Attribution

Lifesight is primarily focused on incrementality-based marketing measurement. Attribution is the process of assigning credit to historical, trackable touchpoints in the customer journey.

Attribution is, by its nature, correlational and partial — it is limited by what is trackable, and it requires access to consented customer journeys. This section explains how Lifesight approaches attribution and how it fits within our broader, incrementality-first measurement philosophy.

Before getting into the methodologies, it's worth explaining why attribution is needed in the first place.

The Need for Attribution

Marketing Mix Models (MMM) and Incrementality Testing are episodic and strategic by design. The reads they produce are based on historical data - arriving either at historical averages, or at marginal expectations (i.e., what's expected at different spend levels at a given point in time).

These insights are typically aggregated at the channel or tactic level. For them to be actionable, we need meaningful approaches to extend these strategic reads down to frequent, daily budget recommendations at the campaign and ad set levels.

Neither of these techniques - models and tests - are operational enablers.

In the page on Unified Marketing Measurements , we discussed 3 levels of decisions. MMM and Incrementality tests are not equipped to enable the operational layer. While MMM and Incrementality tests bring a lot of 'scientific' reasoning to the strategic and tactical level of decision making for marketers - it's crucial how they percolate it to day-to-day operations. Incrementality promised by your models and tests depend on you acting on the right set of campaigns, ad sets and creatives. This is ensured by Attribution (especially causal attribution as we will see in the upcoming sections)

Attribution helps bridge this actionability gap. Connecting high-level incrementality reads to daily budget, bid, and creative decisions.

How Attribution Fits at Lifesight

MMM and Incrementality Testing provide the strategic, incremental "ground truth" — periodic and aggregated. Attribution provides the granular, near-real-time signal — daily, and at the campaign/ad set/ad level — but is correlational and limited to what can be tracked.

Causal Attribution combines the two, calibrating granular attribution signals against incrementality factors derived from MMM or experiments, so that tactical, day-to-day decisions stay anchored to true incremental impact.

Dive into various attribution techniques at Lifesight

Causal Attribution
Single-Touch Attribution
Multi-Touch Attribution
View Through Attribution
Algorithmic Attribution