Fractional data team
Vision Labs works as your fractional data team, connecting marketing, CRM, product, operations, and revenue data so every decision starts from the same identities, definitions, and history. You get senior strategy, engineering, analytics, and implementation without building a full in-house data function first.
The operating model
A fractional data team is a group of senior specialists working inside your company without becoming full-time hires. Instead of asking one person to cover strategy, tracking, engineering, analysis, and reporting, you get the skills the system needs.
The team works in your stack and operating rhythm, with a shared roadmap and clear ownership across marketing, product, engineering, and operations.
When source data, identities, definitions, and pipelines do not line up, every report and AI answer inherits the same gaps.
One connected foundation
Reports and AI can only work with the context they receive. We connect the business systems first, so every interface starts from the same identities, definitions, history, and targets.
We agree on the decisions the system needs to support, define the KPIs behind them, and decide who owns each source and metric. Our web analytics measurement strategy shows how we turn that thinking into an implementation plan.
We implement or repair the collection layer across websites, products, forms, and server-side events. That can include GA4, GTM, PostHog implementation and optimization , and the identity rules that connect an anonymous visit to a known customer.
We connect marketing, CRM, product, billing, and operational sources, then clean and model the data in the warehouse. The right setup may use a CDP, reverse ETL, dbt, BigQuery, or tools already in your stack. See how we approach CDP implementation and data warehouse setup and management .
We build reporting around the questions each team has to answer. Executives, marketing, product, and operations can use different views while working from the same definitions and source data.
Clean conversion and audience signals can flow back into your CRM, product, and ad platforms. The same connected system can give AI workflows the definitions, targets, and history they need to answer business questions with context. Reporting and AI become interfaces on a maintained data foundation.
Scope
The exact mix changes with the problem. A typical Vision Labs engagement can include:
Choose the right operating model
Hire one analyst when the tracking, warehouse, definitions, and recurring pipelines already work. Choose a different model when the work crosses several disciplines or nobody inside the company can own the architecture, priorities, and quality.
The fractional model gives you cross-functional coverage now and a documented system a future internal team can inherit.
Vision Labs has already covered this gap in practice. For Jeff Walker's team, Vision Labs managed complex launch reporting that would otherwise have required dedicated headcount. The system connected server-side tracking, Keap, BigQuery, and Looker Studio so the team could see lead-to-LTV economics in one place. Read the Jeff Walker case study .
Built around your business
You do not need to buy a standard bundle or migrate every tool. We start with your existing systems and custom product or engineering data.
We keep tools that serve the architecture and replace only material constraints. The business question, data volume, ownership, and maintenance capacity drive the recommendation.
Vision Labs' reporting and AI workflows are part of the service, not a separate SaaS subscription.
From first question to ongoing ownership
We map the current system, build the pieces blocking the most important decisions, then stay involved where the system needs ongoing ownership.
We start with the decisions your team cannot make today, then trace the sources, definitions, owners, and failure points behind them. The output is a plan scoped to the system and the decision.
We fix the parts of the system that block the most important decisions first. Depending on the company, that may be identity, broken events, CRM stages, warehouse models, or reporting. The sequence and timeline depend on access, stack condition, and implementation complexity.
Once the foundation works, we monitor quality, answer new questions, and evolve the system as the business changes. Your team has direct access to the people doing the work, plus regular sessions to turn what the data shows into a next action.
Proof from the connected system
With the sources and definitions connected, the team can trace acquisition to customer value, return better signals to operating tools, and answer new questions without rebuilding the logic each time.
For Natural Heart Doctor, Vision Labs tied every lead to revenue and reported lifetime value by acquisition channel from one unified customer profile. Connecting the identity and revenue data first made that analysis possible.
Read the Natural Heart Doctor case studyVision Labs has shipped more than 20 PostHog implementations and currently manages around 30 PostHog accounts. That is proof of one implementation layer, not the whole offer. The team also works across GA4, GTM, BigQuery, CDPs, CRMs, advertising platforms, and custom sources.
“Vision Labs uncovered things we didn't even think to check.”
We will help you identify which part of the system needs to change first and whether the right next move is a focused project, a fractional team, or one specialist.
Fit
Vision Labs is a strong fit when data quality affects real decisions, but nobody owns the whole path from collection to action. You may already have an analyst or engineering team.
The model works especially well for growing SaaS, ecommerce, subscription, information-product, media, and multi-site companies that need several data skills before several full-time hires.
It is usually not the right fit for a pre-revenue company, a one-off dashboard from clean data, or an individual contractor filling a fixed seat.
We will say when one specialist or a smaller project is enough.
Scope-dependent pricing
Starting at $3,000 per month
Final pricing depends on the complexity and condition of your current stack, the number of sources, implementation depth, data volume, access, and the ongoing ownership required.
A complex build may begin with a dedicated implementation phase. After the first conversation, you receive a clear proposal based on which parts of the system need to change. We do not price by dashboard count or one analyst's hours.
Questions before the call
The terms overlap, but the operating model matters more than the label. Vision Labs uses "fractional" because the team works inside your operation, joins your communication rhythm, and stays responsible for an evolving system. A one-time outsourced project can end at delivery; a fractional engagement or data team as a service can continue to operate, maintain, and improve what was built.
Yes. We can own the architecture and implementation backlog, support an analyst with cleaner models and definitions, or work with engineering on events and data access. Responsibilities are made explicit at the start so work does not disappear between teams.
Usually not. We start with your existing stack and custom data, then keep, connect, or replace tools based on the problem. A migration only makes sense when the current tool creates a material limit.
We build and operate the system that makes a dashboard trustworthy: tracking, identity, pipelines, warehouse models, metric definitions, and quality controls. Reporting and AI are interfaces on top of that shared foundation.
AI works after the company has reliable data, definitions, and business context. We connect that foundation first, then help reporting tools, agents, or workflows use the same targets, history, and operating rules. AI is one interface on the system, not a replacement for it.
Two steps
You do not need to diagnose the whole system before we talk. Tell us what does not line up, which sources matter, and which decision your team cannot make today.
On the call, we will understand the problem, clarify the outcome, and decide whether you need a focused project, a fractional team, or one specialist.
Submit the short form. The next screen lets you choose a time with the Vision Labs team.