Overview
Overview
The new Agent Performance Console moves measurement from a single reply to the whole conversation, because that's where the real answer lives: did the guest actually get what they came for. Every campaign your agents run now points at one clear goal, so instead of guessing whether things are working, you see exactly how each one is resolving tasks and how that stacks up against your peers.
Access the Console
There are multiple ways to access the Agent Performance Console:
Access the Console directly here: agent2.satis.fi
From the Launchpad, click here:

From the Content Studio, click on the following sign:

Why the measure changed
Early chat products answered questions, so we measured replies. The Quality Response Index (QRI) counted messages received, replies sent, and how relevant and complete those replies were. Each message was scored on its own.
Agents should be resolving tasks, which are only identifiable if you analyze the entire conversation. The conversation is a better unit of analysis because the task exists across turns; the messages are individual steps used to complete it.
A message-level evaluation asks: "Was this response good?" A conversation-level evaluation asks the more important question: "Did the agent successfully accomplish what the user was trying to do?"
A guest asks about parking, then gate openings, then bag policy, and only the full exchange reveals the one thing they were trying to do: get into the building on time. The task is identifiable only at the conversation level, therefore the console scores conversations, not messages.
The standard: resolution
Every conversation is evaluated against what the guest came to do. Each one receives a single verdict.
Resolved
The guest got what they came for, at the level they needed, within what the agent is built to handle.
Partial
The need was within the agent's remit and the agent moved the guest specifically toward it, but stopped short of the completeness or specificity the guest wanted.
Unresolved
The need went unmet: a generic runaround, conflicting information, or no usable path, or the request is something the agent cannot or will not do.
Campaigns
An Agent Campaign is a structured, AI-driven mission assigned to a single agent. It aligns that agent's behavior with a strategic business outcome, and it is defined by what the guest is trying to accomplish rather than by topic.
Each campaign is anchored by a task completion statement: the plain definition of what a finished task looks like. Every conversation in the campaign is measured against that same bar.
Example. The Guest Experience agent's "Plan the Visit" campaign covers guests preparing for game day. It succeeds when their entry, policy, seating, and wayfinding questions are resolved with the right information.
Objectives and Key Results
OKRs organize what an agent should achieve and how it is measured.
Objective
The qualitative business outcome.
Key Result
One campaign. Scored 0 to 1.
Objective Score
Average of its Key Result scores.
The Key Result Score
The score is produced in two steps. First, measure the campaign's task completion rate. Second, score that rate against the goal for the campaign.
0.7 is success. It marks performance on par with a strong campaign running the same job under the same conditions. The task completion rate required to earn a 0.7 is not the same across campaigns: a hard campaign such as ticket sales reaches 0.7 at a lower rate than an easier one.

Setting goals
Every campaign has a goal. We set it using historical results across clients running that same campaign, adjusted for task difficulty. Task completion rate is the primary input.
FAQ
General Questions
Data
Evals
Resolutions
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