Growth
AI Marketing Analytics for HubSpot
Answers marketing performance questions across your analytics and ad platforms, connected natively to HubSpot so it reads marketing emails, campaigns, forms, contacts…
Growth
AI Attribution Assistant
Every closed deal gets traced back to the marketing touches that actually contributed, weighted by the role each one played.
Last-click reports give all the credit to the final ad someone saw, so channels that start the conversation look worthless. This build traces each closed deal back through the touches that led to it, weights them by rules you set, and explains which channels really contribute to pipeline and revenue. It reads your CRM, analytics and ad data with read-only access.
- Each closed deal traced back through the touches that led there
- Credit weighted by rules your team defines
- Alerts when a channel's contribution shifts
$4,500
20–30 working days
Optional maintenance $249/mo
What it is
AI Attribution Assistant explains which channels and touchpoints actually contributed to pipeline and revenue, tracing each closed deal back through the touches that led to it rather than crediting the last click alone. It checks its model against three months of your own history before launch. Credit rules are yours, agreed at intake.
Why businesses buy it
Budget follows credit. When attribution only counts the last click, teams cut the channels that create demand and overfund the ones that simply close it, and growth stalls without an obvious reason. This build gives you a clear, explainable view of how every channel contributes, checked against three months of your own history before launch, so the numbers hold up in a budget meeting. The scope sets out the data sources, credit rules and reporting schedule before you order, so the model is never a black box.
Problems this solves
Last-click reports hand all the credit to one channel
Each closed deal is traced back through the touches that led to it, not just the last click. You see which channels and touchpoints actually contributed to pipeline and revenue.
Budget meetings stall on arguments about which channel deserves credit
Credit rules are agreed with you at intake and applied the same way every time. The argument happens once, then the reports carry on from there.
Attribution models feel like a black box nobody can check
Before launch, the model is checked against three months of your own history. Your team can compare its output with deals they remember and query anything that looks wrong.
A good fit if
You run marketing across several channels and can't say with confidence which ones actually move deals forward.
Your team currently credits the last click or the last touch, and you suspect that's hiding what's really working.
You have at least three months of closed-deal and touchpoint history to model against.
You want a weighting model built around how your own funnel actually behaves, not a generic default.
Not the right fit if
You mainly need answers on channel spend and totals, not a model of what caused each conversion. See AI Marketing Analytics, the step before this one.
You want the findings turned directly into running experiments on your pages or funnel. See AI CRO Agent, which designs and runs those tests.
Your main question is about one landing page's conversion rate, not cross-channel credit. See AI Landing Page Optimization, which is built for that.
You need more than three connected data sources or attribution across more than one language. Add a note at checkout for a Change Quote, or use our Custom AI enquiry form.
How it works
- Touchpoints are collected across your funnel. Ad clicks, email opens, organic visits and form fills from up to three connected sources such as GA4, HubSpot or Meta Ads.
- Conversions are matched back to the path that led there. Every closed deal or completed order is traced to the sequence of touches that came before it, not just the last click.
- A weighting model splits the credit. Using the rules you define during intake, so a channel that opens deals and one that closes them are credited differently, matching how your team already thinks about the funnel.
- The model is checked against three months of your own history. Before launch, so the credit it assigns lines up with deals you already know the story behind.
- A recurring report shows where budget is actually working. Delivered to email, Slack or a dashboard, with up to five alerts for channels whose contribution shifts sharply.
- You can question any number. Ask why a channel's credit changed and it explains the touches behind that answer, not just the total.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- Read-only access to each data source that should feed the model.
- Your own definitions of the key metrics and what counts as a conversion.
- At least three months of closed-deal and touchpoint history to model against.
- The report recipients and the channel they should receive the findings on.
- Admin access and API keys for every connected system, shared by adding our team as a user or creating a key you control, never by email.
- Your business information (company basics, hours and brand voice), shared during intake.
- One decision-maker who can approve the weighting rules.
- An API key for your own AI model account (for example OpenAI or Google Gemini), created for this build with a spending limit.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake verified, data sources and conversion definitions agreed.
Weeks 1–2
Touchpoint data connected and the attribution model built.
Week 3
Weighting rules applied and alerts configured.
Weeks 3–4
Model checked against three months of your historical deals.
Week 4
Your review and two rounds of changes.
