Connect Google Ads, HubSpot, and Stripe.
Credit payments or leads with a model you can name. A missing source stays missing.
Nothing hidden as zero. Nothing claimed without proof.
MetaNot connected yet
Google AdsAd spend
HubSpotLeads
StripePaymentsAdvertising, customers, and orders in a shared view. Keep the source and period attached to every result.
Read platform claims alongside your model. See the differences without combining overlapping totals.
Spend comes from the connected account. weive credit is the model’s split, and a missing source is not zero.
Turn the evidence into a useful explanation. Bring assumptions and gaps into the conversation.
Example figures. In the product, credit uses the model you select, and a missing source stays missing.
Advertising. Customer records. Revenue.
Google Ads, HubSpot, and Stripe connectMetaGoogle AdsHubSpotStripeMonday’s budget review. Two platforms claim the same sale. A source is missing. Before the next decision, bring the evidence into the room.
Illustrative evidence view
Platform reports can tell different stories. Compare the same period and keep each attribution perspective distinct.
Inspect the source and matching rule. Separate what was observed from what was calculated or estimated.
A missing source becomes an action to investigate. A model becomes a method to review. The discussion has a shared basis.
A platform claim, a record match, and a model estimate answer different questions. Keep the distinction visible before making the decision.
Platform reportedClaimMeta’s attribution perspective
Source matchedDerivedOrder values matched under a stated rule
A separate modeled perspective
Platform reports use their own attribution rules and windows. Two platforms can claim the same order.
A matched result has a source and a rule. Trace it to the records, and read it within its coverage.
A model can offer another perspective. Its assumptions stay explicit, and its result stays separate from observed records.
Follow an attribution result back to the records and rule behind it. Keep the reasoning available, not buried.
Read every result alongside its coverage. A missing source stays visible so it cannot quietly change the story.
Explore how evidence changes the story.
Every value needs context. Every gap deserves to be seen.
$25,000 is the spend present in the connected advertising records for this example. It does not include the unconnected source.
A chart should help explain a result. The period, source, and gaps stay in the picture.
Matched revenue is derived. Known spend excludes the unavailable source. Modeled revenue is kept separate.
| Through date | Matched revenue | Known spend |
|---|---|---|
| 04 September | $6,000 | $3,000 |
| 08 September | $11,000 | $7,000 |
| 12 September | $19,000 | $10,000 |
| 16 September | $26,000 | $14,000 |
| 20 September | $35,000 | $17,000 |
| 25 September | $41,000 | $21,000 |
| 30 September | $48,000 | $25,000 |
Meta$12,000Google Ads$13,000$25,000 of known spend. A missing source remains a gap, not a zero.
Generative AI should make the evidence easier to understand. Sources, calculations, and uncertainty belong in the answer.
The connected records show $48,000 in source-matched revenue and $25,000 in known ad spend. Their ratio is 1.92×, within that scope. An additional spend source is unavailable, so this is not a complete return comparison.
Record matching does not establish causation. Modeled revenue is excluded.
Example conversation. In the product, answers use connected accounts and the model.
Turn a result into a clear explanation, with the source and calculation still within reach.
Surface missing records and incomplete periods before they become a confident conclusion.
Shape the evidence into a useful draft for your next budget review. Keep human judgment in the loop.
An empty field shouldn’t look like a measured result.
Missing sources, incomplete periods, and unavailable values stay visible. A true zero means a valid result within a defined scope.
A confident statement needs an inspectable basis.
Keep source records, calculations, and assumptions distinct. Let the evidence set the strength of the conclusion.
A shared understanding of the data makes the next decision clearer.
Start with where a record came from and which period it covers. Keep the original context attached.
Matched resultDerivedOrder records + matching rule
Show how records become a result. Separate observations from calculations and estimates.
Read the result alongside its coverage. Decide with an understanding of what the evidence supports.
For the conversations behind the numbers.Understand what a campaign result can support before moving the budget.
Make your reasoning inspectable. Explain the source, method, and limits.
See the difference between a measured result, an estimate, and a gap.
Illustrative case studies explore the questions evidence can help answer. These examples do not describe actual customer outcomes.
Case studyA campaign looks stronger in one report than another. Start with the records, matching rule, and period.
Case studyAn unconnected source changes the scope of the report. Explain the gap before presenting the conclusion.
This space is reserved for approved, attributable customer feedback. No customer testimonial is published yet.
Awaiting approved customer storiesIt means reading an attribution result with its basis attached: the source records, the period, the method, and the coverage. A calculated or modeled result should be identified as such.
A zero says something was measured or validly calculated and the result was zero. Missing data says the result is unknown. Treating them as the same can change the decision.
Yes, when they are visibly labeled and their assumptions and uncertainty are available. An estimate should not appear as an observed fact or be silently combined with measured revenue.
Matching records under an attribution method does not, by itself, establish causation. The conclusion should reflect the method and evidence used.
No. The interactive view uses an illustrative dataset to explain evidence states. It demonstrates the design approach, not a live account connection or customer performance.
A shared evidence layer for the way you work. Explore the AI coding ecosystem, from the terminal to the editor.
Aider
GooseEcosystem preview. Tool logos identify their respective products; weive connections are not demonstrated in this preview.
A clearerProposed product controls