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Swan has two separate analytics surfaces: usage analytics, which tracks what Swan is doing and what it costs, and outreach analytics, which tracks how your sequences are performing.

Usage analytics

Usage analytics, at Settings → Usage, shows credits consumed and the number of runs, over a date range, broken down several ways:
  • By trigger — which automations are consuming the most credits and runs.
  • By user — how much a person’s conversations (and any triggers scoped to them) are consuming.
  • By tool and by toolkit — which individual tools or toolkit categories are driving credit usage. On v2 (data and intelligence credits), this view shows data credits only. Intelligence credits have no tool, so they appear in the run, trigger, and user totals but not here. The by-tool numbers therefore add up to less than the total.
It separates trigger-driven runs from conversation runs, so you can see whether your credit spend is coming from automations or from people chatting with Swan directly. See credits for what consumes credits and credit costs for per-action pricing.

The v2 usage page

Orgs on v2 (data and intelligence credits) get a different usage page, built around the billing period:
  • Period picker. Monthly plans open on the current billing cycle and can switch to any earlier cycle since the first payment, or to a custom range of whole days. Yearly plans and orgs without a renewal date open on the last 30 days.
  • Credit pool and forecast. The page shows the plan’s credit pool and what is left of it. While you are looking at the running billing cycle, it projects whether the credits last until the renewal date at the current pace.
  • Daily spend split into automations and conversations, next to the prior period of the same length.
  • Who is spending. One row per automation and per teammate, with the split into intelligence credits (Swan’s reasoning and writing), data credits (lookups with a per-result price) and signal fees (triggers that bring in data), how it compares with the prior period, and a typical (median) and high (95th percentile) cost per run or conversation.
  • Data lookups with result counts and prices, and the costliest runs in the period.
A run’s sub-agents count toward the run that delegated to them, so an automation that fans out to many sub-agents shows as one automation with one cost.

Outreach analytics

Outreach → Analytics shows how your sequences are performing over a date range:
  • A funnel KPI row — accounts reached, people reached, people replied, and reply rate, each with a change indicator versus the previous period of the same length.
  • Per-channel scorecards — a LinkedIn card (people contacted, connections accepted of requests sent, replies of people messaged) and an email card (people emailed, opens, replies), with rates shown as progress toward 100%.
  • A daily engagement chart combining cohort outcomes and send volume, and a performance matrix you can switch between By Campaign and By Sender (inbox).
The Inboxes and Campaigns filters are multi-select, so you can look at any combination of sending accounts and Campaigns at once.

How the outreach date filter works

Performance metrics start from outreach contacted during the selected period: sequence contacts whose first message or LinkedIn connection request was sent in that window. Creating a sequence alone does not put it in the report. When filtering by an inbox, the report attributes messages, replies, and tracking events to that inbox’s channel. Replies, email opens, link clicks, and connection acceptances accrue after the relevant outreach through the moment you view the report. They can count after the selected period ended. For example, if Swan first emailed a contact July 10 and they replied July 25, that reply can appear in the July 1–14 report, regardless of when their sequence was created. Recent results therefore mature over time as later engagement arrives. A reply rate for last week means “outcomes so far,” not a final result. Send volume is the exception. The Emails sent and LinkedIn messages sent KPIs, plus the send bars in the daily chart, count messages actually sent during the selected period. This includes follow-ups from sequence contacts created earlier. Send totals answer “how much did we send this period?” and intentionally may not add up against cohort metrics. The dashboard uses these counting rules: A person can have more than one sequence-contact row. People metrics count that person once within each inbox/trigger group, while the same person can appear in multiple groups. A mixed-channel sequence can contribute to both its email inbox’s group and its LinkedIn inbox’s group once each has contacted the person. In the daily engagement chart, people and their replies are grouped by the outreach date, and connection activity by the invitation date. Later replies and acceptances contribute back to those dates. Send bars use the date each message was actually sent. Links open the matching Campaign’s Enrolled tab and carry the selected date range and inbox filters. The Campaign page filters by sequence-contact creation date, while analytics uses outreach dates and distinct people, so the resulting row count can differ from the clicked metric. Analytics expands the selected dates to whole UTC days. Because each rate’s numerator and denominator come from the same cohort and counting unit, reply, open, click, and acceptance rates cannot exceed 100%.

Known quirks

  • Email open data starts April 17, 2026. Open tracking began collecting on that date, so a date range starting earlier undercounts opens — the page shows a caveat badge when that applies.
  • Today is often grayed out in the date picker. If the current day isn’t selectable, it’s almost always a timezone or caching quirk rather than a restriction — try again after the day rolls over in your timezone, or pick yesterday as the end date instead.

What analytics doesn’t do

Swan’s analytics don’t currently include industry benchmarks (there’s no comparison to typical open, click, or reply rates for your industry) or a bulk data-export API for pulling raw analytics or execution data programmatically. For a custom dashboard, ask Swan to build an app on your live data. If you need that data outside Swan, sync it through your CRM integration — that’s the supported export path. See HubSpot or Salesforce. If you want a recurring digest instead of checking the dashboard yourself, you can set up a schedule trigger that runs on a cadence and posts a summary to a Slack channel. See schedule triggers.

Common questions

Does reply rate count multiple replies from the same person? No. The top-level reply KPI and rate count a person once, so one person replying several times is still one reply. The inbox × trigger table also counts distinct people within each inbox/trigger group; a person can appear in more than one group. Can open rates exceed 100%? No. The numerator and denominator use the same eligible contacts and counting unit, so the rate is capped at 100%. One person opening several times still counts as one open. (Older versions of this dashboard counted raw open events, which could push rates above 100% — that’s no longer how it works.) Why did last week’s outreach results change? Recent cohorts mature. Replies, opens, clicks, and accepted connections continue to count as they arrive, even after the selected date range ends, so recent results are outcomes so far rather than final totals. Why don’t the send totals add up to the people or engagement totals? They measure different things. Send KPIs and bars count messages sent during the selected period, including follow-ups from older sequences. People and engagement metrics count distinct contacts with qualifying outreach in the period and include their outcomes to date. Does the date filter match the Campaign page? No. Analytics uses outreach dates; the Campaign page uses the sequence contact’s creation date. Links carry the selected range across, but the two views can contain different populations and counts. Why don’t the credits shown here match my invoice exactly? Because they measure different things. This dashboard shows credits consumed by your runs over a rolling time window, drawn from Swan’s internal usage records. Your invoice is a flat subscription charge — plan fee plus seats, plus any one-off credit top-ups — billed on Stripe’s cycle, not a tally of credits used. Credit consumption is a quota against your allotment, not a metered line on the invoice, so the two won’t line up. Timing differences (Swan’s rolling window vs Stripe’s billing period, and credit refunds) can widen the gap. Can I export a chart or table from the analytics page? There’s no built-in export for analytics charts today; the reliable way to get the underlying data out is through your CRM sync. Can I filter outreach analytics by a specific inbox or trigger? Yes — both filters are multi-select, so you can narrow the view to any combination of inboxes and automations. Filtering by an inbox counts only what that inbox did: a sequence that emails from one inbox and messages on LinkedIn from another shows only its email activity when filtered by the email inbox. Do usage analytics only cover triggers, or chat conversations too? Both — it separates credits and runs from triggers versus from conversations, so you can see either in isolation or combined.