Revenue Operations
Attribution Modeling
A unified attribution system connecting every marketing channel — paid, organic, direct, referral — to pipeline and revenue. Multi-touch attribution configured to the business's actual customer journey. Dashboards that let leadership see exactly where deals come from and what each acquisition channel is actually worth.
'Attribution' means figuring out which marketing activities actually drove a sale. If someone buys after seeing a Facebook ad, then a Google ad, then clicking an email , which one gets credit? Most companies don't know. They're spending money on 4 channels and can't tell which 2 are working. We build a system that traces a closed deal all the way back to its first touchpoint, so the company can make smarter decisions about where to put their marketing budget.
Generate a dense, AI-written operator playbook for this service: executive overview, business problems solved, technical foundations, stakeholder positioning, sequencing, delivery reality, financial logic, objection matrix, failure modes, AI coach notes.
They're spending on paid media without knowing what's working. They're making channel budget decisions on gut feel. Their board or investors are asking for CAC and ROAS data they can't produce. Their CRM and analytics are disconnected — no bridge between marketing activity and revenue.
A closed-loop view from marketing spend to closed-won revenue. Defensible CAC and ROAS by channel. Confident channel-budget decisions backed by data instead of gut.
Companies with reliable CRM data, consistent UTM discipline, sufficient deal volume to draw conclusions, and an internal owner who can interpret and act on attribution insights.
- Rising paid spend
- Platform-reported ROAS not matching reality
- Multi-touch journeys getting longer
- CFO pressure on marketing ROI
- CRM data is unreliable — attribution flowing into bad data produces wrong answers
- Tracking infrastructure doesn't exist (UTM discipline, event tracking, form tracking)
- Not enough volume to draw attribution conclusions
- No one internally to interpret and act on attribution data
- No consistent UTM tracking
- Spend volume too low to produce meaningful attribution data
- Do not start before CRM is reliable
- Do not start before tracking is validated
- If I asked you what your cost per acquired customer is by channel right now, what would you say?
- How do you currently make decisions about where to increase or decrease ad spend?
- Is your CRM connected to your analytics platform? Can you trace a deal back to its first touch?
- Do you track UTMs consistently across all campaigns and channels?
- When a deal closes, do you know what sequence of touchpoints got them there?
- Reliable CRM data
- Clean conversion tracking
- Sufficient data volume
- Internal analytics owner
- Unified tracking spec
- Attribution model
- Reporting dashboard
- Channel-level reporting
- Documentation
- Reported vs. actual ROAS gap
- Channel-level CPA
- Pipeline by source
- Unreliable CRM
- Tracking gaps
- Cross-domain journey not modeled
- CEO: You'll finally know what's actually driving revenue — and stop guessing.
- CMO: Every budget conversation with the board will be backed by actual attribution data.
- RevOps: You'll have a closed-loop between marketing spend and CRM closed-won — at last.
- Heavily dependent on clean upstream data — if CRM or tracking is messy, attribution will be wrong
- Requires access to all ad platforms, analytics, and CRM
- Results improve over time as more data accumulates — this is not instant
- Client must commit to UTM discipline going forward or the model degrades
- Audit
- Tracking spec
- Model design
- Implementation
- Validation
- Reporting build
- Engineering
- Strategy
- crm-setup
- funnel-optimization
- lifecycle-automation
Attribution modeling that turns platform fiction into operational truth.
Server-side tracking, identity resolution where possible, warehouse-backed model preferred at scale.