Attribution & Marketing-Mix Modelling

Linear vs. Time-Decay

Linear attribution allocates ______ credit across all touchpoints.

Last‑only

Equal

Decreasing

Increasing

Every interaction receives the same share.

Time‑decay attribution assigns greater weight to touches that occur ______ conversion.

Furthest from

Offline

Random in path

Closer to

Credit decays exponentially with time.

GA4’s default time‑decay half‑life is ______ days.

30

14

1

7

Same as Universal Analytics’ legacy setting.

A campaign with long consideration cycles (90 days) might prefer ______ attribution.

Position‑based 40‑20‑40

Last‑click

Linear

Time‑decay

Equal credit recognises early research touches.

Time‑decay tends to undervalue ______ channels.

Awareness display

Retargeting

Email reminder

Cart abandonment

Early touches lose weight over time.

Both linear & time‑decay are categorised as ______ models.

Econometric

Incrementality

Rule‑based

Data‑driven

They rely on predefined formulas rather than statistical learning.

Exponential time‑decay weight formula uses e^(‑λt), where t denotes ______.

Device ID

Cookie age

Ad spend

Time gap from conversion

Decay is a function of elapsed time.

Under position‑based 40‑20‑40, the middle 20 % credit is divided ______ among intermediate touches.

Linearly

Last‑only

Exponentially

First‑only

Each middle interaction receives equal slice, i.e., linear within the middle segment.

Switching from linear to time‑decay often raises ROAS for ______ campaigns.

Retargeting / remarketing

Prospecting display

CTV

Radio

Late‑funnel touches gain weight under decay.

The Google Ads 'Model comparison' report can show CPA impact when switching from linear to time‑decay over the last ______ days.

7

1

365

30

Default lookback for comparison is 30 days, adjustable by user.

Starter

Review the basics and retry.

Solid

Good job—polish the nuances for mastery.

Expert!

Excellent understanding.

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