Every report gives a different answer.
Filters, date logic, definitions, and source systems are not aligned.
Data + reporting
Stop arguing with the dashboard. Start using it.
A beautiful report cannot rescue unclear definitions or unreliable data. We clean the foundation, align the metrics, and build reporting around the decisions leadership, marketing, sales, and service actually need to make.
Data cleanupGovernanceAttributionFunnelsForecastingDashboardsPipeline velocityCustomer health
The symptoms
Recognize any of these?
The visible annoyance is usually connected to a process, ownership, or data decision underneath it.
The dashboard is full. The meeting is still confused.
Metrics exist without a clear decision, owner, target, or response.
Marketing and sales debate lead quality every month.
Lifecycle definitions, qualification rules, source data, and handoff reporting are incomplete.
The forecast is mostly optimism in spreadsheet form.
Pipeline stages, close dates, amounts, and rep behavior do not support a trustworthy view.
Attribution starts a philosophical argument.
The business has not agreed which questions each attribution model can and cannot answer.
Customer risk appears after the cancellation email.
Service, usage, engagement, and commercial signals are not combined into an early warning view.
What we can build
One useful operating system, not another shiny tool.
The exact stack varies. The design principles do not: clear ownership, trustworthy context, tested logic, and a human path when the system needs judgment.
Metric + decision design
Define the question, user, calculation, data source, target, and action before building a chart.
Data audit
Inspect completeness, consistency, duplicates, timestamps, ownership, associations, and source reliability.
Cleanup + normalization
Standardize values, repair records, deduplicate, backfill critical fields, and create repeatable hygiene rules.
Governance
Create definitions, naming standards, required data, permissions, ownership, documentation, and change control.
Lifecycle + funnel reporting
Measure movement, conversion, leakage, velocity, and handoffs across the buyer journey.
Attribution
Select useful models, explain limits, connect campaign data, and separate influence from false certainty.
Executive dashboards
Create a focused operating view of demand, pipeline, revenue, retention, risk, and leading indicators.
Forecasting
Improve stage logic, close-date discipline, probabilities, categories, pipeline coverage, and review cadence.
Customer health
Combine onboarding, support, engagement, commercial, and feedback signals into actionable risk views.
The design questions
Build the operating logic before the clever configuration.
The work gets safer and more useful when every technical choice connects to a person, decision, exception, and measurable outcome.
A chart shows
What happened
A useful metric explains
Why it matters
A target defines
What good looks like
An owner knows
Who responds
A playbook decides
What happens next
A trusted system proves
The data can support the action
Ways to engage
Start with the right-sized problem.
A focused audit, a defined build, or ongoing ownership can all be the right next move.
Data + Reporting Audit
Scoped
Find why the current numbers disagree and identify the highest-value path to trust.
- Metric and stakeholder interviews
- Data and report inspection
- Risk and gap map
- Prioritized roadmap
Reporting System
Scoped
Clean the foundation and build a focused operating view for the teams making decisions.
- Definitions and governance
- Cleanup and calculated fields
- Dashboards and documentation
- Training and review cadence
Fractional RevOps
$1.5K-$5K/mo
Keep the data healthy, evolve the metrics, and connect insight to the operational backlog.
- Flexible monthly priorities
- Data hygiene and governance
- New analysis and dashboards
- 30-day change or cancellation
What changes the scope? Number of systems, record volume, data quality, object model, historical repair, attribution complexity, required calculations, audiences, and automation needed to keep the data healthy.
How the work moves
Clear decisions before clever configuration.
We make the operating logic visible, build it carefully, test the real use cases, and leave the team with a system it understands.
01
Discover
Goals, users, current process, data, systems, risks, and the decision the new system needs to support.
02
Architect
Map the future process, ownership, data flow, exception handling, build plan, and measures of success.
03
Build + test
Configure, connect, migrate, automate, validate edge cases, and test the way people actually work.
04
Launch + improve
Train the team, document the system, monitor behavior, fix friction, and prioritize the next improvement.
Data + reporting questions
Good questions.
Useful scope starts with honest constraints and a clear outcome.
Can you make our existing dashboards trustworthy?
Maybe, but we will inspect the definitions and source data before polishing the charts. Often the fastest path is repairing a few critical fields and reports rather than rebuilding everything.
Do you offer attribution reporting?
Yes. We define the business question first, choose appropriate models, connect the necessary campaign and CRM data, and clearly explain what the result can and cannot prove.
Can you clean our CRM data?
Yes. Cleanup may include normalization, deduplication, association repair, required-field backfill, lifecycle correction, owner rules, and safeguards that reduce future decay.
Will you train leadership and users?
Yes. Decision-makers need to understand how to interpret the view, and users need to understand which behaviors make the data reliable.
Retire the spreadsheet debate
Which number starts the argument?
Bring the dashboards, the conflicting reports, and the question leadership still cannot answer. We will trace the disagreement back to the source.