Describe your queues, your answer target and your scorecard, and Netiva builds a web app where service level by interval, agent handle time and QA reviews sit together — with code you own.
Build a call center dashboard for a 30-seat inbound service center with three queues: Service, Billing and Retention. Team leads enter each half-hour interval — calls offered, answered, answered within 20 seconds, abandoned and agents staffed — plus one row per agent per day with scheduled, logged-in, talk, hold and wrap minutes and calls handled. Show today’s service level against the target by queue, rank the intervals that missed it and give every agent a page with handle time, occupancy and their QA reviews. Agents sign in to read their own scores and acknowledge coaching notes.
Contact center managers spend the first hour of the day rebuilding yesterday: one export of queue intervals, another of agent statistics and a QA workbook nobody has opened since Friday. By the time the numbers agree, the huddle is over. A call center dashboard built with Netiva keeps interval rows, agent shifts and QA reviews in one web app, so service level against target, abandon rate, handle time and coaching all read from the same records — and every agent can sign in to see their own.
Every interval row carries calls offered, answered, answered within your target and abandoned, so the day reads as a line against the target instead of one daily average that hides the 11 a.m. queue.
One row per agent per day gives handle time, occupancy and calls handled without a pivot table, and each agent gets a page that pulls their shifts and reviews together for the one-to-one.
Reviews are records rather than a workbook: a weighted score, an auto-fail flag for a missed verification and the coaching note the agent signs in to read and acknowledge.
Figures arrive the way your setup allows — typed into the grid by a team lead, or pulled from your phone platform’s REST API with the key stored securely — and go back out as a morning email.
Netiva keeps your records in built-in collections. Here’s a starting structure — the agent adapts it to your prompt, and you can change it any time.
Who takes calls, which team they sit in and which queues they are trained for.
One row per queue per half hour — the raw material behind every service-level figure.
One row per agent per day: the minutes behind handle time, occupancy and adherence.
One scored call per row, with the coaching that came out of it.
Required field. Types are Netiva collection field types.
A typical first version. Ask the agent for more, or annotate the preview to change any of them.
Every queue’s half-hour blocks for the day so far: answered in target against the line you set, abandons and the agents staffed in each block.
Your teamOne queue over recent weeks — daily service level, abandon rate, the busiest half hours and the days that missed target, with the rows behind each figure.
Your teamWhere a team lead types yesterday’s interval and shift rows, or checks the rows that arrived from the phone platform overnight.
Your teamOne agent’s shifts, handle time, occupancy and QA history with the latest coaching note on top — the page a team lead opens for a one-to-one.
Your teamWhat a signed-in agent sees: their own shifts, handle time trend and QA reviews, with a button to acknowledge the latest coaching note.
Signed-in usersThe scorecard itself — section scores, the auto-fail flag, the call reference and the coaching note, held in draft until it is shared with the agent.
Your teamTell Netiva your queue names, the answer target in seconds, the share you expect to hit and what your scorecard measures. It drafts collections for agents, queue intervals, shifts and QA reviews while you watch.
Type a week of intervals and shift rows into the grid, or ask the collection assistant to draft and tidy them, then check whether the service level and handle time match the figures you already trust.
Invite a team lead into the workspace, annotate the daily view where a column is missing or an average reads wrong, and keep chatting until the screens match how your huddle runs.
Publish in one click, give leads and agents their sign-ins and switch on the morning email. Every later change is checkpointed, so a mid-week edit is easy to roll back.
