You’re exploring a test edition. No real payments are taken.About this edition ↗
agency chapter
Explore Agency Chapter
Fictional worked example · not client results

Meet Northline Packs.

A made-up commuter-backpack retailer helps us practice a real sequence of decisions. Every Northline business fact and number is invented for teaching. Separate, attributed case-study analyses follow the practice project.
01 · The starting point

A product. A question. Some gaps.

Northline sells commuter backpacks with a laptop compartment and water-resistant outer material. It ships nationally and has a stated returns policy. The owner wants to assess a new advertising channel.

Unknown: contribution per order, verified purchase tracking, and an approved media budget. These gaps prevent a launch recommendation.
02 · The scoped service

Make readiness the first decision.

The assessment delivers one readiness summary, a campaign brief, and a measurement plan. Website development and media costs are excluded. A live pilot is scoped separately after prerequisites are resolved.

Client responsibilities: supply true product facts, own the account, pay media directly, and approve consequential changes.

03 · A planning fee

Explain the assumptions.

Eight delivery hours × $40 internal cost, plus $40 direct costs and $40 contingency, equals $400. At a 20% gross-margin assumption, the planning fee is $500. A separate media budget is not agency revenue.

This is arithmetic using invented assumptions, not a recommended market price.

04 · An inconclusive report

Two purchases do not prove a pattern.

A synthetic report records $200 spend, 100 clicks, and two purchases in a click-based dataset. CPC is $2, purchase conversion rate is 2%, and media CPA is $100. With zero purchases, CPA would be unavailable.

Revenue is not profit. Tracking, attribution, costs, and data maturity still matter.

Read a case study critically

These are publishers’ reported experiences, not Agency Chapter student results or predictions for your business. We have not independently audited the underlying campaign data.

Published case · Stream

Connect a specific problem to a useful next step.

OpenAI’s Stream case study describes ads tailored to developers’ technical questions. It reports roughly 2× return on ad spend in a June 5–August 5, 2026 test with about $10,000 media spend per test group, based on Stream’s internal data.

Our interpretation: make the problem, message, destination, and intended action fit together. For practice, write that chain for one use case and identify the evidence you would need to evaluate it.

Limits: one company’s reported comparison does not establish typical results, causation, beginner feasibility, or profit. Ask how revenue was attributed and which delivery costs were excluded.

Source: OpenAI’s Stream case study ↗

Published September 1, 2026 · Checked September 23, 2026.

Agency account · InterTeam

Define lead quality before celebrating volume.

InterTeam reports more than 150 qualified leads across three clients and describes matching educational resources or demo offers to different stages of buyer research.

Our interpretation: specify what makes a lead qualified before a pilot. For practice, define the criteria, follow-up owner, and later evidence needed to connect an inquiry to a sale.

Limits: this is the agency’s own account. The page does not supply a complete per-client dataset, qualification rules, or closed revenue. It names four verticals while referring to three clients; do not infer four separate case studies. Treat its tactics as hypotheses, not guaranteed targeting controls or performance.

Source: InterTeam’s ChatGPT Ads case study ↗

Checked September 23, 2026. Recheck current platform documentation before applying a tactic.

Optional measurement preferences

Allow first-party counts of page visits and tool actions to help check this test edition. No project text or cross-site advertising tracking. Test activity is excluded from real sales. You can change this at any time.