Reply performance

Reply performance answers a different question than the rest of Analytics: not what reviews say, but how well they’re being answered. It’s reached from Analytics as Performance, and splits into two tabs — AI Agents and Humans — that read the same underlying reply data from two different angles. Every number on this page is read per app and folded together, so a multi-app scope reports a true combined total rather than one app’s numbers standing in for the rest.

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AI Agents tab

This tab opens with a summary strip of four numbers:

• Automation score — the share of your app-sent replies that were automated
• Auto replies — replies posted in the window
• Pending approval — replies queued now
• Reply impact — the rating effect of automated replies

Below the strip, three bands go from coarse to fine detail:

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Coverage

A time-series chart tracks daily reply coverage: how many reviews arrived, and how many got an answer. Next to it, a reply coverage donut shows the same split (answered vs. unanswered) for the window. The time series can be viewed aggregated by day or rolled up weekly, which smooths day-to-day noise on a longer window. For a window of 28 days or more, the chart opens on weekly. Your own Daily or Weekly choice sticks until you pick a window with a different default. The chart’s legend lists the ten busiest rules, then a +N more rules toggle (Show fewer collapses it again). The cap never hides the Manually replied and Unreplied keys.

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Effect on ratings

A table shows what a review’s rating did after it was answered, split by AI/Automation, Human, and Combined reply source. Each row shows replies published, how many reviews moved rating, the average rating change, and a win rate (the share of moved reviews that went up). A second card breaks every reply down by outcome — whether the rating rose, fell, or stayed the same — as a share of that source’s replies. Immovable 5★ reviews (5★ before and after) are counted here but can’t meaningfully move a rating.

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Repliers: by rule, by quality, and by speed

An Automation-by-rule table lists every automation rule that sent replies in the window, so you can see which specific rules are actually moving ratings, not just which are running most often: Below the table, two scatter charts plot every rule (and your hand-written replies, shown hollow) against the same rating-change axis:

• Quality against effect — each replier placed by how often its replies pass your reply-quality scorecard (left to right) against the rating change that followed (bottom to top). Dot size scales with replies sent; a dashed line marks the account’s own overall pass rate.
• Speed against effect: the same layout, placed by mean time to reply instead of pass rate. A dashed line marks the account’s own average reply time, drawn only once every replier’s time is known. Its legend is capped at ten rules with the same +N more rules toggle.

A replier needs enough graded or timed replies before it gets a plotted rate; repliers that don’t clear that bar are counted in the chart’s key instead, with the reason available on hover.

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Humans tab

The Humans tab (labeled “Humans” next to “AI Agents”) swaps the automation-rule view for a per-person one: who on your team is replying, how fast, and what happens to ratings afterward. It opens with a Replies over time chart (one line per teammate, opening on weekly for windows of 28 days or more) next to the same reply-coverage donut used on the AI tab, then an Agent leaderboard table with, per person: An agent selector in the filter bar (visible only on this tab) lets you narrow the chart and leaderboard to specific teammates.