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06 · Data & Reporting

Marketing attribution & ROI: Connect spend, journeys, calls, leads, work and recognised value without pretending the evidence is perfect.

Lumaivo joins advertising, web, call, contact-centre, CRM, booking, job and finance facts into an attribution model that shows confidence, conflicts and unknowns as well as performance.

Map the first useful step All services

What this service is for

Start with the business meaning, then make the technical route explicit.

Marketing platforms report the activity they can observe. Website analytics covers consented journeys. Phone systems know calls, a CRM knows lead stages, operational systems know fulfilled work, and finance knows recognised revenue or margin. None of those sources is the whole truth by itself.

We independently ingest the relevant facts, preserve source lineage and define deterministic matching rules. Staff-entered source values remain useful comparison evidence, not automatic truth. The output shows where attribution is strong, where it is inferred and where the trail is unresolved.

Where it becomes useful

Common use cases, framed around the decision or hand-off.

01

Calls and forms to outcomes

Connect campaign, landing-page, call and form activity to lead, quote, booking, job and recognised-value stages.

02

Spend control

Compare channel and campaign cost with qualified pipeline, delivered work, revenue or margin at the level the data can support.

03

Conflicting source analysis

Show where platform attribution, CRM source fields and operational evidence disagree instead of selecting a convenient answer.

Method

A controlled route from discovery to an accepted output.

  1. 01

    Inventory the facts

    List spend, click, session, call, form, CRM, operational and finance sources with their identifiers and timing.

  2. 02

    Define the journey

    Agree the lead, quote, booking, job, revenue and margin stages that matter to the business.

  3. 03

    Match deterministically

    Use approved identifiers, windows and reference data to join records without inventing a connection.

  4. 04

    Grade confidence

    Separate direct matches, bounded inferences, conflicts, unattributed records and unknowns.

  5. 05

    Report for action

    Produce channel, campaign and journey views with caveats, reconciliation and drill-through to evidence.

Typical deliverables

What the review-ready work can contain.

  • Source and identifier map across marketing, calls, CRM and finance
  • Attribution rulebook with windows and confidence levels
  • Spend-to-outcome reporting model
  • Unmatched, conflicted and unknown exception views
  • Campaign, channel and journey dashboards
  • Measurement-gap and instrumentation backlog

Boundaries

What stays explicit instead of being over-promised.

  • No model can recover evidence that was never captured; unknowns remain labelled unknown.
  • Consent, privacy and platform-access boundaries are preserved.
  • Recipient reads, spam placement and similar unavailable signals are not inferred from unrelated tools.
  • Attribution outputs explain rule and confidence, not false certainty.

Questions before the first conversation

Plain answers, with the limits left in.

Can you provide perfect attribution?

No honest system can promise that. Consent choices, offline behaviour, shared devices, missing identifiers and manual processes create gaps. We make the supported links, uncertainty and unmatched population explicit.

Can phone calls be included?

Yes, where suitable call-system data, campaign identifiers and privacy controls are available. Calls can then be linked to later CRM or operational outcomes when a valid matching route exists.

Is a CRM source field enough?

It is useful evidence, but staff-entered source values can be incomplete or inconsistent. We compare them with independently captured campaign, web, call and operational facts.

Can reporting use margin instead of revenue?

Potentially, if recognised margin is available at the appropriate level and the finance owner approves the definition. The model records which commercial measure is being used.

Do you replace existing analytics platforms?

Usually not. We connect and reconcile the useful facts from those platforms with downstream business outcomes, then identify specific instrumentation gaps.

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Start with the messy version. Make the first useful outcome explicit.

Send the systems, reports, constraints and decisions involved. Lumaivo will help define a bounded first step and the evidence needed to accept it.

Map the first useful step