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.
Here’s what’s in it
The top row leads with the 4 numbers that matter most: Attributed revenue, ROAS, Cost per conversion, Conversions. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (Attributed revenue over time, Ad spend by channel) show how the headline numbers have moved over time. A breakdown (ROAS by channel) splits the metric by dimension so you can see what's driving the total. A detail table (Cost efficiency & funnel) 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.
Attributed revenue
Data ▾
| Period | Attributed Revenue |
|---|---|
| Jan | $463K |
| Feb | $395K |
| Mar | $549K |
| Apr | $503K |
| May | $453K |
| Jun | $605K |
| Jul | $655K |
| Aug | $812K |
| Sep | $697K |
| Oct | $766K |
| Nov | $725K |
| Dec | $958K |
ROAS
Data ▾
| Period | ROAS |
|---|---|
| Jan | 3.1× |
| Feb | 2.1× |
| Mar | 3.1× |
| Apr | 2.4× |
| May | 2.2× |
| Jun | 3.0× |
| Jul | 3.7× |
| Aug | 4.1× |
| Sep | 3.2× |
| Oct | 3.4× |
| Nov | 2.7× |
| Dec | 3.1× |
Cost per conversion
Data ▾
| Period | Cost per Conversion |
|---|---|
| Jan | $58 |
| Feb | $59 |
| Mar | $58 |
| Apr | $50 |
| May | $55 |
| Jun | $44 |
| Jul | $46 |
| Aug | $42 |
| Sep | $41 |
| Oct | $38 |
| Nov | $46 |
| Dec | $70 |
Conversions
Data ▾
| Period | Conversions |
|---|---|
| Jan | 2.6K |
| Feb | 3.1K |
| Mar | 3.1K |
| Apr | 4.3K |
| May | 3.7K |
| Jun | 4.6K |
| Jul | 3.9K |
| Aug | 4.7K |
| Sep | 5.4K |
| Oct | 6.0K |
| Nov | 5.9K |
| Dec | 4.5K |
Attributed revenue over time
Data ▾
| Period | Attributed Revenue |
|---|---|
| Jan | $463K |
| Feb | $395K |
| Mar | $549K |
| Apr | $503K |
| May | $453K |
| Jun | $605K |
| Jul | $655K |
| Aug | $812K |
| Sep | $697K |
| Oct | $766K |
| Nov | $725K |
| Dec | $958K |
ROAS by channel
Data ▾
| Channel | ROAS |
|---|---|
| Paid Search | 0.0× |
| Paid Social | 0.0× |
| Organic | 1.0× |
| 1.0× | |
| Referral | 1.0× |
Ad spend by channel
Data ▾
| Period | Ad Spend |
|---|---|
| Jan | $151K |
| Feb | $184K |
| Mar | $179K |
| Apr | $214K |
| May | $204K |
| Jun | $203K |
| Jul | $179K |
| Aug | $197K |
| Sep | $217K |
| Oct | $227K |
| Nov | $273K |
| Dec | $314K |
Cost efficiency & funnel
- Which Google Ads campaign's ROAS dropped last month, and what changed?
- Show me the ad groups behind the spike in cost per conversion on search.
- Are our branded keywords cannibalizing organic, or are they incremental?
- Trace this month's attributed revenue back to the search terms that generated it.
- What would ROAS look like if I paused the bottom three campaigns by cost per conversion?
- Break conversions out by ad group and keyword instead of campaign.
- Break ROAS by campaign and ad group inside Google Ads, not just the channel total.
- Show me which keywords are driving conversions that actually close in Salesforce.
- Add a cost per conversion trend by campaign type over the last six months.
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.
| Metric | What it measures | How it's calculated | Sources |
|---|---|---|---|
| ROAS | Revenue attributed back to ad spend per dollar spent, the headline efficiency number for paid. | Attributed Revenue ÷ Ad Spend | Google Ads |
| Cost per Conversion | What you pay, on average, for a single conversion, the unit cost of demand. | Ad Spend ÷ Conversions | Google Ads |
| CPC | What you pay, on average, for a single click. | Ad Spend ÷ Clicks | Google Ads |
| MQL → SQL Rate | The share of marketing-qualified leads that sales accepts as qualified, the handoff health check between the two teams. | SQLs ÷ MQLs | Salesforce |
Have our agent watch for you
A google ads marketing attribution 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.
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 →
Build your google ads marketing attribution dashboard
From signup to a working dashboard in one sitting. No data team required.
Connect your sources
Stripe, your CRM, accounting. Definite syncs and models them automatically.
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.
Ask Fi to build it
Describe what you need in plain language. Fi builds the dashboard, and you refine by asking follow-ups.