An error appears during reporting
A drop in events or conversions is noticed only when the data is needed for a decision.
Ongoing analytics · maintenance · development · decisions
Continuous care for analytics, reporting and data that keeps pace with the business.
I take ownership of the operating rhythm around measurement and reporting: monitoring data quality, delivering an agreed change backlog and answering business questions. Each request does not restart with discovery because I retain the architecture, definitions and decision history.
This model suits companies that need regular analytics expertise but do not yet need a full internal team. Monthly capacity, priorities and response windows are matched to the real scope.
One owner of contextstack, KPIs, change history and priorities remain connected
Planned capacitymaintenance, development and analysis share one visible backlog
Monthly work reviewdata status, delivered work, usage and next decisions
Common starting point
Analytics exists, but no one owns its day-to-day usefulness.
After launch come small changes: a new campaign, rebuilt checkout, additional dashboard or conversion issue. Without an owner they form a queue that no one prioritises deliberately.
The backlog has no owner
Marketing, sales, product and management submit requests, but no one evaluates dependencies or priority.
Every request begins with discovery
Another person has to relearn GTM, sources, KPI definitions and earlier decisions.
Reporting requires manual work
Exporting, joining and correcting data takes time and makes the result hard to trace.
Questions wait for a separate project
A sales or marketing-channel diagnosis is deferred because there is no simple way to start it.
Changes break earlier solutions
A new CMP, checkout, CRM or campaign affects measurement without analytics taking part in acceptance.
Monthly operating system
Ongoing support turns a request list into a controlled cycle of maintenance, development and decisions.
A regular rhythm does not mean a rigid plan. A critical issue may change the order, but its cost to other work is visible and agreed.
Data and system health
Monitoring, alerts, change controls and user signals.
Outcome: status and new risksPriorities and capacity
Business impact, urgency, dependencies, estimate and decision owner.
Outcome: current backlogAnalysis and change
Diagnosis, report, configuration, test, documentation and handover.
Outcome: accepted workMonthly review
Effect, capacity usage, risks and recommendations for the next actions.
Outcome: next-cycle decisionsIncident before improvementloss of critical data may change the monthly plan
Impact before task countbacklog order follows value, not arrival time
Documentation within deliverychanges, definitions and decisions remain in company context
Three service streams
Capacity is shared between stability, development and business questions.
The balance changes with the business stage. One month may focus on measurement repair, another on reporting development or commercial analysis.
RUN
Maintenance and quality
Work needed to keep data available, current and understandable.
- GA4, GTM and conversion monitoring
- QA after website changes
- integration and refresh checks
- anomaly and gap diagnosis
- documentation and access hygiene
CHANGE
Measurement and report development
Small and medium changes that do not require a separate project.
- new events and parameters
- dashboard and KPI development
- recurring-report automation
- BigQuery and source integration
- specifications for IT
INSIGHT
Analysis and decision support
Answers to questions that require more than reading a dashboard.
- funnel and sales-change diagnosis
- channel and campaign performance
- customer segments and behaviour
- metric-definition reconciliation
- business review preparation
Visible outcome
The Analytics Control Board combines data health, work and decisions.
The format can fit your tools. Sponsors and teams should see what works, where risk sits and how monthly capacity is used.
Analytics Control BoardIllustrative monthly viewCurrent status
Primary signal
Purchase completeness declined after a checkout change
Diagnosis shows a missing value parameter in one payment path. Repair and retest take priority over dashboard development.
Next decision: publish the fix- RUN
Checkout QA
In progress - CHANGE
New margin view
Planned - INSIGHT
Lead-source analysis
Decision needed
The view illustrates service management; it is not a ready-made product or a client-result claim.
Capacity selection
The hour package is a delivery limit, not the purpose of the service.
Capacity follows the number of systems, frequency of change and expected delivery pace. It can be adjusted after the first cycles using the real backlog.
Stability and consultation
For a mature implementation with few changes and a team that handles most operations.
- critical-data checks
- a smaller remediation backlog
- consultation and monthly review
Maintenance and active backlog
For marketing, product or e‑commerce teams needing monthly analysis and measurement changes.
- stable RUN / CHANGE / INSIGHT split
- regular priority planning
- more concurrent needs
An analyst close to the team
For several stakeholders, an intensive backlog and more frequent alignment.