Go-live
Live, recorded handoff session, 30 days of support starts.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $4,500 |
| Express | 15–25 working days | $5,300 |
| Rush | 10–20 working days | $6,100 |
What you receive at handover
- AI Attribution Assistant running with read-only access to up to three agreed data sources
- Your agreed credit rules, configured as workflow, prompt and guardrail settings
- A recurring report or dashboard with up to five alerts, delivered to email, Slack or a web dashboard
- A test report showing the model checked against three months of your historical data
- An admin guide and recorded handoff session
- 30 days of post-launch support
Expected benefits and how to measure them
- Can give a fairer picture of which channels feed revenue
- Helps budget conversations move faster
- Makes the reasoning behind attribution visible
- Revenue by contributing channel
- Compare the attribution report with your previous last-click view for the same quarter.
- Budget reallocated with evidence
- Log budget shifts made using the report and review their results the following quarter.
- Time spent on attribution debates
- Note meeting time spent on channel credit before launch and after.
Before you start: Save your current channel report and record how budget is split today, along with the reasons given.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build price is one-time. Running it costs roughly $20 to $150 a month in your own accounts, covering AI model usage and the hosting or scheduler that keeps the model current.
AI usage during the build and testing is billed the same way, in your own accounts, so every provider relationship stays yours.
Ask about running costsCustom requirements
If you need a fourth data source, multi-currency deals, or attribution modeled in more than one language, add a note at checkout for a written Change Quote. Larger or bespoke projects go through the Custom AI request form instead.
Request a custom versionKeep it running
After launch, monthly maintenance keeps the build current as your business changes. It covers monitoring, fixes and monthly change hours for changes such as a revised weighting rule or a new metric. It starts after the post-launch support period, bills monthly and can be cancelled any month. Unused hours do not roll over.
$249/mo (the minimum fee, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | An attribution tool charges a monthly fee tied to tracked revenue | An analytics agency quotes a project retainer | Ours is one fixed price, shown on this page before you buy |
| Scope | An attribution tool applies one default model to everyone | An agency agrees scope during the project | Ours is written on the Scope Card, weighted to your funnel |
| Delivery | An attribution tool needs weeks of tracking data before results | An agency usually takes several weeks, set per project | Ours has a fixed delivery time shown before you buy, with faster options |
| Model basis | An attribution tool ships a fixed algorithm | An agency build depends on what was agreed | Ours is checked against three months of your own deals |
Questions about this product
Does AI Attribution Assistant replace last-click reporting entirely?
No, it sits alongside it. The model shows how credit splits across every touchpoint in a deal's path, while your existing platforms can still report last-click for comparison. Most teams use the two together during the first few months, until they trust the weighted view enough to lead on it.
What does AI Attribution Assistant cost to run each month?
Roughly $20 to $150 a month in your own accounts, covering AI model usage and the hosting or scheduler behind the model. You pay that directly to the provider. Monthly maintenance is optional. We charge nothing extra per deal modeled.
How fast can AI Attribution Assistant go live?
Delivery follows the fixed timeline shown in the delivery panel, counted from a verified intake. Express and rush options are available for a fee. The clock starts once your data access, conversion definitions and historical deals are confirmed, so a complete intake is what keeps the build on schedule.
How does it decide how much credit each channel gets?
It applies the weighting rules you set during intake to the full touchpoint path behind every closed deal, so a channel that opens deals and one that closes them are credited differently. Before launch, that model is checked against three months of your own deals to confirm it lines up.
Can it connect to my CRM as well as my ad platforms?
Yes, within the three connected data sources included, such as HubSpot for deal data alongside GA4 and an ad platform like Meta or LinkedIn. All connections are read-only, so nothing in your CRM or ad accounts gets changed by the model.
Can I change the weighting rules later?
Yes. Adjusting how credit splits between channels, or adding a new metric to track, fits inside the monthly change hours that come with maintenance. A fourth data source or a rebuilt model for a different business unit is scoped separately as a Change Quote.
What if the model's numbers don't match what my team expects?
You get two rounds of changes built into the build price, using the three months of historical deals it was checked against. After delivery you have five working days to flag anything that doesn't match the Scope Card, and that gets corrected as part of the original price.
Who owns the attribution model once it's built?
You do. The weighting rules, the report and the underlying logic belong to your business, running in your own connected accounts. There is no license fee for using the model after launch, only optional monthly maintenance if you want ongoing changes made for you.
Know which channels actually earn their budget.
Order AI Attribution Assistant and see which channels really earn their budget. Data sources and credit rules are agreed in writing before you pay.
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