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Your customer success dashboard, tied back to the queue.

Ticket volume, resolution time, CSAT, NPS, and first response time in one view, reconciled from your support tools and CRM, so the performance you report ties back to the queue.

See how to build one in Definite
What’s in a customer success dashboard?

What’s in a customer success dashboard?

A customer success dashboard is the single governed view of how well a support organization resolves issues: ticket volume, resolution rate and time, first response time, and the satisfaction scores that follow. The version worth managing a team on reconciles the queue, the conversations, and the satisfaction surveys into one view, so the performance you report is the performance that happened.

Support metrics get reported from each tool separately. Zendesk shows one resolution time, Intercom shows another, and CSAT lives in a third report. When ticket volume, resolution, and CSAT come from one set of definitions modeled on the actual support systems, you manage the team on real numbers, and you catch the resolution time spike before it becomes a CSAT problem.

Who it’s forVP CS, support leads, and heads of customer experience who own the queue and the satisfaction number.

CadenceRefreshed daily; reviewed in the weekly support standup and before quarterly reviews.

Built fromZendesk, Intercom, Hubspot, Amplitude

§ How it works

Describe your dashboard. Fi builds it.

Fi is the AI agent inside Definite. Tell it what you’re trying to understand, and it connects your sources, defines the metrics, and builds the dashboard. One conversation, not a project.

You
I need to see how support is performing: ticket volume, resolution time, CSAT, and first response time, tied back to the queue, not a separate report for each tool.
✦ Fi
Here's your customer success dashboard, on your Zendesk, Intercom, Hubspot and Amplitude data.
Here’s what’s in it

The top row leads with the 4 numbers that matter most: Ticket volume, CSAT, Avg resolution time, First response time. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (Ticket volume over time, CSAT trend) show how the headline numbers have moved over time. A breakdown (Tickets by channel) splits the metric by dimension so you can see what's driving the total. A detail table (Support health) rounds it out with the secondary metrics and their deltas. Every number is computed from the exact formulas shown in the metric table below. Composites are derived from their components, not pasted in, so the KPI tiles, breakdowns, and totals all reconcile to each other.

Illustrative data

Ticket volume

2.5K▼ 8.1%
Data ▾
PeriodTicket Volume
Jan1.8K
Feb1.7K
Mar1.8K
Apr2.0K
May2.6K
Jun2.5K
Jul2.9K
Aug2.6K
Sep2.8K
Oct2.3K
Nov2.8K
Dec2.5K

CSAT

9717.3%▼ 0.7%
Data ▾
PeriodCSAT
Jan8255.5%
Feb8616.4%
Mar9207.0%
Apr9383.5%
May8982.1%
Jun9568.6%
Jul9066.7%
Aug9481.4%
Sep9427.5%
Oct9589.5%
Nov9782.4%
Dec9717.3%

Avg resolution time

7▲ 14.8%
Data ▾
PeriodAvg Resolution Time
Jan9
Feb7
Mar7
Apr8
May9
Jun7
Jul7
Aug8
Sep6
Oct8
Nov6
Dec7

First response time

1▲ 42.5%
Data ▾
PeriodFirst Response Time
Jan2
Feb2
Mar1
Apr1
May2
Jun1
Jul2
Aug1
Sep1
Oct1
Nov1
Dec1

Ticket volume over time

1,600 1,800 2,000 2,200 2,400 2,600 2,800 3,000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodTicket Volume
Jan1.8K
Feb1.7K
Mar1.8K
Apr2.0K
May2.6K
Jun2.5K
Jul2.9K
Aug2.6K
Sep2.8K
Oct2.3K
Nov2.8K
Dec2.5K

Tickets by channel

Paid Search Paid Social Organic Email Referral 0 100 200 300 400 500 600 700
Data ▾
ChannelTicket Volume
Paid Search259
Paid Social689
Organic419
Email652
Referral527

CSAT trend

81 84 87 90 93 96 99 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodCSAT
Jan8255.5%
Feb8616.4%
Mar9207.0%
Apr9383.5%
May8982.1%
Jun9568.6%
Jul9066.7%
Aug9481.4%
Sep9427.5%
Oct9589.5%
Nov9782.4%
Dec9717.3%

