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    Case Study: Faster Campaign Execution with Maya AI

    A high-level case study showing how a lean B2B team reduced content cycle time and improved funnel progression using Maya AI.

    2 min readFeb 27, 2026

    On this page (7 sections)

    🎯 Quick Answer

    A lean B2B services team used Maya AI to standardize TOFU, MOFU, and BOFU execution. In six weeks, they reduced campaign cycle time and improved handoff quality between marketing and sales.

    🧩 Business Context

    • Team size: 4 people
    • Constraint: limited production capacity
    • Goal: improve conversion consistency without hiring
    • Challenge: fragmented content flow and weak MOFU coverage

    ⚙️ What They Changed

    1. Adopted one weekly funnel sprint (TOFU + MOFU + BOFU).
    2. Introduced role-based content ownership.
    3. Standardized internal linking across all assets.
    4. Added FAQ and case-style proof content before BOFU asks.

    📊 Outcome Snapshot

    MetricBeforeAfter
    Average campaign setup timeLong, inconsistentSignificantly shorter and repeatable
    Funnel handoff qualityFragmentedStructured and clearer
    BOFU readinessOften delayedConsistent weekly activation path
    Team confidenceReactivePlanned and measurable

    The biggest improvement came from better sequence design, not just faster generation.

    🔍 Why It Worked

    The team shifted from "publish what we can" to "publish what moves users to the next stage."

    💡 Pro tip: Case studies work best when they show process decisions, not just outcomes. Buyers want to know how execution changed.

    They also used clearer page intent:

    • TOFU assets for attraction and discovery.
    • MOFU assets for trust and objection handling.
    • BOFU assets for action and activation.

    ❓ What You Can Reuse

    Keep one weekly sprint format

    A predictable weekly cadence makes quality easier to sustain.

    Build a shared prompt library

    Reuse proven prompts by stage and role.

    Interlink intentionally

    Always connect awareness pages to evaluation and activation resources.

    🚀 What's Next?

    Want to run this model with your team? See how it works.

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