The Revenue Split Quieting Sales vs Marketing Wars

What’s the difference between sourced vs. influenced revenue?

At a simple level, marketing-sourced revenue is about creation. Influenced revenue is about impact on deals that started somewhere else. When I look at both side by side, I can see how marketing opens new conversations and how it helps move, strengthen, or close deals that are already in motion.

Executive definition
Marketing-sourced revenue is pipeline and closed-won revenue from opportunities that start with a marketing-led first touch.
Influenced revenue is pipeline and revenue from opportunities created by Sales, partners, or outbound that still had meaningful marketing touches that helped move or close the deal.

This debate exists because credit tends to drive budget decisions. Sales wants recognition for outbound effort and relationships. Marketing wants recognition for campaigns, content, events, and other programs. Without clear rules, “sourced vs. influenced” becomes a blame loop instead of a shared view of attribution.

As a leader, I care because definitions here affect forecasting, acquisition costs, and ROI modeling. If sourced numbers are overstated - or influenced rules are so loose that any minor interaction “counts” - my reporting stops reflecting reality. Then I’m making high-stakes decisions on unstable inputs. (For a deeper view of what drives acquisition efficiency, see The economics of B2B CAC: what actually drives it up or down.)

Common misconception
I don’t have to choose between tracking sourced or influenced. In practice, I need both - clearly defined and reported side by side. One shows who opened the door. The other shows who helped get the deal across the line.

Once I treat sourced vs. influenced as created vs. impacted, the rest of the measurement becomes easier to reason about.

Assess my reporting before I change definitions

I can’t fix what I can’t measure. Before I tighten definitions, I need to confirm the data can support the story I want to tell. In practice, that means my CRM has stages that reflect the real sales cycle, an original/first-touch source that’s consistently captured, campaign membership or interaction tracking that’s actually used, and a reliable way to connect closed-won opportunities back to the contacts (and campaigns) that touched them. If you want a structured way to evaluate this, use Assess Your Reporting.

When that plumbing is weak, the symptoms are predictable: the same opportunity appears with different “sources” depending on the report; “Unknown/Other” is common in closed-won; source fields get edited after the fact; or I can’t see meaningful touches after the first form fill.

A simple audit usually clarifies whether I’m ready to argue about attribution at all. I pull the last 90 days of closed-won deals and check three things:

1. Is first-touch data present and believable?
2. Is there at least one marketing touch before opportunity creation?
3. Are there touches during the active sales process before key stage changes or close?

If those checks are often blank or obviously wrong, I fix the plumbing first - and only then revisit sourced vs. influenced rules.

Key differences at a glance

I think of sourced as “who opened the deal” and influenced as “who helped finish the job.” Here’s the side-by-side view I use to keep the concepts straight:

Created vs. impacted is the core idea. Sourced focuses on the moment the opportunity appears in the CRM. Influenced looks across the full timeline before and after that moment.

Marketing sourced revenue

Marketing-sourced revenue sounds simple, but I still need to define it in system terms. Otherwise, every rep and every marketer ends up making their own call.

In practice, I see three workable ways teams define “marketing-sourced.” The problem isn’t picking one - it’s mixing them without realizing it.

First, some teams define sourced as “opportunity created by Marketing” - meaning a marketing user or automation creates the opportunity record from a qualified lead. Second, others use “first known touch driven by Marketing” - the first tracked interaction that led to the opportunity came from a marketing channel (for example, organic search or a content download). Third, some use a conversion-window rule: the lead entered through marketing and converted to opportunity within a set period (often 30-60 days).

I don’t need all three. I pick one, document it, and keep it stable for multiple quarters - because moving goalposts destroys trust in the metric. If I need a reference point for measurement mechanics, I’ll also compare against How to Measure Marketing-Sourced Revenue.

Here’s a quick example using a first-touch rule. A director finds my company through search, reads a comparison guide, returns a few days later and fills out a contact form, and Sales creates an opportunity for a defined amount. Under first-touch attribution, that opportunity is marketing-sourced pipeline, and if it closes, it becomes marketing-sourced revenue.

