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Analytics & Data

Marketing Performance Analysis

Reading the data rather than collecting it: finding what actually changed, what caused it, and what to do differently next quarter.

Panoramica

Plenty of companies have adequate data and no analysis. Reports are produced, numbers are read out, and the meeting ends without anyone establishing why a number moved or what to do about it. Collection has been solved and interpretation has not.

Analysis is a different skill from implementation. It means segmenting until a change becomes explicable, distinguishing a trend from noise, checking whether an apparent effect survives a control, and being willing to conclude that a favoured initiative did nothing.

A chi è rivolto

  • Companies with good data and no idea what it is telling them
  • Teams whose monthly review reads numbers without explaining them
  • Businesses that need an independent read on whether something worked
Cosa è compreso

Il nostro approccio a Marketing Performance Analysis

Le attività concrete che comprende un incarico tipo. Il perimetro si concorda prima: nulla di quanto elencato ricompare più avanti come voce a sorpresa.

  • Diagnostic analysis

    Segmenting a change until it becomes explicable. Aggregate numbers almost always hide the actual movement.

  • Cohort analysis

    Following groups over time, which separates a genuine change in customer quality from a change in mix.

  • Statistical rigour

    Significance, sample size and confidence applied honestly, so a normal fluctuation is not presented as a result.

  • Campaign post-mortems

    Honest reviews of what worked, including campaigns that did not, which is where the transferable lessons are.

  • Competitor and market context

    Whether your change is specific to you or the whole category moved, which changes the conclusion entirely.

  • Recommendations

    Specific actions with expected effect and confidence, rather than observations left for someone else to interpret.

Come procede

Dal primo contatto al risultato misurato

Sempre la stessa sequenza, così sapete cosa viene dopo.

  1. Frame the question

    Agree what needs explaining. Open-ended analysis produces interesting findings nobody acts on.

  2. Check the data

    Verify the numbers before analysing them. A surprising share of dramatic findings are tracking faults.

  3. Analyse

    Segment, compare and test until there is an explanation that holds up rather than one that sounds plausible.

  4. Recommend

    Present findings with actions and confidence levels, including where the evidence is thin.

Perché conviene

Risultati, non pile di documenti

Un cumulo di deliverable non è progresso. Questi sono i cambiamenti che il lavoro deve produrre.

  • Explanations, not just numbers

    Knowing why something moved is what makes the next decision better.

  • An independent read

    An outside view is more likely to conclude that a favoured initiative did nothing.

  • Fewer decisions on noise

    Applied significance testing stops normal variance being treated as a trend.

  • Lessons that transfer

    Honest post-mortems, including on failures, are where the reusable knowledge actually is.

Domande

Domande frequenti su Marketing Performance Analysis

Quello che ci chiedono prima di contattarci. Se la vostra domanda non c'è, fatecela direttamente.

How is this different from your reporting work?

Reporting tells you what happened. Analysis works out why and what to do about it. Many companies have solved the first and assume the second follows automatically, which it does not.

Our numbers dropped and we do not know why. Can you find out?

Usually. The first step is verifying the drop is real, because a meaningful share of dramatic changes turn out to be tracking faults. After that it is segmentation until the change localises to something specific.

Will you tell us if our campaign did not work?

Yes, and that is much of the point of an independent analyst. Internal analysis has an understandable tendency to find reasons a well-funded initiative succeeded.

How much data do you need?

Enough for the change to be distinguishable from noise, which depends on your volumes. For low-traffic sites we would be honest that some questions cannot be answered from the data and need an experiment instead.

State pensando a Marketing Performance Analysis?

Diteci che cosa volete cambiare. Se non siamo i partner giusti ve lo diciamo e vi indichiamo di meglio.

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