Turn Messy Marketing Data into Decisions that Drive Revenue
Your data should be driving decisions — but conflicting metrics, broken pipelines, and tools nobody trusts are getting in the way. We fix that. Then we turn the cleanup into analytics, workflows, and AI your team can actually trust.
- Marketing analytics and attribution you can defend
- Trusted data foundations your team actually uses
- AI-powered activation built on clean data
For mid-size SaaS and ecommerce teams ($10M+ ARR or venture-funded).
What We Do
Stop Guessing Which Channels Drive Revenue
For the VP of Growth who cannot prove ROAS to the board — and the RevOps team tired of defending numbers that still do not match.
- Marketing analytics and attribution
- Revenue operations metrics
- Cross-channel performance analytics
- Ad spend optimization
Your Dashboards Are Lying. Fix the Foundation.
For data leaders who need more than technical capacity. We make the data trustworthy enough for dashboards, decisions, and AI workflows — without losing the business context that makes the models useful.
- Data strategy and architecture
- Pipeline development
- dbt implementation
- Data governance and AI readiness
Data Sitting in Your Warehouse Isn’t Working
For product and growth teams tired of rich data gathering dust. We ship activation workflows — reverse ETL, scoring, automated audiences — that prove value in weeks, not quarters, and start with one MVP that changes a real decision.
- Reverse ETL implementation
- AI-powered predictions and scoring
- Warehouse-as-CDP solutions
- Automated activation workflows
Exploring AI but not sure your data is ready?
Start with an AI readiness auditStart with the problem, not the service line
If you know where trust is breaking but do not yet know which engagement fits, start with the diagnostic built for that situation.
Growth / Performance Marketing
Where Did the Money Go?
You are spending aggressively on paid channels and still cannot defend which half of the budget is working.
See the spend diagnosticRevenue Operations
Three Teams, Three Numbers
Marketing, sales, and finance are all reporting different versions of revenue and nobody trusts the board deck.
See the metric-alignment diagnosticProduct, Analytics, or Growth Leadership
The $500K Question
You are about to bet a quarter of roadmap and growth effort on something that might not move revenue.
See the growth-leverage diagnosticHead of Data / Analytics
Translate the Ask
The business asked for better analytics, but nobody has translated that into a build plan your team can trust.
See the translation sprintEcommerce
Show Me the Margin
Revenue is up, but you still cannot see the real profit by channel, product, and customer segment.
See the profitability diagnosticBuilt on tools you already know
“Most companies do not have a dashboard problem or an AI problem first. They have a data trust problem.”
People buy from people
Work directly with the person doing the diagnosing
Most teams I talk to have the same problem: they do not know who to trust and what to do next with the budget they already have. I help mid-size SaaS and ecommerce teams cut through that uncertainty, sort out what is actually broken, and turn messy marketing and revenue data into decisions leadership can use.
- Former Director of Data & Analytics at Springboard
- Works across attribution, RevOps, analytics engineering, and AI-readiness diagnostics
- Hands-on with dbt, BigQuery, Snowflake, Databricks, HubSpot, and Salesforce
Jason B. Hart
Operator, translator, and builder for messy revenue and data questions.
Trusted by data-driven teams
From stronger data hygiene to AI workflows teams can actually trust.
Client names are withheld here because many teams do not want public attribution at this stage, but each example below is specific enough to sound real and points to the closest published case study.
Proof for the situations we talk about
A few representative examples of what happens when messy marketing and revenue data gets connected to decisions leaders can actually act on.
Growth / Attribution
From conflicting dashboards to one trusted attribution pipeline
A 300-person SaaS growth team stopped arguing with finance and started making budget decisions in hours.
We unified ad platforms, CRM, and billing data into one attribution pipeline the growth team and finance team could both trust.
Read case studyProduct-Led Growth / Activation
A churn-reduction workflow shipped in 3 weeks
Warehouse data moved from passive reporting to a live retention workflow.
A PLG SaaS team used reverse ETL and churn-risk scoring to get high-signal accounts into the CRM fast enough to act.
Read case studyEcommerce / Profitability
True channel-level ROAS cut wasted ad spend 35%
A DTC brand stopped trusting platform-reported vanity numbers and started reallocating budget based on real outcomes.
We connected ad spend, Shopify revenue, and downstream outcomes so the team could see which channels were actually profitable.
Read case study