There are a few classic failure modes I watch for. Self-reported source (“How did you hear about us?”) can be helpful context, but it’s often incomplete. Re-attribution is another: if SDRs or AEs can overwrite source fields to fit internal incentives, sourced reporting becomes a negotiation instead of a record. And if my systems effectively behave like last-touch attribution (for example, overwriting source based on the last click before a form fill), retargeting and branded clicks can steal credit from earlier work that actually created demand.

One more nuance I keep explicit in my reporting: a deal can be both sourced and influenced. “Sourced” is the origin label. “Influenced” is the layer that shows what helped after the origin event.

Influenced revenue

Influenced revenue is about contribution, not creation. It answers a different question: not “who opened this deal?” but “did marketing do something that helped this deal move or close?”

For influenced revenue to be useful (and not a vanity metric), I set criteria that are practical and tied to the sales process. That usually includes: a meaningful marketing touch within a defined window before opportunity creation, touches during the open opportunity that align with stage movement, and engagement from people who plausibly belong to the buying group (not random contacts with no role in the deal). (If buying-group logic is fuzzy in your CRM, this helps: The B2B buying committee explained: roles, risk, and information needs.)

I also define what counts as “meaningful.” Attending a webinar, downloading a case study, revisiting pricing or proof content, or engaging with account-based ads can be meaningful. A single accidental email open usually isn’t. The goal is to avoid treating every micro-touch as equal to high-intent engagement.

A few B2B service examples make the distinction clearer. A prospect might consume multiple pieces of content before an outbound SDR ever books a meeting; that deal is sales-sourced but clearly marketing-influenced. Midway through evaluation, a deep-dive webinar can coincide with an opportunity moving forward; that’s influence I can point to. Late in the cycle, proof assets (pricing, case studies, implementation detail) often reduce perceived risk for finance or legal stakeholders; that’s still influence even though it didn’t “create” the opportunity.

Because many campaigns can touch one deal, double counting at the campaign level is normal. One opportunity may appear in several influenced-revenue views. I’m fine with that as long as I communicate it clearly: influenced reporting is meant to show where marketing showed up and what it touched, not to pretend that each touch independently “generated” 100% of the revenue.

The simplest way I explain it internally is this: sourced reporting answers “who opened the door” using single-touch logic, while influenced reporting uses multi-touch logic to reflect the programs that kept the deal moving.

How I define and report both consistently

The value isn’t in the cleverness of the model - it’s in using the same model consistently. Leaders get tired of metric definitions changing whenever someone dislikes a number.

When I lock sourced vs. influenced down, I make the core choices explicit: what object I’m measuring on (lead/contact/opportunity/account), which timestamps matter (first touch, opportunity created date, stage-change dates, close date), the lookback window I will use, which touch types are eligible, how I dedupe multiple contacts and multiple leads from the same account, and who has authority to change the rules. If you want a longer-form guide for B2B cycles specifically, I’d pair this with Attribution for Long B2B Cycles: A Practical Model for Reality.

I also keep attribution models simple by design. For sourced, first-touch is usually easiest to explain and hardest to game. For influenced, I can use a multi-touch approach (for example, time-decay or a staged model) as long as I’m transparent about what it does and doesn’t mean.

To make this operational, I maintain a one-page reporting spec (often in internal notes alongside the dashboard) that states the sourced rule, the influenced rule, the lookback window, the required fields, the filters (like excluding test records), and the governance process for changes.

Lookback windows deserve special attention. If my sales cycle is long, I avoid a window that’s obviously too short to reflect reality. Whether I choose 90, 180, or 365 days matters less than using the same window consistently so trends are comparable.

30-day reporting sprint

I don’t need a six-month overhaul to get to a workable first version. A focused 30-day sprint can produce a stable baseline if I keep scope tight and prioritize data integrity over perfect attribution.

