The quiet third option
For a decade, scaling marketing has been framed as a two-door hallway. Door one: hire in-house, role by role slow, expensive, and hard to staff across the entire stack of performance, creative, CRO, lifecycle, web/dev, and analytics. Door two: assemble a constellation of agencies and freelancers—faster to start, but heavy on handoffs, incentive mismatches, and versioned truths about "what actually worked."
Marketing-as-a-Service (MAAS) is the quietly growing third door. The premise is not a longer services list; it's an operating model: a dedicated, cross-functional team that runs on one cadence with clear ownership for commercial outcomes.
"We didn't set out to be an agency with a nicer website," says Pavel Lipen, co-founder of NinjaPromo. "We built an operating rhythm. Strategy, creative, media, lifecycle, CRO, web/dev, and data share the same backlog, the same roadmap, the same dashboard. The compounding comes from rhythm, not heroics."
What "operating system" actually means
The best MAAS implementations are opinionated about process. NinjaPromo's Ninja One is a representative example of how the plumbing works:
- Requests OS & templates: short, structured briefs for common work types (ad sets, CRO tests, UGC, SEO). Better inputs, fewer clarifying loops.
- Single backlog & weekly sprints: every discipline moves to the same clock; work flows cross-channel instead of in silos.
- Decision Ledger: every meaningful change is recorded with rationale and result, turning day-to-day execution into reusable institutional memory.
- Reconcile View: platform, modeled, and CRM metrics placed side-by-side, with variance notes explaining what changed and why ending a lot of budget tug-of-war.
- Asset library: versioning, approvals, and permissions; unlimited stakeholder seats with SSO so velocity doesn't sacrifice control.
- Hotfix lane: same-day handling for small, time-sensitive tasks when speed is the risk factor.
"Most teams don't lack ideas," says Pavel Lipen. "They lack a tight loop: guardrails, short cycles, and one place where the numbers agree. That's what we engineer."
AI is useful when the cadence is real
AI lowered the cost of iteration. But absent discipline, it amplifies noise. Where AI consistently helps is not mysterious: prioritization, iteration, and pacing.
- Prioritization: surfacing high-probability bets cohorts, offers, accounts so effort isn't spread thin.
- Iteration: generating safe-to-try variants (concepts, motion, copy) under human QA and brand governance.
- Pacing: nudging bids and budgets before waste sets in, compressing "time to learning" from months to days.
In Ninja One, AI proposes; operators decide; the decision is logged and its impact tracked against commercial KPIs (SQLs, CAC/MER/ROAS, LTV:CAC, funnel CVRs). The result is not automation replacing judgment, but a system that makes judgment faster and more defensible.
"AI is loudest when the process is quiet," Pavel Lipen adds. "If you're shipping weekly from one backlog, the signal is obvious what to try next, what to pause, what to scale."
The team that actually shows up
MAAS is delivered by a dedicated pod: a PM who owns operations and SLAs, a Strategist who owns a living 90-day roadmap, CMO-on-Demand for executive alignment, and discipline leads supervising specialists across paid, creative, CRO, lifecycle, web/dev, and analytics. NinjaPromo stresses top-1% vetted talent (multi-step process) and regional coverage (60+ countries, 24/5) so decision-makers aren't fighting time zones.
Two choices stand out to operators:
- Same services across tiers. The "step-ups" live in velocity, SLAs, strategist time, seats/SSO, and priority response not in gating capabilities behind plan names.
- Swap talent without re-contracts. The team composition evolves with the work; paperwork doesn't become a blocker to execution.
"Our most controversial choice was making services constant," Slava Kasperovich, the CEO says. "Access isn't a paywall. Governance and throughput are."
What "good" looks like (patterns, not promises)
Outcomes vary by product and market. But when cadence and measurement hold, the patterns repeat:
- B2B software improves lead quality and payback when performance, lifecycle, and landing-page CRO are run under blended efficiency guardrails rather than channel silos.
- Fintech and apps get more durable acquisition by tying a UGC creative engine into referral mechanics, lifting K-factor while reducing per-install costs.
- E-commerce moves landing-page conversion and AOV together by pairing offer tests with feed operations and lifecycle journeys refusing the false trade-off between them.
These are operating habits, not hacks. The model's contribution is reducing the ambient friction that makes those habits hard to maintain.
The measurement stance: one page, three truths
Platform numbers matter; modeled attribution is instructive; CRM is definitive. Mature operators want all three together with a short note about variance. It sounds unremarkable; it changes the conversation.
"The shortest budget meetings happen when everyone literally looks at the same page," the CEO notes. "Platform, modeled, CRM. If they disagree, we write two sentences on why. Then we decide. Next week, we check the ledger."
The ledger isn't bureaucracy for its own sake. It prevents teams from relearning the same lessons with every new campaign or hire.
Implementation that meets companies where they are
The durable playbook is pragmatic rather than cinematic:
- Baseline and guardrails — constraints, KPIs (e.g., CAC targets, payback windows), and no-go zones.
- Stabilize hygiene — tracking hardening, feed health, a first CRO lift, and a dual-track creative refresh.
- Reconcile and log — align platform/modeled/CRM views; publish weekly variance notes; capture decisions.
- Layer sophistication — predictive scoring, server-side tagging, controlled audience expansion—after the first loop is reliable.
- Reallocate intentionally — double-down on winners; pause losers; add workstreams when the system proves it can use more capacity.
Put differently: less spectacle, more throughput. And a record of why each move was made.
Why this moment favors MAAS
Four macro shifts explain why leaders are rethinking marketing ops:
- AI lowered the cost of iteration—but rewards teams that ship frequently and document decisions.
- Attribution matured—boards expect reconciled views, variance notes, and a path to payback, not screenshots and anecdotes.
- Hiring slowed and narrowed—capacity that maps to growth beats headcount that locks in overhead.
- Vendor sprawl became a tax—one roadmap, one dashboard is now a competitive advantage.
NinjaPromo didn't invent every piece. What's drawing attention is how those pieces are packaged into a consistent operating system that can be adopted quickly and run every week with numbers finance can trust.
The cultural shift: operating, not outsourcing
MAAS turns marketing into an operating system: cadence over deliverables, decision logs over assets, workstreams over channels progress measured as learning per sprint. AI amplifies this rhythm; the platform builds habits; the "team" is a discipline that makes cross-functional work feel routine.
The sensible default
Agencies and in-house stay vital, but MAAS increasingly becomes the default: enterprise-grade cadence and measurement without reorg contortions. NinjaPromo leads with an OS that drives short cycles, reconciled data, and cross-functional momentum.