| Criterion | With Netiva | Traditional build |
|---|---|---|
| The morning report | Interval rows sit in one collection and the day’s service level updates as they arrive | Three exports from the phone system stitched into a workbook before the huddle |
| QA and coaching | Each review sits on the agent’s page with a coaching note the agent signs in to read | Scores in a shared spreadsheet and coaching notes buried in email threads |
| Getting started | Describe what you need in chat and watch it take shape in a live preview | Hire developers, or stitch together templates, plugins and a hosting plan |
| Content and data | Built-in collections with nine field types, bound straight to your pages | Set up and connect a separate database or CMS |
| Making changes | Ask the agent; every change is checkpointed and reversible | File a ticket, wait for a sprint, redeploy |
| Hosting and domain | Global hosting and automatic SSL; connect a custom domain from the Starter plan | Buy hosting, then install and renew SSL certificates yourself |
| Code ownership | Clean production code you own and can export | Locked into a template, plugin or agency setup |
One manager covers service, billing and retention queues with three team leads. Each lead enters their queue’s intervals before lunch, and the Monday review compares the week’s answered-in-target share with the target set for each queue.
A small provider runs a queue for each client, each with its own answer target. Queue names carry the client, so one client’s service level, abandon rate and QA sample can be pulled for the monthly review without unpicking a shared report.
A retailer triples its team for the holiday peak. Temporary agents get shift rows and a first QA review in week one, and the coverage view shows a lead which of 40 new agents has been scored and which has not.
Individual figures invite comparisons that one bad day can distort. Agree which numbers are coaching signals and which are targets, show how many calls sit behind each average, and read QA scores next to volume rather than on their own.
Netiva does not connect to your ACD by itself. Interval and shift figures are typed into the grid or pulled from your platform’s REST API if it has one, so treat the screens as a daily and weekly picture, not a live wallboard.
Keep the call reference in the review, not the audio or the caller’s details. Federal law allows recording when one party consents, while several states require everyone on the call to agree — check yours before you tie reviews to recordings.
If your team dials out, the FTC’s Telemarketing Sales Rule caps abandoned calls at 3% of calls answered by a person, measured per campaign or 30-day period. The dashboard records what your dialer reports; the dialer settings keep you inside the rule.
Call statistics and QA scores name individual agents, so they are personal data about your staff. Tell agents which figures the dashboard keeps, who can read them and how they are used in reviews, and give each agent a sign-in so they can see their own record. Keep pay, absence and HR case notes in your HR system, set how long interval rows and reviews are kept, and check the rules on monitoring staff where you operate before you publish.
Each interval row holds calls offered, calls answered and the number answered inside the target — 20 seconds, say. The daily figure divides answered-in-target by calls offered for the queues and opening hours you choose, and the chart draws your target line beside it. If you discount short abandons under five seconds, describe that rule when you ask for the calculation and the app follows it.
Netiva apps can call any REST API with keys stored securely, so if your cloud phone platform publishes one, you can describe the call and the fields you want and have yesterday’s intervals land in the collection each morning. Check what your platform’s API exposes first. Without an API, a team lead types the rows into the grid, which takes a few minutes a day.
Average handle time adds talk, hold and wrap minutes on the shift rows and divides by calls handled, so a rise in after-call work shows up on its own. Occupancy compares that handling time with logged-in minutes. Both depend on how agents use their states: if breaks are taken while logged in, occupancy reads lower, so agree the definition before you compare teams.
Yes. Agents sign in with their own account and land on a page filtered to their records: shifts, handle time, QA reviews and the coaching note from the last one-to-one, which they can mark as read. Team leads keep the queue and team views. Tell your agents what the dashboard measures and who can see it before you switch their sign-ins on.
No. Netiva builds the dashboard, not a forecasting engine. You can ask for staffing math on your own history — an Erlang C style estimate of the agents needed per half hour from volume and handle time, which assumes callers wait rather than hang up — but rosters, shift bidding and interval-by-interval adherence stay in your WFM tool.
The collections stay as they are; only the way the numbers arrive changes. Point the daily pull at the new platform’s API, or keep typing rows until it is wired up. The code is yours either way: Netiva writes clean production code you can read, edit and export whenever you want, and every change is checkpointed, so a rewrite you dislike rolls back.
Drafted with AI assistance from Netiva’s product pages and reviewed by the Netiva team. Example data models, screens and prompts are illustrative starting points, not customer projects.
Describe it in a sentence and watch Netiva’s agent build it. Free to start — no credit card required.