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Campaigning Wiki

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Summary

Campaign math is the quantitative discipline of modeling a campaign’s target — win number, vote deficit, persuasion/turnout/registration sub-totals, lead-generation funnel, donation-rate targets, per-day operating cadence — in numbers that can be tracked against actuals week-to-week. It is the operating-budget conversation grounded in evidence-grade field-experiment effect sizes.

Body

Campaign math sits at the intersection of behavioral-science effect sizes (Green & Gerber’s Get Out The Vote; the Analyst Institute’s RCT library) and operational planning (the number of doors, calls, texts, or donor conversations per week required to hit the campaign’s targets). Without numbers, a campaign plan is a wish; with numbers, it is a trackable operating system. [source: get-out-the-vote]

re:power’s campaign-math toolkit operationalises the discipline with three canonical worksheets. The Win Number worksheet calculates how many voting-eligible supporters the campaign needs to convert (by persuasion, turnout, registration) to reach the goal, plus the per-day operating rate that requires. The Vote Deficit calculation breaks the same target into sub-totals by intervention (persuasion doors, GOTV calls, registration drives) and tests whether the campaign’s budget and volunteer capacity can hit the sub-totals. The SCOPE matrix (Support, Constituency, Organisation, Politics, Execution) gives a multi-dimensional snapshot of where the campaign actually is, to ground after-action review. [source: repower]

The Caltech/MIT Voting Technology Project’s vote-deficit modeling adds the ballot-design dimension to campaign math: the number of votes a jurisdiction loses to over-voting, under-voting, or design-driven confusion. A campaign cannot math its way around a ballot design that disenfranchises 3 percent of the electorate; civic-design interventions (ballot redesign, voter-education campaigns) are usually part of the campaign-math answer [source: caltech-mit-voting-tech].

Campaign math connects to microtargeting as the tool-side: a voter file is not useful until the campaign has translated effect-size evidence (which tactic works best by demographic) into a microtargeting model that scores each voter on the relevant propensity, and then into a targeting plan that allocates volunteer-hours to the marginal-comparable buckets. The two disciplines share a data infrastructure.

Use it for

Building the campaign-budget model (dollars-to-doors, dollars-to-calls, dollars-to-texts) at the start of a campaign; running a mid-campaign re-targeting exercise with new polling or voting data; deciding which voter-contact methods to fund given the relative effect sizes; producing the budget-defensibility document a funder or board needs to see.

Open Questions

  • The re-targeting cadence question: how often should a campaign re-run its campaign-math calculations in-cycle (weekly, monthly, only at key milestones) and what data inputs justify a re-run?
  • The persistence question: does a campaign-math-driven operation develop durable field capacity that survives between cycles, or does the infrastructure collapse back to zero after each election?

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