What the RFE playbook covers
RFE answers one question: which accounts should be worked this week. It keeps Recency and Frequency from RFM, drops Monetary because a net-new B2B account has no purchase history underneath it, and splits Engagement into Channel, where the account came from, and Activity, what it actually did. The playbook is the model itself rather than a summary of it: the Channel and Activity scoring tables, the caps that hold the total at 100, the routing bands that turn a score into an owner and an SLA, and the steps to deploy it in HubSpot or Salesforce.
The reasoning behind the model, and the funnel arithmetic that makes selection matter more than sending capacity, is set out in what 200 SQLs a month requires.
What it deliberately leaves out
Firmographic fit is not one of the dimensions. Fit does not change week to week, so weighting it in lets a perfect-fit account that has done nothing for months collect a respectable score simply by existing. RFE assumes fit has already been applied as a binary gate before scoring starts. Building that gate is a separate job, and the ICP that builds your account list is where we set it out.
Who it suits
Demand gen and RevOps owners who already have a target account list and need a defensible way to rank it: the people who get asked why a given account sits at the top of the queue and want a better answer than a vendor's black box. It is a chassis you retune against your own conversion data, and like everything else in the Omnitics resource library, it is free and it is yours to keep.
If you would rather have the model built and tuned inside your own stack, that is the scoring engine underneath our account-based marketing service.