AI marketing attribution
across every channel
Terno AI computes blended CAC and multi-touch attribution across Google Ads, Meta Ads, LinkedIn Ads, and your CRM, joined in a single conversation, so channel ROI reflects the whole customer journey, not one platform's siloed view.
Every attribution model, computed on demand
Ask for first-touch, last-touch, or multi-touch, and get the answer under that model, not a single fixed view.
First-touch
Credits the channel that introduced a prospect to your brand. Useful for measuring top-of-funnel discovery and awareness spend.
Last-touch
Credits the final channel before conversion. Simple, but it overweights bottom-funnel channels like branded search and retargeting.
Multi-touch
Distributes credit across every touchpoint in the journey, weighted by position or influence, for a more honest view of what drove the deal.
No single model is universally correct. First-touch is useful for justifying awareness budget, last-touch is simple and common for day-to-day optimization, and multi-touch gives the fairest picture for budget planning decisions. Most mature marketing teams look at more than one model side by side rather than picking a single one permanently, which is exactly why Terno AI computes each on demand instead of locking in one fixed methodology.
Attribution & Channel ROI
What is AI-powered marketing attribution?
Ask which channels actually drive revenue the way you'd ask a growth lead, and get a computed answer instead of reconciling five platforms in a spreadsheet.
Beyond platform-reported conversions
Every ad platform only counts what it can see. Attribution needs the whole journey.
Models, compared directly
See how much the answer changes between first-touch, last-touch, and multi-touch.
Computed, not guessed
Every ratio and dollar figure comes from a real query joining your platforms and CRM.
Every ad platform reports its own conversions, and every one of them looks good in isolation. Google Ads takes credit for the click, Meta takes credit for another, and LinkedIn takes credit for a third, and if you add up what each platform claims, the total is often larger than your actual number of customers. That double counting is the core problem attribution is meant to solve, and it requires seeing all the channels and the CRM outcome together, which no single platform's dashboard can do on its own.
AI-powered marketing attribution means asking that cross-channel question directly instead of exporting each platform's data into a spreadsheet and reconciling it by hand. Terno AI connects to Google Ads, Meta Ads, LinkedIn Ads, and your CRM or warehouse, and computes blended CAC, LTV to CAC, and channel-level ROI under whichever attribution model you ask for.
This is also where the choice of attribution window matters more than most teams account for. A window built for a short consumer sales cycle badly understates upper-funnel channels when applied to a six-month enterprise deal, because most of the influence happened well outside that window. Terno AI can compute attribution under a window that actually matches your sales cycle, rather than whatever a single ad platform defaults to.
There's a security dimension worth naming too. Cross-channel attribution means combining spend figures from every ad platform with revenue data from your CRM, which is exactly the kind of sensitive, cross-system data that shouldn't end up in a general-purpose AI tool with no access control. Terno AI computes the same answer without that exposure, since the query runs inside your own environment and only controlled metadata reaches the underlying LLM.
These are the recurring questions a growth or finance lead asks every budget cycle, and normally each one means pulling exports from three or four platforms and reconciling them by hand in a spreadsheet, a process that can take days and is stale by the time it's done. AI marketing attribution removes that step, so the question and the answer happen in the same conversation.
It also changes the tenor of budget conversations. A recommendation backed by a spreadsheet reconciled once a quarter tends to be treated as a static fact by the time it reaches leadership. A number that can be recomputed live, in the meeting, under a different model or a different date range, tends to earn a different kind of trust, because it can be interrogated on the spot rather than taken on faith.
What growth teams can do with Terno AI
The cross-channel questions finance and growth leaders ask most, answered in seconds instead of a reconciliation project.
Blended CAC, computed correctly
Combine spend across Google Ads, Meta Ads, and LinkedIn Ads with pipeline from your CRM to compute true blended customer acquisition cost.
