The reports and models we build are tested with the people who use them and documented so your team can maintain them. When you decide what to change, the reasoning is in front of you.
What’s included.
Three steps.
Understand
Agree the task, baseline, source systems and delivery boundary.
Build
Develop and review the code, configuration and integrations in scope.
Verify
Test representative cases, compare with the baseline and hand over.
Recognise the challenge?
Start with the problem you see. Explore what we can change, then open the implementation notes for the detail.
01Contractual customer-report reconciliation
What you may be seeing
- An important customer needs a report our exports cannot produce.
- Staff manually reshape spreadsheets every month.
- The report uses the wrong customer-specific definitions.
- The customer disputes figures that we cannot trace.
- Reports arrive late or contain another account's records.
We reconcile customer-facing reports with the agreed contract and underlying records, making differences visible and explainable.
Implementation & verification
We encode the agreed customer-specific definitions and reporting format as a reproducible transformation. We code validated exports or scheduled reports with the correct account boundary, period and reconciliation rules. We retain source references and report versions so disputed figures can be traced back to contributing records. We verify representative historical periods and exceptional cases against the customer's approved expectations.
How we verify the work
- Translate reporting definitions into executable calculations with stable record grain.
- Reconcile exceptional periods, corrections and late records before automating delivery.
- Apply account filters at the server/data layer and include report version and refresh date.
- Accept on matching approved reference results and on-time reproducible report generation.
Tools considered for this work
Delivery: SQL (the language used to query a database)/reporting development + scheduled workflow integration. Transformation: dbt or versioned SQL (the language used to query a database)/Python. Delivery: existing BI scheduled export, reporting service or n8n for noncritical distribution. Output: required CSV/XLSX/PDF or authenticated portal report. QA: contractual reference cases, row-level access checks and reconciliation tests.
02Embedded customer-reporting installation
What you may be seeing
- Customers repeatedly ask staff for account reports.
- Our portal shows old numbers or incomplete exports.
- Customers cannot filter reports for their own needs.
- An embedded dashboard could expose another customer's data.
- The reporting interface is hard to use on phones.
We build reports into your customer portal with the right permissions, filters and clear explanations.
Implementation & verification
We embed useful reports or build a reporting screen around the client's existing account data and agreed metrics. We code server-verified account access and necessary export/filter endpoints so customer controls cannot bypass data boundaries. We configure refresh, loading and empty states and explain the definitions behind the numbers. We test account separation, freshness and the real reporting tasks customers currently ask staff to perform.
How we verify the work
- Expose only necessary datasets and metrics; select embedding mode based on interaction and authentication needs.
- Enforce tenant restrictions outside editable browser filters and validate export paths too.
- Optimize common queries and show update time and unavailable-data states.
- Measure self-service report completion, report accuracy and reduced manual reporting requests.
Tools considered for this work
Delivery: portal/frontend/backend development + embedded BI configuration. Embedded option: Metabase or the client's Power BI/Looker embedding capability. Custom option: React/Vue reporting components with an authenticated query API (a controlled connection between applications). Data: existing warehouse/SQL (the language used to query a database) metric views with server-enforced customer access. Validation: access tests, query performance checks and export comparison fixtures.
03Business dashboards
What you may be seeing
- We have many reports but no clear picture of business performance.
- Staff spend hours combining spreadsheets.
- The dashboard is full of clicks instead of meaningful outcomes.
- We cannot separate new customers from returning customers.
- The numbers change without anyone knowing whether data is missing.
We connect the records behind your key decisions and create dashboards people can investigate, understand and maintain.
Implementation & verification
We build a concise operational dashboard from reconciled customer, conversion and revenue definitions. We code the necessary SQL (the language used to query a database) transformations and connectors, then configure views that expose the decisions owners actually need to make. We include meaningful business breakdowns and visible freshness or completeness indicators. We verify each headline metric against business records and add alerts for material data or performance changes.
How we verify the work
- Use a small metric set with agreed decisions, denominators and reporting periods.
- Separate acquisition, customer journey and revenue views without mixing record grains.
- Reconcile totals and label incomplete/fresh data before creating trend alerts.
- Accept on correct reproducible metrics and faster answers to agreed operating questions.
Tools considered for this work
Delivery: BI configuration + SQL (the language used to query a database)/data-integration development. BI options: Looker Studio, Power BI or Metabase; retain the client's suitable platform. Data: warehouse/SQL (the language used to query a database) views with dbt tests and shared metric definitions. Sources: CRM (a system for managing customer relationships), orders/bookings and GA4 (Google Analytics 4)/PostHog. Automation: existing scheduler; n8n for supported noncritical API (a controlled connection between applications) synchronization.
04Connect the enquiry to the eventual customer
What you may be seeing
- Marketing reports count enquiries, but sales reports show different results.
- The team cannot follow calls, bookings or renewals back to the original journey.
We connect acquisition, enquiries and business outcomes around agreed customer definitions. Your reports distinguish an initial lead from a qualified opportunity, completed sale or retained customer.
Implementation & verification
We connect acquisition, enquiries and business outcomes around agreed customer definitions. Your reports distinguish an initial lead from a qualified opportunity, completed sale or retained customer.
How we verify the work
- Agree customer identifiers, permitted joins, revenue adjustments and the treatment of duplicates.
- Reconcile a sample from campaign and website records through the customer relationship system to the completed transaction.
- Show missing matches and attribution limitations instead of assigning every unknown outcome to a channel.
Ask questions. Follow the evidence.
An AI reporting assistant can explain an agreed dataset in plain English. We connect it to shared metric definitions and permissions, with source records and freshness visible alongside the answer.
Explore the technical toolkit
Selected around your existing stack, licences, permissions and agreed scope.
Define what better means.
Trust
Reconciliation, event completeness and data freshness.
Decisions
Time to answer a defined operational or customer question.
Outcomes
Qualified conversions, retention and experiment uncertainty.
Targets follow the baseline. These are measurement areas, not promised results.
Engineering terms, explained
- Grounded AI / RAG
- An assistant retrieves relevant approved evidence before generating an answer. Access controls and evaluations still need to be engineered and tested.
- Idempotency
- Retrying the same operation does not create an extra order, payment or record.
- Controlled experiment
- A concurrent comparison of assigned variants, with a defined outcome, observation window and decision rule.
- Core Web Vitals
- Measures of main-content loading, responsiveness to interaction and visual stability.
Technical references: Web Vitals · Azure document access · Structured data guidelines.
Quick answers.
We already have analytics. What would you change?
We check whether it answers your actual business questions. That can mean repairing collection, reconciling reports or connecting activity to orders and qualified leads before adding another dashboard.
Can you run A/B tests on a low-traffic product?
Not every product has enough traffic for a useful result. We assess the sample and decision window first. Where a test is impractical, we use task research and monitored changes, with the limits of the comparison made clear.
Can staff ask questions in plain English?
Yes, within a defined set of data and permissions. We build the governed queries and evidence retrieval behind the answer, then check factual accuracy and access boundaries.