Measurement before spend. Analytics, attribution and lifecycle automation read from the same data the operations system writes, so campaign reporting and finance reporting cannot disagree.

01 / Deliverables

What you get

  • A measurement layer reading from the same records finance reports on
  • Server-side event tracking that survives browser and consent restrictions
  • Attribution with its assumptions written down, including what it cannot see
  • Lifecycle automation triggered by operational events, not by guesswork
  • A dashboard whose numbers reconcile with the ledger, and a note when they cannot
02 / Method

How it works

01

Audit the measurement

We compare what the analytics platform reports against what the ledger records, and quantify the gap.

02

Fix the collection

Server-side events, consistent identifiers, and a documented event schema.

03

Model attribution honestly

With its limits stated, because attribution is an estimate and pretending otherwise misleads spend.

04

Automate the lifecycle

Messages triggered by real operational state — shipped, delayed, replenished — not by a calendar.

How a PIYAVE Labs platform is assembled A schematic of one platform. Four source systems — point of sale, suppliers, warehouse and the web storefront — write into a single core platform in the centre. The core platform holds one record and is highlighted. From it, three surfaces read: finance, operations and reporting. POINT OF SALE SUPPLIERS WAREHOUSE STOREFRONT FINANCE OPERATIONS REPORTING CORE PLATFORM ONE RECORD

Reference architecture — source systems write once into a single modelled record; every surface reads from it.

The limit

We will not implement tracking that ignores a consent signal, and we will not build attribution we cannot explain to your finance team.

03 / Questions

Asked before you ask

Tell us what is not working

Describe the system you are running on now. We will tell you what we would change, what it would cost and how long it would take.