Marketing CRM

See which channels actually drive revenue

Multi-touch attribution ties every click, email, and touchpoint to closed deals on your own CRM data, so you fund what works and cut what doesn't.

6+
Attribution models
100%
Touchpoints tracked
Attribution Copilot — Leadify Marketing CRM
6+
Attribution models
first-touch to data-driven
100%
Touchpoints tracked
across every channel
30%
Wasted spend found
typical in first quarter
1
Source of truth
no separate CDP or tool

How it works

Every channel claims the win and last-click gives it all to whoever showed up last, so budgets get set on flattering fiction. Stitching this together usually means a pricey analytics tool that lives apart from your CRM. Attribution Copilot connects every touchpoint to real closed-won revenue inside Leadify, then shows you in plain language which channels, campaigns, and content genuinely move deals forward.

Every touch, one revenue view

From first ad to closed deal, each interaction is captured and mapped to actual pipeline and revenue.

  • Full-funnel tracking across ads, email, web, and sales
  • Ties touchpoints to closed-won revenue, not just leads
  • Cross-device and cross-session stitching
  • One timeline per account and contact

Models you can actually compare

Switch between attribution models to see how each channel's credit changes, then trust the data-driven view.

  • First-touch, last-touch, linear, time-decay, and more
  • AI data-driven model weighted by real outcomes
  • Compare models side by side in one report
  • Drill from channel to campaign to keyword

Answers, not just dashboards

The Copilot surfaces where budget is wasted and where to double down, in plain language.

  • Flags underperforming spend automatically
  • Shows cost per revenue by channel and campaign
  • Recommends where to reallocate budget
  • Exports board-ready ROI summaries

Where teams use it

Built for real revenue work.

Defend and reallocate budget

Walk into planning with proof of which channels create revenue and which just take credit for it, then move spend accordingly.

Value the assist, not just the close

Credit the webinar and nurture emails that warmed a deal instead of handing all the glory to the last paid click.

Prove marketing's revenue impact

Give the board a clean line from campaign spend to closed-won so marketing is seen as a growth engine, not a cost center.

DO
Last-click had us overfunding paid search and starving the content that was actually opening deals. The data-driven model reshaped our whole budget in one quarter.
Daniel Ortiz · CMO, a mid-market martech firm
28% lower CAC

FAQ

Questions, answered.

What is multi-touch attribution and why does it matter?

Multi-touch attribution distributes credit for a deal across every interaction that influenced it, not just the first or last one. It matters because single-touch models systematically over-reward some channels and hide the ones doing the quiet work, which leads to budget decisions based on the wrong data.

Which attribution models does Leadify support?

First-touch, last-touch, linear, time-decay, position-based, and an AI data-driven model that weights credit by what actually correlates with closed revenue. You can compare models side by side, so you see how each channel's contribution shifts rather than trusting one view blindly.

Do I need a separate analytics or attribution tool?

No, and that is the point. Tools like Ruler or HockeyStack sit outside your CRM and require ongoing integration and cost. Attribution Copilot runs on the touchpoint and revenue data already in Leadify, so your attribution and your pipeline are the same source of truth.

How quickly can it show ROI insights?

As soon as it has your historical CRM and campaign data, it can build the timeline and run every model, typically surfacing wasted spend within the first quarter. Because it is native to the platform, there is no long implementation project before you see answers.

Fund what works. Prove it.

See exactly which channels drive revenue with multi-touch attribution on your own data.