Every dollar gets a role, a signal, and a measurement rule.

Marathon Engine runs paid media as one system: four funnel roles with distinct optimization signals, attribution triangulated into a single operating view, and an evidence-led loop that moves budget as the data changes — not a fixed media plan.

Four funnel roles, each with its own optimization signal.

The stages are separated by the behavior we want to create. Each has a distinct audience state, optimization signal, and accountable read.

01 · Top funnel

Build reach + brand opt-ins

Exclude social engagers, website visitors, and purchasers to reach people who have generally never heard of the brand. Optimize for efficient reach and platform-native actions.

02 · Mid funnel

Develop measurable intent

Exclude website visitors and purchasers. Keep social engagers eligible, then use a platform-side Marathon custom event to move awareness toward consideration — for example, a session returning from branded organic search.

03 · Bottom funnel

Convert new customers

Exclude purchasers and optimize for purchase under incremental attribution. Run demand capture broad, or test separate prospecting and website-visitor retargeting campaigns.

04 · Retention

Grow known customers

Run a distinct purchase campaign for repeat purchase, with no exclusions by default so delivery can concentrate among the highest-intent existing customers — measured under a conservative recognized-value rule.

The purpose is clarity. Budget is assigned to a defined customer state, a behavior to create, and a measurement rule before it moves.

Why the upper funnel exists at all.

Purchase campaigns naturally prioritize people already signaling intent. The upper funnel creates future demand among people the purchase algorithm is unlikely to select today.

Top funnel

Create memory before the category is urgent

Reach people who are not currently in-market at a materially lower cost than the last mile of conversion. The goal is familiarity: when the category becomes relevant, the brand is already mentally available.

  • Earn the first memory among people purchase campaigns are unlikely to reach.
  • Increase the likelihood of a later ad response without depending on it.
  • Create the better outcome: branded organic search or direct traffic from people proactively seeking the brand.
Mid funnel

Turn awareness into observable consideration

Keep social engagers eligible while excluding purchasers and website visitors. A platform-side Marathon custom event can optimize toward a high-value behavior such as a session returning from branded organic search.

  • Move people from awareness into interest or consideration.
  • Create a higher-converting audience that has remembered and actively searched for the brand.
  • Start with the branded-search-return signal; other event optimizations remain later tests, not the default.
A broken mid-funnel makes the behavioral journey more expensive. Without a deliberate next step after awareness, the brand often has to buy another expensive ad click to create the same action.

Funnel roles define what we measure — not a fixed spend mix.

The four roles clarify what each dollar is trying to do. The starting mix is set collaboratively inside approved guardrails; live marginal evidence determines allocation.

01

Top funnel

Net-new reach + brand opt-ins.

02

Mid funnel

High-value intent.

03

Bottom funnel

Incremental new customers.

04

Retention

Incremental repeat purchase.

No universal percentages. Budgets are reviewed on the weekly operating rhythm and moved as the evidence clears as evidence changes.

Triangulating multiple attribution sources into one operating view.

The operating model does not require the team to abandon a trusted source. It makes each source's role explicit, applies an agreed weight or discount, and converts the result into a comparable decision input.

Existing attribution tool

Use the agreed share

Incorporate the attribution view your team already trusts and recognize an agreed portion of its attributed revenue.

Analytics last touch

Weight last-touch evidence

Use last-touch analytics where it adds signal, with a multiplier or discount that reflects what the team knows about the channel and customer journey.

Platform attribution

Recognize by campaign role

Use incremental attribution, standard platform reads, or a conservative recognized-value rule according to the campaign role and the evidence available.

Marathon measurement

Add modeled value

Layer in Marathon Brand Value, cohort and repeat-purchase evidence, or other modeled inputs where they improve the decision without pretending to be the only truth.

No universal source of truth is imposed. The team agrees on which sources to use and what portion of each source to recognize.

Weights are collaborative — and built to evolve.

You bring the historical context. Marathon translates the agreed view into explicit, inspectable weights, multipliers, and discounts.

01 · Calibrate together

Agree on what to recognize

Select the attribution sources and agree on the portion of each source that should count in the operating model.

02 · Configure the model

Make every input explicit

Marathon records the channel, campaign role, source, metric, and agreed weight so the modeled return can be inspected.

03 · Recalibrate

Revise as evidence improves

Model trainers, campaign tests, new-customer growth, and contribution evidence can change how much of each source is recognized.

Initiative → selected sources + weights → modeled return → operator-reviewed allocation. The model is governed by shared judgment and documented inputs.

How we turn the framework into evidence-led allocation.

The funnel defines the jobs. This operating loop defines how we launch, learn, and move capital across those jobs.

01 · Define

Assign the role + weight

Set the customer state, optimization signal, attribution inputs, recognized-value rule, spend guardrail, and decision threshold.

02 · Build

Launch the learning matrix

Rebuild the hierarchy, load Testing and Winners, verify exclusions and event quality, then start the model trainers.

03 · Read

Connect platform + business signals

Read reach, event response, purchases, contribution, brand demand, and new-customer value together — using the agreed measurement model.

04 · Reallocate

Move budget by evidence

Promote winners, cap weak cells, update the creative portfolio, and shift spend in controlled steps with human approval.

Daily paid-media management and the weekly allocation rhythm use the same agreed measurement model.

Start with testing + scaling — then let the business shape the structure.

This is an illustrative initial architecture, not a prewritten account recipe. We begin by protecting learning and proven scale, then add a split only when the brand's economics, catalog, content, promotion plan, or delivery needs make the business read materially better.

Core starting structure

Testing + Winners / Scaling

Testing: protect new concepts, hooks, and formats from being crowded out. Scaling: give proven work stable delivery while the next ideas keep learning separately.

Optional split 01

Business economics

Separate product, category, buyer persona, or usage occasion only when unit economics, LTV, inventory, or performance differ enough to manage independently.

Optional split 02

Higher-SKU / dynamic product ads

Use a separate feed-based cell when a larger catalog and the available creative warrant it; this is an option, not the default for every business.

Optional split 03

Content type

Separate influencer, static, brand-owned video, or organic content when spend concentration, fees, or distinct performance require a clearer read.

Optional split 04

Promotion isolation

Keep promotional media separate while live only when its spend and impact need to remain independently readable.

Optional split 05

Audience, customer state, or delivery control

Add audience, prospect-versus-customer, geographic, or other delivery structure only when it protects signal quality or creates meaningful operating control.

Test options that sharpen allocation decisions.

Where it makes sense, we use focused tests to challenge assumptions and gather additional information about how capital should be allocated.

01 · Initiative spend

Adjust initiative spend

Change the spend behind a campaign or initiative and read the effect on incremental new-customer acquisition and contribution — not only platform-reported efficiency.

02 · Campaign type

Consider alternate signals

Test reach, video-view, or traffic campaign types when the question warrants it. These are experiments around the starting framework, not automatic additions to every account.

03 · Branded search

Estimate marginal incrementality

Increase brand-search spend, read paid and organic brand clicks together, and calculate cost per incremental click so paid clicks are not mistaken for clicks the brand would have earned organically.

From click to return

Translate the click into a return

Compare cost per incremental click with paid-brand revenue per session after a heavy recognized-value reduction — to form a conservative directional marginal-return curve.

Standing question

Revisit when the evidence changes

Brand-search dynamics can change by season, promotion, and competitive pressure. If the evidence changes materially, the question can be tested again rather than treating an old answer as permanent.

Want this system running your media?

If your paid media runs on platform-reported ROAS and a fixed media plan, there's usually contribution on the table. Let's find out how much.