Analytics & Business Intelligence
Most businesses are not short of data — they are short of trustworthy answers. We consolidate your sources, define the metrics once, and build reporting your team stops second-guessing.
Typically the right fit when
Dashboards built without a question behind them get opened twice. These are the kinds of questions our reporting work usually starts from.
Revenue
Product
Operations
If your version of one of these takes a week to answer — or produces a different figure depending on who answers it — that is the problem this service exists to fix.
What changes
Trust in reporting is built by defining the metric once and making every figure traceable back to its source.
We write down what "active customer" or "qualified lead" means, then implement it once. Half of all reporting disputes are definitional.
The recurring pack that currently takes a person a day arrives on schedule, populated, without anyone touching it.
Each dashboard starts from a question somebody actually needs answered, which is why they stay in use after the first month.
Every figure traces back to its source, so when a number looks wrong you can check it instead of arguing about it.
Capabilities
Most engagements start with consolidation and metric definition, because dashboards built on unmodelled sources do not survive scrutiny.
Real-time views of the metrics your team acts on, designed for the decision they support.
Pipelines that bring product, finance, marketing and support data into one modelled source.
A written, agreed dictionary of your core metrics, implemented consistently everywhere.
Scheduled reports and threshold alerts delivered to email, Slack or your intranet.
Event tracking and funnel instrumentation that shows where users actually stop.
Trend analysis and scenario models for planning, with their assumptions stated plainly.
How it runs
The build is the quick part. Agreeing what each metric means, and reconciling it against a period you already know, is what makes the output trustworthy.
We collect the decisions your team makes repeatedly and the questions that precede them. Dashboards designed without this step get abandoned.
Every system holding relevant data is catalogued along with its quality, gaps and refresh rate.
Data is consolidated into a modelled layer with transformations under version control, so figures are reproducible.
Dashboards built, then checked line by line against a known period until the numbers reconcile.
Training on reading and extending the reporting, plus documentation of every metric definition.
The pipeline code and the metric dictionary matter as much as the dashboards — they are what let your team extend the reporting without us.
Already invested in a BI platform? We build into it rather than argue for a migration you do not need.
Questions
Analytics tells you what happened on your website. It cannot tell you which of those visitors became profitable customers, because that lives in your CRM and billing system. The value comes from joining those sources together.
Usually four to six weeks for the first one. The build itself is quick; agreeing what the metrics mean and reconciling the numbers against a known period is what takes the time, and skipping it produces reporting nobody trusts.
Yes. If you have already invested in Power BI, Looker or similar, we build into it. We only recommend a change when licensing cost or a genuine capability gap justifies one.
That is the normal starting condition. The source audit exists to surface exactly how messy, and we tell you which gaps must be fixed before the reporting is meaningful versus which can be worked around.
Tell us the question you cannot currently answer. We will show you what it would take to answer it reliably.
No obligation. We will tell you if we are not the right fit.
Connect the tools you already run and remove the manual steps between them.
Search, content and paid campaigns measured on pipeline rather than impressions.
Custom web applications and internal platforms engineered to hold up in production.