Compare attribution models side by side
Ask the same question under first-touch, last-touch, and multi-touch models to see how much the answer actually changes.
Budget reallocation, backed by data
See which channels are over-credited by last-touch reporting alone, and where budget would be better spent.
Full-funnel, not platform-siloed
Every ad platform only reports its own conversions. Terno AI joins them with your CRM so you see the whole customer journey, not one slice of it.
Ask in plain language
"What's our blended CAC by channel this quarter under a multi-touch model?" Terno AI computes it, with no spreadsheet to build.
Read-only and secure
Terno AI reads reporting data through each platform's official API with read-only scopes, and deploys inside your own cloud.
Terno AI vs. single-platform dashboards vs. generic AI chatbots vs. manual reconciliation
Four ways to answer a cross-channel attribution question. Here's how they compare.
| Capability | Terno AI | Platform Dashboard | Generic AI Chatbot | Manual Reconciliation |
|---|---|---|---|---|
| Answers a brand-new attribution question in plain English | ✓ | – | ✓ | ✓ |
| Answer is computed from a real query, not generated text | ✓ | ✓ | – | ✓ |
| Joins every ad platform with your CRM in a single query | ✓ | – | – | – |
| Supports first-touch, last-touch, and multi-touch on demand | ✓ | – | – | – |
| Marketing and revenue data never leaves your network | ✓ | ✓ | – | ✓ |
| Available the same day, every day | ✓ | – | ✓ | – |
Best practices for marketing attribution
Habits that keep attribution numbers trustworthy enough to actually reallocate budget against.
Ask under more than one attribution model before deciding
A channel that looks weak under last-touch can look strong under first-touch or multi-touch. Checking a budget decision against more than one model avoids overreacting to a single, incomplete view.
Reconcile platform-reported conversions against CRM outcomes monthly
Every ad platform inflates its own contribution to some degree, since each only sees its own touchpoints. A monthly reconciliation against actual closed revenue keeps blended CAC honest.
Separate new customer CAC from expansion or renewal CAC
Blending acquisition spend for new logos with retention or expansion spend for existing accounts produces a CAC number that doesn't map cleanly to either decision.
Revisit attribution windows when sales cycles are long
A 30-day attribution window makes sense for a short sales cycle and badly understates upper-funnel channels for a six-month enterprise cycle. Matching the window to the actual cycle length keeps the model honest.
Track channel combinations, not just individual channels
Deals often involve more than one channel before closing. Looking only at individual channel performance misses which combinations of touchpoints actually correlate with your highest-value deals.
Revisit the model itself periodically, not just the numbers
As channel mix and buyer behavior shift, the attribution model that made sense a year ago may no longer fit. A periodic review of which model to use is as important as the ongoing reporting itself.
Include organic and SEO-driven channels in the same picture
Attribution conversations often focus only on paid channels, which overstates paid's share of the credit. Including organic and referral touchpoints gives a fairer, fuller view of what's actually driving conversions.
How it works
Three steps, and no separate modeling project to commission before you get an answer.
Connect every channel
Authorize Terno AI with Google Ads, Meta Ads, LinkedIn Ads, and your CRM or warehouse. Each connection is read-only and revocable.
Ask an attribution question
Ask for blended CAC, channel ROI, or a specific attribution model in plain language, with no modeling project to commission first.
Reallocate with confidence
Get a computed answer across every connected channel, so budget shifts are backed by the full customer journey, not one platform's view of it.
Read-only and secure, across every channel
Terno AI connects to each ad platform through its official API with read-only reporting scopes, and deploys fully inside your own cloud or on-prem environment. Spend and revenue data never leaves your network, and only controlled metadata is shared with the underlying LLM. The same deterministic security layer governs every connected source, so cross-channel attribution doesn't mean a looser security standard than any single platform on its own.
