Marketing Attribution & Data Engineering

Overview

What we deliver

We build attribution systems and data pipelines that connect campaigns, touchpoints, and revenue so you can credit spend correctly.

We help B2B marketing teams answer the question of what is actually working. Our team builds attribution models and the data engineering behind them, so every touchpoint, channel, and campaign can be tied back to pipeline and revenue. We design models that match your buyer journey, whether that is first touch, last touch, linear, position-based, or a custom blend. The engineering work behind it includes connecting ad platforms, CRM, web analytics, and offline sources into a warehouse, then cleaning and modeling that data so it is consistent and queryable. We also handle identity stitching, deduplication, and the time-zone and currency normalization that often breaks reports. The outcome is a defensible view of channel contribution that survives audits, supports planning, and helps you shift budget toward what produces results.

Fit Check

Built for teams like yours

Who it's for

B2B teams with complex buyer journeys
Companies running multi-channel demand programs
Marketing leaders defending budget decisions
Analytics teams needing reliable source data
Organizations consolidating fragmented data

Pain points we solve

Last-click reporting that misses real drivers
Disconnected data across ad and CRM systems
Duplicate leads and contact records
Conflicting revenue numbers between teams
No way to compare channels on equal footing

What's included

Capabilities

Everything we cover in this engagement.

Attribution model design and selection
Data warehouse setup and modeling
ETL and ELT pipeline construction
Identity resolution and deduplication
CRM and ad platform integration
Offline conversion import flows
Data quality monitoring
Documentation and governance

How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Scoping

We map your data sources, buyer journey, and attribution requirements.

02

Architecture

We design the warehouse, pipelines, and model that fit your stack and needs.

03

Build

We construct pipelines, integrations, and data models with testing throughout.

04

Validate

We compare model output against known benchmarks and resolve any gaps.

05

Operate

We monitor pipelines, run quality checks, and refine the model as needed.

What you get

Deliverables & outcomes

What you get

Attribution model documentation
Data warehouse and modeled tables
ETL or ELT pipeline code
Integration with CRM and ad platforms
Data quality monitoring setup
Governance and lineage guide

Outcomes you can expect

Clear and defensible channel attribution
Reliable single source of truth
Better budget allocation decisions
Reduced manual data reconciliation
Stronger trust in marketing reporting

Timeline

10 to 16 weeks for initial build

Engagement

Monthly retainer, Project, Sprint

Tools we use

BigQuery, Snowflake, dbt, Fivetran, Segment

KPIs we track

data freshness, pipeline reliability, model accuracy, channel contribution variance, source coverage

Client stories

What clients say

"

We were paying three agencies and a lifecycle freelancer to argue over attribution. RevoraOps absorbed all of it in 30 days, killed our worst-performing Meta ad sets, and rebuilt the welcome flow from scratch. CAC dropped 31 percent in the first full month. Honestly the relief of having one weekly call instead of four was worth it alone.

Megan W.

"

We were drowning in tier-one tickets about password resets and appointment changes. They built a deflection layer on top of our help desk and kept their agents in the loop for anything sensitive. Volume to humans dropped 58 percent in two months and our patient NPS held steady. The hybrid handoff is the part most vendors get wrong. They did not.

P.M.

Proof