Pick and Adapt Your Automation

You've been through five courses of real technique — campaign automation sequences, lead scoring and routing, content and social pipelines, KPI rollups, and A/B testing — each one ending in a real, written deliverable. This capstone has one job: make sure at least one of those deliverables actually leaves the doc and starts running against your organization's real tool and real data. A course full of exercises that never touch production doesn't change how you do your job. One shipped automation does.

Your task: pick exactly one of the five, and adapt it to your own org's actual setup.

• A drip/nurture sequence (from Campaign Automation Basics) — take your written trigger → condition → action spec and build it in whatever ESP or CRM your organization actually uses, translating your generic design into that platform's specific trigger, condition, delay, and exit settings.
• A lead scoring and routing script (from Lead Scoring & Routing) — take your filled-in scoring skeleton and either configure it as native workflow rules in your CRM, or stand it up as a real script against your CRM's export or API.
• A content calendar and platform-variant pipeline (from Content & Social Automation) — take your QC'd pipeline and actually run it for a full real month, scheduling the output into your real content tools.
• A KPI rollup (from KPI Dashboards for Marketing) — take your rollup structure and turn it into something that actually refreshes on a real cadence, from your organization's real ad and CRM exports, not a one-time manual pull.
• An A/B test (from A/B Testing with AI) — take a test you designed and actually launch it against real traffic, with your tracking template committed to before you look at results.

Why "pick one" instead of "review all five": shipping one real thing, adapted to your actual constraints, teaches you something no amount of exercise work can — every organization's tools, data quality, and approval process have quirks that only show up when you try to make something real work, not when you're drafting a spec in a doc. A scoring script that looked clean on paper might hit a CRM field that doesn't actually track what you assumed. A sequence spec might need a step your platform's automation layer handles differently than the generic pattern described. That friction is the actual learning.

How to adapt it, concretely:

1. Pull up your written deliverable from whichever course you're choosing, and your organization's actual tool.
2. Map every generic step to a real, specific setting, field, or export in that tool — not a hypothetical, the one you'll actually click or run.
3. Note every place the real tool forces a decision your generic spec didn't cover — a required field, a platform-specific limit, a data source you assumed existed but doesn't. Resolve each one deliberately, not by accident.
4. Get whatever real data you'll need — real leads, real customer lists, real campaign exports — rather than testing on placeholder data that won't reveal real problems.

▶️ Try this

Choose one automation from the five options above, right now, based on what would actually move your real work forward. Pull up your written deliverable from that course and your organization's actual tool side by side, and map at least the first three steps of your spec to specific, real settings or fields in that tool.