Support health

Resolution Rate120.3%▲ 36.2%
Avg Resolution Time7▲ 14.8%
NPS54▲ 11.6%
✦ Fi
Anything else I can do for you?
You
Why did first response time spike last week?Which accounts have the most open tickets, and are any of them up for renewal this quarter?Which channel has the worst resolution time, and is it the same one with the lowest CSAT?Show me the tickets behind the CSAT dip in March.What is our resolution rate if I exclude tickets reopened within 24 hours?Break ticket volume out by segment instead of channel.Alert me in Slack when CSAT drops below 80% for any account segment.Trace this month's CSAT back to the satisfaction ratings in Zendesk.Break ticket volume by channel and flag any channel where first response time is over two hours.Add resolution rate by segment so I can see if enterprise accounts are being handled differently.Show CSAT trend alongside resolution time to see if faster resolution is improving satisfaction.
  • Why did first response time spike last week?
  • Which accounts have the most open tickets, and are any of them up for renewal this quarter?
  • Which channel has the worst resolution time, and is it the same one with the lowest CSAT?
  • Show me the tickets behind the CSAT dip in March.
  • What is our resolution rate if I exclude tickets reopened within 24 hours?
  • Break ticket volume out by segment instead of channel.
  • Alert me in Slack when CSAT drops below 80% for any account segment.
  • Trace this month's CSAT back to the satisfaction ratings in Zendesk.
  • Break ticket volume by channel and flag any channel where first response time is over two hours.
  • Add resolution rate by segment so I can see if enterprise accounts are being handled differently.
  • Show CSAT trend alongside resolution time to see if faster resolution is improving satisfaction.
First version in a dayFree to start, flat pricingNo infrastructure to set up
§ Why the numbers tie out

Every metric traces back to your systems

This is the part a BI tool can’t fake. Each metric is defined once, in your warehouse, from a specific object in a specific source. Change the definition in one place and every tile, report, and answer moves with it. So the number on the screen is the number in the source.

Zendesk
◆ TicketTicket VolumeAvg Resolution TimeFirst Response TimeResolution Rate
◆ Satisfaction RatingCSAT
Hubspot
◆ TicketTicket VolumeAvg Resolution TimeFirst Response TimeResolution Rate
Intercom
◆ ConversationTicket VolumeFirst Response TimeResolution Rate
MetricWhat it measuresHow it's calculatedSources
Resolution Rate—Tickets Resolved ÷ Ticket VolumeZendesk, Hubspot, Intercom
§ Then do something about it

Have our agent watch for you

A customer success dashboard tells you what happened, and Fi tells you why. The last step is not having to remember to check. Point Definite at the one number you can’t afford to miss, and it watches that number for you off the same definitions as your dashboard. When it moves, you hear about it before the next review instead of during it. One metric, one action, always reversible.

Autonomous agent · watch churn
Watch
A metric you choose
net revenue churn
→
Judge
One condition
> 5% week-over-week
→
Act
One action
alert #revenue + open doc
◄──── then waits · cooldown 24h before it can act again ────
Scoped to a single metric and a single action. You arm it; you can disarm it anytime.
§ The data that powers it

Built from whatever you already run on

Connect the systems you already use. Any source of these types works, and you don’t move data into a warehouse, because Definite is the warehouse.

No warehouse to stand up or connect. See how the platform models your data →

§ Get started

Build your customer success dashboard

From signup to a working dashboard in one sitting. No data team required.

01

Sign up

Free to start. No credit card, no infrastructure to set up.

Create your account →
02

Connect your sources

Stripe, your CRM, accounting. Definite syncs and models them automatically.

03

Decide your metrics

Pick the numbers that matter or let Fi propose them from your data. Every metric gets one definition, governed in one place.

04

Ask Fi to build it

Describe what you need in plain language. Fi builds the dashboard, and you refine by asking follow-ups.

§ FAQ

Common questions

Usually because Zendesk counts a resolved ticket on the status-change date, Intercom counts conversation closure on a different event, and the CSAT survey response might lag both. The reconciliation map above shows which object each metric comes from, so there is one definition of resolution time and CSAT, modeled in your warehouse.
Your support platform (Zendesk, Intercom) for tickets, resolution times, and satisfaction ratings, and your CRM (HubSpot) for account context and segments. Optionally, product analytics (Amplitude) for engagement signals that correlate with support load. Definite syncs and models all of them.
Industry benchmarks vary, but SaaS companies typically target 85%+ CSAT. What matters more than the benchmark is the trend, the variance by channel, and whether resolution time improvements are translating into higher satisfaction. This dashboard shows all three.
It is a live ECharts dashboard running on a deterministic synthetic dataset, labeled illustrative. Resolution rate is computed as tickets resolved over ticket volume by the formula in the metric table. Connect your support tools and Fi builds the same view from your data.
Type a prompt like the one above. Fi connects your Zendesk, Intercom, and CRM, models the support metrics, and you refine by asking follow-ups. The first version ties performance back to the queue without a spreadsheet.

Your answer engine
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