach that has been developed by Rakuten Attribution over the past 5 years. Our consultants analyse the converting and non-converting journeys to understand the propensity to purchase for all touch points, by analysing which touchpoints actually increase the conversion rate we derive a coefficients matrix which is then integrated within the Storm Platform to drive real-time sales attribution.

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