- larger monthly capacity
- participation in the team rhythm
- cross-functional change coordination
Scope before hours. We first agree systems, responsibility, meeting rhythm, request channels and availability. Only then do I propose capacity and pricing.
Priorities and availability
Not every request is an incident, and not every incident can wait.
Classes organise communication. Response windows, channels and operating hours are defined in the agreed service model.
| Class | Example | Handling | Plan impact |
|---|---|---|---|
| P1 · Critical | Loss of critical conversions or an unavailable operational report. | Response within the agreed window, rapid diagnosis and impact-reduction plan. | May pause the active backlog. |
| P2 · Significant | Partial data gaps, KPI inconsistency or one segment affected. | Diagnosis and estimate in the current cycle. | Order changes after agreement. |
| P3 · Development | A new event, dashboard, integration or automation. | Backlog, scope refinement, delivery and acceptance. | Planned by value and dependencies. |
| P4 · Exploration | A hypothesis, ad-hoc analysis or new-tool assessment. | Timebox or separate estimate before delivery. | After higher-priority work. |
Starting collaboration
First we establish the baseline and rules. Then we move into a regular rhythm.
- 01Outcome: recommended model
Needs qualification
Systems, audiences, current problems, change frequency, contact expectations and team responsibility.
- 02Outcome: baseline and inventory
Onboarding and baseline
Access, documentation, KPIs, sources, dashboards, current risks and open work.
- 03Outcome: service handbook
Operating rules
Request channel, priority classes, planning rhythm, acceptance, capacity reporting and escalation.
- 04Outcome: first-cycle plan
First backlog
We separate incidents, technical debt, development and questions and rank them by impact.
- 05Outcome: closed work
Delivery and acceptance
Each task has a scope, outcome, test or answer and a trace in documentation and reporting.
- 06Outcome: next-month plan
Review and capacity adjustment
We review data health, delivered impact, usage, open risks and the service model.
Working standard
Every task should end with an outcome the team can verify.
Definition of done follows the work type. An analysis, GTM change and automated report need different acceptance criteria.
Service boundaries
Ongoing care does not mean unlimited scope or 24/7 support.
- The service has defined capacity.A new task may change priority or timing or require an additional estimate.
- Availability is agreed.Response windows, channels and urgent handling follow the service model.
- A large project may need separate scope.Migration, enterprise BI or architecture redesign may exceed sensible monthly capacity.
- Monitoring cannot detect every error.Coverage depends on sources, tests, alerts and change information from the team.
- Data does not replace an owner's decision.I provide diagnosis and recommendation; priority and action remain with the organisation.
- Unused and carried capacity needs an explicit rule.Commercial terms are agreed rather than assumed to be identical for every client.
Continuity from implementation to daily use
I connect technical measurement expertise with business analysis.
I work with GA4, GTM, Piwik PRO, BigQuery, Looker Studio, Power BI and Tableau. I can move from quality diagnosis through configuration change to reporting and decision support without repeatedly handing the task between suppliers.
20+years of experience
150+analytics and data projects
50+clients
Figures refer to the broader analytics, data and digital-transformation practice, not only retainer clients.
Before we talk
Frequently asked questions.
How does ongoing support differ from a project?
A project has one outcome and an end. Ongoing support retains context, quality and a backlog after delivery. Monthly capacity covers monitoring, smaller changes and analysis, while a large scope may still need a separate project.
How is monthly capacity selected?
It follows the number of systems, change frequency, meeting rhythm, monitoring scope and backlog. After the first months, planned and actual use can be compared and adjusted.
Does unused capacity carry over?
That depends on the agreed model and offer. Capacity is reserved for a specific period, so unused, carried and additional work terms are agreed before launch.
How are urgent data problems handled?
Before launch we define critical cases, request channels, operating hours and response windows. An urgent incident may displace development work in the active backlog.
Can you work with our team or agency?
Yes. I can own measurement and analysis, prepare development requirements, perform change QA and structure decisions. Roles, access and acceptance are agreed during onboarding.
Can the service cover GA4, BI and BigQuery together?
Yes, when that scope is realistic for the available capacity. We first identify critical systems and ownership. More technologies and stakeholders require more capacity or a narrower cycle priority.
First step
Show the current stack, backlog and how the team uses data.
I will follow up on systems, audiences, quality, change pace and expected availability, then propose onboarding, monthly capacity and operating rules.
Assess the starting point