ORAC: Why Your Attribution Model Doesn't Know What Channels Actually Do

Multi-touch attribution assigns credit. But credit assignment alone doesn't tell you what a channel is actually doing in the customer journey. A channel can receive 8% of the credit in a fractional model and be the reason half your customers ever heard of you — or it can receive 8% and be a retargeting pixel showing ads to people who were already going to convert. Those are not the same thing, and treating them as equivalent will produce bad strategic decisions.

ORAC is C3 Metrics' proprietary journey taxonomy. Rather than treating every touchpoint as a simple input to a credit-allocation model, ORAC classifies each touchpoint by the role it played: Originator, Roster, Assist, or Converter. The result is a measurement framework that answers not just "how much credit?" but "what did this channel actually do?"

What ORAC Stands For

Originator — the channel or touchpoint that first introduced the brand to a consumer who ultimately converted. Originators are responsible for creating the relationship. Without them, there is no journey to measure. They tend to be upper-funnel: TV, out-of-home, social awareness campaigns, display prospecting.

Roster — the channels that kept the brand present during the consideration period. A consumer who sees a TV ad, returns to search three weeks later, and converts has had multiple intervening exposures that kept the brand on their mental shortlist. Roster touches often receive minimal credit in standard MTA models because they don't sit at the beginning or end of the path.

Assist — touchpoints that actively advanced the consumer toward conversion. A targeted retargeting ad shown after a product page visit, a comparison-focused display unit, a promotional email — these are Assists. They are distinguishable from Roster touches by their timing and context: they appear during active evaluation, not passive awareness.

Converter — the final touch before conversion. Typically paid search on brand terms, a direct email click, or a return visit from a saved bookmark. Converters often appear to be the most important channel in a last-click or even naïve fractional model — because they're the most visible. They are frequently not the most important.

The Problem With Credit Without Role

Standard MTA approaches — time-decay, linear, even data-driven fractional models — produce a single output: credit percentages. But credit percentages carry an implicit assumption: that all credit is equivalent. A channel that gets 12% of the credit deserves 12% of the budget, regardless of what it was doing.

This assumption fails when the strategic question isn't "how much of this conversion can I attribute to each channel?" but rather "if I cut this channel, what happens to my pipeline twelve weeks from now?" Those are different questions. The second question requires role data, not just credit data.

If paid search on brand terms is a Converter for 40% of conversions, and TV is the Originator for 60% of those journeys, then cutting TV to fund more brand search spend will produce a short-term efficiency gain and a long-term pipeline decline. The brand search credit will look fine for a quarter. Then Originator activity will dry up, and there will be fewer journeys to convert.

Why Paid Search Always Looks Like the Best Channel

In virtually every last-click model, and in most naïve fractional models, paid search on brand terms appears to be the most efficient channel. The CPA is low, the conversion rate is high, the ROI looks excellent.

The reason is structural: brand search is where consumers go when they are already ready to buy. Someone who saw a TV ad six weeks ago, read a review, visited the site twice, and is now searching for your brand name is highly likely to convert. When that person clicks a brand search ad and buys, last-click attributes the conversion to paid search.

ORAC shows what actually happened: the TV ad was the Originator. The site visits were Roster touches. The review was an Assist. The brand search click was the Converter. The conversion credit that belongs to the Converter is real — it facilitated the final step. But it is not the credit that should drive the budget allocation decision. That decision should be informed by the Originator and Assist data, which reveals which channels created and advanced the relationships that are now converting.

What Changes When You Measure With ORAC

The most common change we see when clients adopt ORAC classification: upper-funnel channels get substantially more budget credit than in their previous models. TV, OOH, and display prospecting tend to have high Originator rates — they show up first in converting journeys disproportionately often. When budgets are set using Originator data rather than credit data alone, investment flows toward these channels.

The second common change: retargeting budgets get rationalized. Retargeting often has very high Converter rates — it intercepts consumers who are already on a conversion path and shows an ad at the moment they're ready to buy. This is valuable, but it is not generating demand. ORAC makes this distinction explicit, preventing retargeting from accreting budget that it isn't actually earning in terms of demand generation.