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Your unit economics dashboard, modeled from your stack.

CAC, LTV, LTV:CAC ratio, ARPA, and gross margin in one view, modeled from billing, your CRM, and ad spend, so the economics you present are grounded in the stack, not a spreadsheet.

See how to build one in Definite
What’s in a unit economics dashboard?

What’s in a unit economics dashboard?

A unit economics dashboard is the single governed view of what it costs to acquire a customer and what that customer is worth: customer acquisition cost, lifetime value, the LTV:CAC ratio that determines payback, average revenue per account, and gross margin. The version worth planning on is modeled from billing, the CRM, and ad spend, so each input is a governed definition, not a spreadsheet cell.

Unit economics gets re-derived in a spreadsheet every quarter, pulling from billing for revenue, marketing for spend, and the CRM for customer counts, each on a different date with a different denominator. When CAC, LTV, and margin all come from one set of definitions modeled on the actual systems, the economics are the economics, and you catch the shift in payback before it compounds.

Who it’s forCFOs, founders, and finance leads who own the customer economics and the board narrative around payback.

CadenceRefreshed daily; reviewed before board prep and quarterly planning.

Built fromStripe, Hubspot, Google Ads

§ 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 our unit economics: CAC, LTV, the ratio, ARPA, and margin, modeled from our billing and spend data, not a spreadsheet.
✦ Fi
Here's your unit economics dashboard, on your Stripe, Hubspot and Google Ads data.
Here’s what’s in it

The top row leads with the 4 numbers that matter most: LTV : CAC, CAC, LTV, ARPA. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (LTV:CAC over time, ARPA trend) show how the headline numbers have moved over time. A breakdown (CAC by channel) splits the metric by dimension so you can see what's driving the total. A detail table (Economics summary) 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

LTV : CAC

11.4×▼ 24.4%
Data ▾
PeriodLTV : CAC
Jan7.0×
Feb11.7×
Mar8.5×
Apr8.1×
May9.1×
Jun11.1×
Jul8.0×
Aug13.1×
Sep8.6×
Oct8.7×
Nov15.1×
Dec11.4×

CAC

$3K▲ 20.3%
Data ▾
PeriodCAC
Jan$3K
Feb$2K
Mar$2K
Apr$2K
May$2K
Jun$2K
Jul$3K
Aug$2K
Sep$3K
Oct$3K
Nov$2K
Dec$3K

LTV

$29K▼ 9.1%
Data ▾
PeriodLTV
Jan$21K
Feb$24K
Mar$19K
Apr$19K
May$19K
Jun$24K
Jul$21K
Aug$29K
Sep$25K
Oct$23K
Nov$32K
Dec$29K

ARPA

$531▲ 3.8%
Data ▾
PeriodARPA
Jan$443
Feb$438
Mar$442
Apr$449
May$456
Jun$459
Jul$469
Aug$478
Sep$492
Oct$504
Nov$511
Dec$531

LTV:CAC over time

6 8 10 12 14 16 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodLTV : CAC
Jan7.0×
Feb11.7×
Mar8.5×
Apr8.1×
May9.1×
Jun11.1×
Jul8.0×
Aug13.1×
Sep8.6×
Oct8.7×
Nov15.1×
Dec11.4×

CAC by channel

Paid Search Paid Social Organic Email Referral 0 100 200 300 400 500 600 700
Data ▾
ChannelCAC
Paid Search$372
Paid Social$398
Organic$612
Email$546
Referral$614

ARPA trend

420 440 460 480 500 520 540 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodARPA
Jan$443
Feb$438
Mar$442
Apr$449
May$456
Jun$459
Jul$469
Aug$478
Sep$492
Oct$504
Nov$511
Dec$531

Economics summary

CAC$3K▲ 20.3%
LTV$29K▼ 9.1%
Gross Margin78.2%▲ 0.6%
✦ Fi
Anything else I can do for you?
You
Why did CAC spike last quarter?Which segment has the best LTV:CAC, and which is underwater?Show me how ARPA has trended as we have added new pricing tiers.How has LTV moved as gross margin has changed over the past year?Break CAC out by channel instead of the blended number.Trace this quarter's CAC back to the spend in Google Ads and the new customers in HubSpot.Break CAC out by channel so I can see which acquisition path is cheapest.Show LTV by segment and flag any segment where LTV:CAC is under 3x.Add payback period in months next to the LTV:CAC ratio.
  • Why did CAC spike last quarter?
  • Which segment has the best LTV:CAC, and which is underwater?
  • Show me how ARPA has trended as we have added new pricing tiers.
  • How has LTV moved as gross margin has changed over the past year?
  • Break CAC out by channel instead of the blended number.
  • Trace this quarter's CAC back to the spend in Google Ads and the new customers in HubSpot.
  • Break CAC out by channel so I can see which acquisition path is cheapest.
  • Show LTV by segment and flag any segment where LTV:CAC is under 3x.
  • Add payback period in months next to the LTV:CAC ratio.
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.

Stripe
◆ SubscriptionLTV : CACLTVARPA
◆ CustomerLTV : CACCACLTVARPA
◆ Balance Transaction (Ledger)LTV : CACLTVGross Margin
◆ InvoiceLTV : CACLTVGross Margin
◆ PaymentLTV : CACLTVGross Margin
Google Ads
◆ AccountLTV : CACCACLTVARPA
◆ CampaignLTV : CACCAC
MetricWhat it measuresHow it's calculatedSources
LTV : CACThe payback test on growth spend. Lifetime value divided by acquisition cost.LTV ÷ CACStripe, Google Ads
CACWhat it costs in sales and marketing to win one new customer.S&M Spend ÷ New CustomersGoogle Ads, Stripe
LTVThe gross-margin revenue an average customer is worth over their lifetime, before you spend to acquire the next one.(ARPA × Gross Margin) ÷ Logo ChurnStripe, Google Ads
ARPAAverage recurring revenue per account, MRR spread across the customer base.MRR ÷ CustomersStripe, Google Ads
Gross MarginThe share of net revenue left after the direct cost of delivering the product, the ceiling on how efficiently the business can grow.(Net Revenue − COGS) ÷ Net RevenueStripe
§ Then do something about it

Have our agent watch for you

A unit economics 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 unit economics 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 CAC uses a different spend total than the ad platforms report, LTV uses a different churn rate than billing shows, and ARPA uses a different customer count than the CRM. The reconciliation map above shows which object each metric comes from, so each input is a governed definition, not a spreadsheet cell that drifts.
Billing (Stripe) for revenue per account and margin, your CRM (HubSpot) for customer counts and segments, and your ad platforms (Google Ads) for acquisition spend. Definite models all three into one set of economics.
CAC is sales and marketing spend divided by new customers acquired. LTV is ARPA times gross margin divided by logo churn rate. When every input comes from a governed definition, the ratio between them is a real number, not a formula built on estimates.
It is a live ECharts dashboard running on a deterministic synthetic dataset, labeled illustrative. LTV:CAC is computed from CAC, ARPA, margin, and churn by the formulas in the metric table, not pasted in. Connect your sources and Fi builds the same view from your data.
Type a prompt like the one above. Fi connects your billing, CRM, and ad platforms, models the unit economics, and you refine by asking follow-ups. The first version is board-ready without a spreadsheet.

Your answer engine
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Book a 30-minute call and watch us build your first dashboard live, with your own data.