Marketing analytics
A dashboard is useful when the team agrees what the numbers mean and knows what to do next.
Same business. Different numbers?
The advertising platform counts a conversion, the CRM counts a deal and the accounts show a payment. These may describe different moments, or different customers. We reconcile definitions and data flows before building another chart.
What we work on
Agreed measurement definitions
A clear description of an enquiry, customer, paid order, cancellation and repeat purchase in your reporting.
A data quality review
Checks for duplicates, missing events, mismatched periods and differences between analytics and operational records.
Reports with a decision attached
Views of acquisition, customer behaviour and sales performance designed around the questions your team actually needs to answer.
How the work takes shape
Define the question
Specify the decision the report should support and the period, customer population and cost categories it needs.
Reconcile the records
Follow a sample of customers and orders through the systems. Record discrepancies and test their extent before drawing conclusions.
Make reporting repeatable
Document definitions, responsibilities and refresh logic. Add a review cadence so the report remains useful as the business changes.
For teams that need to explain channel performance, understand repeat purchases or trust the numbers behind a budget decision.
See it in practice
A simpler CRM, clear responsibilities and courier delivery connected through Telegram.
Read the case
A few useful answers
Can a report prove a campaign caused a sale?
An attribution report alone cannot establish that. Where feasible, a properly designed comparison or experiment gives stronger evidence of incremental impact.
What if our data is incomplete?
We identify which conclusions the data supports and which gaps need work. We do not fill missing evidence with precise-looking estimates.