Week 1 is about auditing recent closed-won deals and agreeing on definitions. Week 2 is about cleaning the core fields (especially original source) and standardizing campaign naming and tracking rules so new data is consistent. Week 3 is about building a minimum viable dashboard and doing QA on real deals to confirm the logic. Week 4 is about an executive readout, capturing decisions in a change log, and committing not to revise definitions midstream. If I need a formal starting point, I’ll use the maturity framework here: Start Assessment Now.

For the first version, I keep the dashboard simple - just enough to answer the essential questions without drowning everyone in nuance:

• Marketing-sourced pipeline and revenue by channel
• Influenced pipeline and revenue by campaign type
• Win rate and sales cycle length for influenced vs. non-influenced deals
• A month-by-month trend showing how sourced and influenced change over time

As long as this core is stable and trusted, I can add layers later.

Created vs. impacted

It helps me to picture sourced and influenced as two lanes on one timeline: one lane for creation and one for impact.

Created (Sourced)
[ First Touch ] -> [ MQL / SAL ] -> [ Opportunity Created ] -> [ Stages ] -> [ Closed-Won ]

Impacted (Influenced)
          ^     ^            ^                ^            ^
      Marketing touches can occur before and after opportunity creation

The sourced story starts at first touch and emphasizes the moment the opportunity is created. That’s when marketing-sourced pipeline is counted.

The influenced story wraps around it. Touches can happen before opportunity creation (during research) and during the open opportunity (right before stage changes, during evaluation, or late in procurement). When I present this to leadership, I label charts clearly so nobody confuses created with impacted. If stage movement is a recurring debate, I’ll often pair this reporting with Pipeline Analytics: Reading Stage Drop-Off Like a Diagnostic.

Operational guardrails

Without guardrails, even good definitions drift. People change roles, processes evolve, and “quick fixes” accumulate.

I keep guardrails simple and enforceable: consistent naming conventions for campaigns, a stable taxonomy for grouping programs, standardized tracking parameters for campaigns, mandatory CRM fields at the moments that matter (especially opportunity creation), and tightly controlled edit rights for original source once the lead reaches a sales-accepted point. I also make sure event and webinar attendance (or similar high-intent actions) is recorded promptly; delayed updates create false negatives in influence reporting.

When a rule does change, I log it - what changed, when it changed, why it changed, and what impact I expect on sourced vs. influenced numbers. That log becomes the reference point when someone challenges a trend.

Accountability mechanics

Reporting only matters if it shapes behavior. I use sourced vs. influenced revenue to align teams, not to encourage credit-hoarding. If I want a shared operating model for this, I’ll reference Revenue Marketing Accountability.

In practice, I treat sourced targets as primarily a marketing accountability metric for pipeline creation quality and efficiency. I treat influenced targets as a shared metric that reflects whether marketing is showing up inside active deals in ways that plausibly help. Outbound-created opportunities fit cleanly into this approach: I label them sales-sourced for origin, while still counting meaningful marketing influence when it exists. That tends to preserve fairness without flattening marketing’s role in deal progression.

I also pair the right KPIs with the right metric. If marketing-sourced pipeline is high but win rate is weak, I likely have a fit or qualification problem - not a reporting problem. If influenced deals consistently move faster or win more often, I can use that insight to invest in what supports late-stage confidence rather than only top-of-funnel volume. (When ROI scrutiny gets CFO-level, this framing helps: Content for the CFO: How to Explain ROI Without Getting Dismissed.)

Exec-ready takeaway
I track sourced to see how marketing fills the funnel. I track influenced to see how marketing accelerates and strengthens deals. When I use shared definitions, protect source fields, and report both views on one scorecard - then keep the rules steady long enough to observe trends - the numbers become useful rather than political.

Finally, I keep one principle front and center: consistency beats perfect attribution. If the organization trusts the definitions, the conversation shifts from “who gets credit?” to “what’s working, what isn’t, and what I should do next.” If I need a lightweight governance body to keep this steady, I’ll borrow the structure behind Revenue Councils.