No single view of the customer
Data split across systems that don't talk to each other. To understand one user, someone has to pull from multiple sources and reconcile it manually.
The problem01 02 03
The problem
AI is useless on data you can’t trust
You want personalization, churn prediction, automated journeys. None of it works when the underlying data is fragmented or missing.
Every team has different numbers
Product uses one source, finance another, growth a third. The team that shouts loudest wins the debate.
Our approach
Three phases. One source of truth.
We don't start with tools. We start with the questions your teams need to answer — then reverse-engineer the data, architecture, and connections required.
Use Cases & Tracking Plan
Weeks 1–4We run workshops with each team — Growth, Product, Finance, Customer Support. We ask what decisions they need to make, then work backwards to define the exact events and properties required.
Deliverables- Tracking Plan — events, properties, owners, priority
- Workshops with each business team
- Work plan for Phase B
Stack, Architecture & Implementation
Weeks 3–10 (runs parallel)We define the stack, design the data model, resolve customer identity across all systems, and build the pipeline. Every destination receives QA-verified data before we connect it. We document governance processes so nothing breaks six months from now.
Deliverables- Architecture diagram
- Data models + dbt documentation
- QA validation process
- Governance framework
Activation by Team
Month 3+ (ongoing)With clean data flowing, we activate each team in their tools: retention journeys in OneSignal, product funnels in Mixpanel, enriched context in your CRM, revenue analytics in BI. Each team trained to operate without needing to call engineering.
Deliverables- Active flows per team — journeys, boards, dashboards
- Training — each team operates autonomously
- Governance that holds over time
Rhythm
Weekly 60-min call + private Slack channel. We review progress, unblock issues, and define next steps. You never have a blocker sitting for more than a day.
Division of work
Bildung designs, documents, and supports. Your tech team implements. We lead architecture, data modeling, Tracking Plan, QA, and training. You own the pipelines and system access.
Collection & CDP
From fragmented sources to one unified stack.
Every implementation looks different. The logic is always the same: clean data collection, unified identity, a warehouse as the single source of truth, and destinations that receive verified data.
Source
Behavioral Activity
AppsWebsiteOffline
Source
Operational Data
SalesforceHubSpot
ZendeskIntercom
StripeRevenueCat
Source
Marketing Signals
AppsFlyerGoogle AdsMeta AdsTikTok Ads
ApolloSupermetrics
Collection & CDP
Event streaming + batch ETL
RudderStackSegment
Enrichment
Data Warehouse
Snowflakedbt
SnowparkPython
HightouchCensus
Activation
Customer Engagement
OneSignalBrazePendo
Activation
Product Analytics
MixpanelAmplitudePendo
Built for the people who own the data problem.
Head of Data
You inherited a fragmented stack and a backlog from every team. You need architecture that scales and a system that doesn't require you to be the bottleneck for every data request. We build it with you — and document it so your team can maintain it.
Head of Growth
You want to build retention journeys and run real experiments. You can't — because the data feeding your tools is unreliable. We fix the foundation so the work you've been trying to do for months actually becomes possible.
CTO / VP Engineering
You keep getting pulled into ad hoc data requests. You want business teams to have autonomy without breaking production. We design the architecture, document everything, and train teams to operate independently.
Common questions
Ready? Let's fix your data stack.
Book a free 45-minute call. We'll map what's broken, what it would take to fix it, and whether we're the right fit.
Get in touch