> For the complete documentation index, see [llms.txt](https://help.zaapi.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.zaapi.com/analytics/support-dashboard.md). # Support dashboard **Volume, response, and resolution health across all your conversations.** This is your day-to-day overview page: how much came in, how fast you replied, how much got resolved, and how that splits across channels. Everything here is calculated for the **date period you select** and respects the filters at the top — so the numbers always reflect the slice you're looking at. If you haven't already, read How we calculate analytics first; it explains the period model, time zones, and the rules every metric on this page follows. *** ### Filters and how to read the cards Three controls sit at the top of the page: * **Date period** — e.g. *Last 7 days · May 6 – May 12, 2026*. Sets the window every metric is calculated for. * **Channel** — e.g. *All channels (4)*. Narrows to one or more channel types (Facebook, Instagram, WhatsApp, Email). * **Agent** — e.g. *All agents*. Scopes metrics to specific agent(s). Each headline card shows three things: the **value** for the period, a **trend line** (the in-period movement, day by day), and a **comparison to the previous period** of equal length (the 7 days before your 7 days). For volume metrics, the comparison shows the percentage change. For time metrics, it's shown as **"faster"** or **"slower"** — an increase in response or resolution time is *slower*, and is flagged in red because higher is worse. *** ### How human and AI replies are counted on this page Zaapi is AI-first, so several metrics deliberately separate work the AI Agent handled from work your human team handled. The model across this page: | Metric | Basis | | --------------------------------------------- | ---------------------------------------------------------- | | Avg First Response Time, Avg Response Time | **AI Agent /** **Human agent** replies | | One Touch Tickets | **Human agent** replies only | | Zero Touch Tickets | **AI Agent / automation** resolutions, with no human reply | | Avg Resolution Time, Created / Closed Tickets | **All** tickets, however they were resolved | So a ticket the AI fully resolves with no human involved counts as **Closed**, has a **Resolution Time**, and lands in **Zero Touch** — but it has **no First Response Time** (there was no human reply to measure). *** ### Volume Four headline counts for the period. #### Created Tickets The number of tickets created during the period. Counts when the ticket was **created.** #### Closed Tickets The number of tickets closed during the period and still closed at period end. Counts when the ticket was **closed**. Closed can be **higher** than Created in the same period (in the example, 1,015 closed vs 895 created) — that's normal when your team is working down a backlog carried in from earlier. The two aren't meant to tie out. #### Messages Sent The total number of messages sent **to customers** during the period, excluding internal notes. Counts each message by its **sent** time (so this is a message count, not a ticket count). #### Messages Received The total number of inbound messages **from customers** during the period. Counts each message by its **received** time. *** ### Customers #### Customer Messages by Time of Day A heatmap of **when customers reach out**, with day of week across the top and three-hour blocks down the side. Each cell is the number of inbound customer messages that you received in that day-and-time slot, shaded darker as volume rises. Times use your **workspace time zone**. Use it for staffing — it shows your real demand curve across the week so you can put coverage where the messages actually are. #### New vs Returning Customer Tickets A split of the period's tickets by whether the customer is **new** (their first-ever message to you happened during this period) or **returning** (they messaged you before this period). The donut shows the total with the new/returning breakdown and each side's share. #### Unique Customer Interactions Per Day The number of **unique customers** (Contacts) who messaged you per day during the period based on "opened at". A customer who opened five tickets within one day counts once. *** ### Response & Resolution Three averages describing speed. All three are **medians** (not averages) and measure **elapsed clock time**, including nights and weekends — see the calculations page. #### Median First Response Time (FRT) The median time from a customer's first message to the **first human or AI agent reply**, across tickets that got their first reply during the period. Automated acknowledgements (except AI) don't count here. #### Median Response Time The median time a customer waits for a reply across **every** response in the period — not just the first. Where FRT measures the opening reply, this measures ongoing responsiveness throughout the conversation. This includes human, AI, automated or native channel responses. #### Median Resolution Time The median time from a customer's first message to the ticket's **final closure**, across tickets closed during the period. This includes AI-resolved tickets. As on the calculations page: reopened tickets use the final closure time is included (it doesn't shorten resolution time). *** ### Resolution Effort How much resolution happened with little or no human touch — the core efficiency story for an AI-first inbox. #### Zero Touch Tickets Tickets **resolved by the AI Agent or automation with no human reply at all**, shown as a count and as a share of resolved tickets. This is your automation/deflection metric: the higher it is, the more your team is freed from routine work. #### One Touch Tickets Tickets **resolved with exactly one human agent** reply, shown as a count and share. One efficient human reply, done. Internal notes don't count toward the "one." *** ### Performance by Channel A **per-channel breakdown** repeating every metric above, sliced by channel type, and it **respects the current filters**. The bottom **Total** row matches the headline cards. | Column | Metric (defined above) | | ----------------- | ------------------------------ | | Created | Created Tickets | | Closed | Closed Tickets | | Msg Sent | Messages Sent | | Msg Recv | Messages Received | | Median FRT | Median First Response Time | | Median Resp | Median Response Time | | Median Resolution | Median Resolution Time | | Zero Touch | Zero Touch Tickets (count + %) | | One Touch | One Touch Tickets (count + %) | Two things worth knowing when you read it: * The time columns (Median FRT, Median Resp, Median Resolution) are **medians, so they don't add up**. The Total row is the blended median across all integrations, not the sum of the rows above it. *** ### Good to know * **Why don't these numbers match the Live page?** Support reports on a date range and includes closed tickets; Live is a real-time snapshot of only open tickets. Different questions, different numbers. * **Why is Closed higher than Created?** You're clearing older backlog — see Closed Tickets above. * **Do AI replies count?** See *How human and AI replies are counted* above — FRT, Response Time, and One Touch are human-only; Zero Touch is the AI/automation view; Resolution Time and the volume counts include everything.