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A Scorecard (Evaluations → Scorecards in the left dashboard nav, visible with the Manage Agents permission) is a reusable scoring policy for real call recordings you upload — a named bundle of metrics from the shared Metrics library, each with a weight, plus a minimum passing score per side of the conversation. Upload a batch of recordings, and every call in the batch gets graded against the scorecard the same way, so “did this call pass?” means the same thing across a hundred recordings and across months of audits. This is the one part of Evaluations that faces backward instead of forward. Evaluators and Runs grade simulated conversations before you ship a change; a Scorecard grades calls that already happened — a QA sample of last month’s collections calls, recordings exported from a legacy dialer before you migrate, or any call made outside Revve entirely. If what you want is automatic grading of every live call one agent completes, that’s the per-agent Voice Agent Evaluation tab, not a scorecard.

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Where Scorecards fits

Four things in Revve grade conversations, and they all draw metrics from the same library: Because a scorecard is just a policy over shared metrics, editing a metric’s definition in the library changes how every scorecard that uses it grades — the scorecard only owns the metric’s weight within its policy.

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The Scorecards page

The page (“Reusable scoring policies for evaluating uploaded call recordings”) lists your team’s scorecards in a table: Before you’ve created any, the empty state reads “No scorecards yet — Create your first scorecard to start scoring uploaded recordings.” The Scorecards page in its empty state, with the No scorecards yet message and the New scorecard button

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Creating and editing a scorecard

Click New scorecard (top right) to open a sheet from the right — “Pick metrics and weights to score completed call recordings.” Clicking an existing row opens the same sheet as Edit scorecard. The policy editor is the same weighted-metrics editor as the Voice Agent Evaluation tab: pick metrics from the shared Metrics library, give each a weight, and set a minimum passing score (1–5) per tab. It has separate Caller and Agent tabs, each with its own minimum pass score — so a scorecard can hold the agent side to a strict compliance bar while scoring the caller side leniently (or not at all). If you already know that editor from an agent’s Evaluation tab, there’s nothing new to learn here; the scoring mechanics are documented in Voice Agent Evaluation. Submit with Create scorecard (new) or Save changes (editing).
Weight by what a failure costs you, not by how easy the metric is to check. In a compliance scorecard, “read the required disclosure” should be able to sink the score on its own — give it a dominant weight — while style metrics like tone share the remainder. A flat equal-weights policy lets three polite pleasantries outvote one missed disclosure.

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Upload Batches

Once you’ve uploaded at least one batch of recordings, an Upload Batches section appears below the scorecards table — “Batches of uploaded call recordings queued for scoring” Scoring is asynchronous: a batch queues, processes each file, and reports progress here.
The Scorecards page defines the policy and tracks batch progress — that’s all. Uploading the recordings themselves, and reviewing each scored call afterward, both happen on the Call History side. Clicking a batch name here is the shortcut across: it lands you in Call History pre-filtered to that batch.
A partial or failed status means some files never got scored — check the Failed count before treating the batch’s results as a complete sample, especially for a compliance audit where the unscored calls are exactly the ones you can’t vouch for.

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When to reach for a scorecard

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What’s Next

  • Evaluation Metrics — build the deterministic and LLM-judged metrics your scorecards attach.
  • Voice Agent Evaluation — the same weighted-metrics editor, applied automatically to every live call one agent completes.