Explore connected platforms
Frequently Asked Questions
What is AI-powered marketing attribution? +
AI-powered marketing attribution lets you ask questions about channel ROI, blended CAC, and multi-touch attribution in plain English and get a computed answer, instead of manually stitching together spend data from each ad platform and pipeline data from your CRM.
Can Terno AI compute multi-touch attribution across Google Ads, Meta Ads, and LinkedIn Ads? +
Yes. Terno AI connects to each platform's official API and joins that spend and conversion data with your CRM, so it can compute first-touch, last-touch, or multi-touch attribution across every channel in a single query.
What's the difference between first-touch, last-touch, and multi-touch attribution? +
First-touch credits the channel that started the customer journey. Last-touch credits the final channel before conversion. Multi-touch distributes credit across every touchpoint in between. Each tells a different story, and Terno AI can compute all three on demand so you can compare them directly.
Can Terno AI calculate blended customer acquisition cost (CAC)? +
Yes. Terno AI can combine spend across every connected ad platform with pipeline and revenue data from your CRM to compute true blended CAC, not just a single-channel CPA.
Is our spend and revenue data safe with Terno AI? +
Yes. Terno AI connects to each ad platform with read-only reporting scopes and deploys inside your own cloud or on-prem environment. It only shares controlled metadata, never raw spend or revenue values, with the underlying LLM.
How is this different from a marketing mix modeling tool? +
Marketing mix modeling typically requires a dedicated statistical model built and maintained by a data science team, often refreshed quarterly. Terno AI answers attribution and channel ROI questions on demand, computed from your actual connected data, without a separate modeling project.
How is Terno AI different from a generic AI chatbot for attribution questions? +
A generic chatbot generates text that sounds plausible. Terno AI generates and executes a real query joining your ad platforms and CRM, so every number is computed, not guessed.
How fast can we set up cross-channel attribution with Terno AI? +
Once your ad platforms and CRM or database are connected, which is a one-click, read-only authorization for each, attribution questions can be asked immediately, since there's no separate modeling project to build first.
Can Terno AI account for offline or sales-assisted conversions? +
Yes, if that data lives in your CRM or database. Terno AI can join ad platform data with CRM-recorded outcomes, including deals influenced by sales outreach or offline events, not just online conversions.
How long does an attribution window need to be? +
It depends on your sales cycle. A short-cycle consumer product might use a 7 or 30-day window, while an enterprise B2B sale might need 90 days or longer. Terno AI can compute attribution under whichever window you specify.
Can Terno AI show which channel combinations drive the highest-value deals? +
Yes. Terno AI can query which combinations of touchpoints appear most often in your highest-value closed deals, not just which single channel gets credit.
Does Terno AI replace a dedicated growth or revenue operations analyst? +
No. Terno AI answers the computational questions instantly, but deciding what to do with the answer, like restructuring a budget or changing a go-to-market motion, still benefits from someone who owns that strategy.
Can Terno AI recompute attribution retroactively if we change models? +
Yes. Since attribution is computed on demand from your connected data rather than precomputed and stored, switching models means asking the same question again under the new model, not rebuilding a report.
What happens if we disconnect an ad platform from Terno AI? +
Access to that specific platform can be revoked at any time. Attribution questions involving that channel will no longer be answerable until it's reconnected, but every other connected source keeps working normally.
Can Terno AI show attribution for organic and SEO-driven traffic too? +
Yes, if Search Console or GA4 is connected alongside your paid platforms. Terno AI can include organic channels in the same cross-channel attribution picture, not just paid media.
Can Terno AI help justify a budget shift to finance or leadership? +
Yes. Since every number is computed from a real query against connected data rather than a static slide, the same attribution question can be asked again with updated numbers whenever it needs to be revisited.
Can Terno AI compute attribution at the individual campaign level, not just channel level? +
Yes. Attribution can be computed at whatever level of detail you ask for, from a blended channel view down to an individual campaign or creative, as long as that granularity exists in the connected platform's data.
Get Started with Terno AI
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