You’re stuck between "too junior" and "too expensive."
Junior hires can maintain reports but not design proper measurement. Senior analytics leaders are expensive, hard to find, and often overkill for your current size.
Analyze Pillar · Fractional Analytics Team
Senior analytics, without the full-time burn.
Analytico's fractional analytics team gives you senior analysts, data engineers, and measurement strategists on tap. You get the same quality as a full in-house team—without adding headcount, getting stuck in hiring cycles, or managing three different freelancers.
- Plug-and-play team across GA4, GTM, server-side tagging, BI, and experimentation.
- Execution plus thinking: from fire drills and fixes to roadmap and strategy.
- Flexible capacity: scale up during heavy quarters, dial back when things stabilize.
Ideal for growth-stage companies, lean marketing teams, and founders who want enterprise-level analytics without building an enterprise headcount.
Example · Your fractional analytics squad
Core pod
- Lead analytics strategist (your main point of contact).
- Web / product analyst (events, funnels, reporting).
- Data / tagging engineer (GTM, sGTM, server events).
Extended bench
- BI specialist (Looker Studio, Power BI, BigQuery).
- Experimentation / CRO support.
- Ad platform measurement support (Meta, Google, etc.).
You get the team, not just a person.
We assign a core pod that learns your stack and business. When you need deeper specialization, we pull in the right skill from our bench— without you needing to source or manage more vendors.
Why Teams Bring Us In
You don't need more dashboards. You need an analytics team that can actually move the needle.
Most organizations either under-invest in analytics and stay blind, or over-invest in tools and data they can't fully use. Fractional analytics gives you the senior thinking and hands-on implementation you’re missing, without committing to building a full department on day one.
Analytics is always context-switching and fire-fighting.
One week it’s GA4 events, the next it’s Meta CAPI, then a tracking bug, then a dashboard request from the CEO. Internal teams burn out or avoid owning it.
You depend on agencies who don’t speak data.
Media or creative agencies send numbers without explaining what’s real, what’s modeled, and what actually matters for profit and growth.
Important projects keep slipping "to next quarter."
Server-side tagging, attribution rebuilds, governance, and LTV models never get done because nobody has both the time and the skills to own them end-to-end.
Who You Get
A pod of specialists that behaves like your in-house team.
We don't throw random freelancers at problems. You get a stable squad with clear roles, shared context, and accountability across tracking, analysis, and enablement.
Lead Analytics Partner
Owns the relationship, understands your business model, and drives the analytics roadmap alongside you.
- Translates business questions into clear measurement plans.
- Prioritizes analytics backlog: fixes, improvements, and strategic projects.
- Runs recurring analytics reviews with leadership and growth teams.
Web / Product Analyst
Lives in GA4, event streams, funnels, and cohort views to spot what’s working and what’s broken.
- Designs events, conversions, and funnels aligned with your product and marketing flows.
- Builds and maintains reporting views and investigations.
- Documents insights and recommended experiments, not just charts.
Tagging & Data Engineer
Owns the underlying tracking and data flows so that insights are grounded in reality.
- Implements and maintains client- and server-side tagging (GTM / sGTM).
- Sets up data pipelines into BigQuery or your warehouse of choice.
- Monitors data quality, consent impacts, and tracking resilience.
BI / Dashboard Specialist (as needed)
Turns raw data into clean executive and team-level reporting.
- Builds Looker Studio and/or Power BI dashboards with clear narratives.
- Connects GA4, ad platforms, CRM, and backend data into unified views.
- Optimizes performance and usability for recurring decision-making.
Engagement Models
Flexible ways to work with a fractional analytics team.
We'll recommend a model based on your current stack, internal team, and urgency. The goal isn't to lock you into a retainer— it's to match the right level of analytics muscle to where your business is today.
Project + Fractional Combo
Most common starting point
Kick off with a focused project (e.g. GA4 rebuild, measurement reset, server-side tagging) and roll into a fractional pod that maintains and evolves it.
- Clear start/end to the initial project, then ongoing momentum.
- Easy way to get quick wins while building the right foundation.
- Keeps your new setup from decaying after launch.
Monthly Fractional Pod
Ongoing analytics muscle
A fixed level of capacity per month across a dedicated pod. We run standups, prioritize work, and stay plugged into your roadmap.
- Good for teams with constant analytics needs and a steady roadmap.
- Predictable cost with flexibility to rebalance focus month to month.
- Feels like an in-house team—without recruiting and payroll.
Quarterly Sprints
For seasonal or initiative-driven teams
Intense 8–12 week pushes around product launches, growth sprints, or key experiments, with lighter support in between.
- Aligns analytics investment with your biggest quarters or projects.
- Good fit if you have strong ops but lack specialized analytics muscle.
- Can be paired with internal analysts for knowledge transfer.
How We Plug Into Your World
We behave like an embedded team, not an external vendor.
We join your Slack, standups, and planning rituals. We work with your developers, marketers, product managers, and finance leaders— with clear ownership on our side so you're not project managing us.
- Shared backlog of analytics work in your existing tool (Jira, Asana, Linear, etc.).
- Regular cadence: weekly or bi-weekly check-ins plus ad-hoc support for critical issues.
- Clear SLAs and expectations around response times for urgent tracking problems.
- Documentation-first culture: we leave your team with playbooks, not just fixes.
How different teams experience us
For founders / leadership
You get a clear story about where money is going, what it's returning, and what needs to change—backed by trustworthy numbers.
For marketing / growth
You get clean attribution, faster answers to performance questions, and a partner who can sanity-check channels and campaigns.
For product / engineering
You get a single analytics counterpart who understands your stack and respects release cycles and performance constraints.
For finance
You get reconciled numbers and clearer links between marketing activity, product behavior, and real revenue and margin.
The outcome: fewer "what is this number?" conversations, more "what should we do next?" conversations.
Selected Fractional Engagements
Where a fractional analytics team changed the trajectory.
Names can be anonymized, but the patterns repeat: over-stretched teams, under-utilized data, and growth decisions made on gut. Fractional analytics is how we straighten that out without you needing to build an entire department.
E-commerce · Growth-stage DTC brand
Problem: Running paid across Meta, Google, and influencers with inconsistent tracking and no unified view of performance.
What we did: Rebuilt tracking, introduced weekly analytics reviews, and embedded a fractional pod to support campaigns and experiments.
Impact: Clear view of channel profitability, faster test cycles, and the ability to scale spend with confidence.
SaaS · PLG + sales-assisted funnel
Problem: Product analytics, marketing analytics, and CRM reporting lived in different silos with no shared owner.
What we did: Created a measurement framework across GA4, product events, and CRM; then staffed a fractional pod to maintain and evolve it.
Impact: Leadership finally saw a coherent funnel from acquisition to expansion, guiding roadmap and GTM strategy.
Healthcare · Multi-region virtual care
Problem: Complex compliance and consent environment made tracking fragile; internal team had no bandwidth for deep fixes.
What we did: Implemented robust tracking and attribution, then stayed on as a fractional analytics team to support growth and launches.
Impact: Trustworthy reporting in a regulated context, with analytics able to keep pace with expansion.