How to Run a Weekly D2C Performance Review That Actually Drives Decisions

The first five minutes belong to accountability, not new data.

Pull up last week's decision log. For each decision made last week:

• What did we decide? ("Scale Campaign A by 20%")
• Did we do it? ("Yes, budget increased Monday")
• What happened? ("CM2 held at 28%, POAS improved to 1.41x")
• What's the next action? ("Scale again by 20%" or "Hold — test new creative before next increase")

This takes five minutes. It ensures your review is a learning system, not a weekly reset. Over time, reviewing last week's decisions is where the most useful strategic pattern recognition happens.

If no decisions were made last week — that's the first thing to address. A review that ends without decisions is a review that wasn't worth having.

Not campaign-level. Business-level. Three numbers only:

1. 1. Shopify net revenue (last 7 days): Is it up, down, or flat vs the prior week? Up vs the same week last year?
2. 2. MER (last 7 days): Are we becoming more or less efficient in aggregate? A declining MER is a macro warning regardless of how individual campaign ROAS looks.
3. 3. New customers acquired: Is new customer volume growing, holding, or declining? Revenue can hold while new customer acquisition stalls — which means the business is recycling its existing audience, not growing.

If all three are healthy — proceed. If any are deteriorating — the rest of the review focuses on diagnosing why.

This is the core of the review. Go through every active campaign with spend above ₹10,000 in the week.

For each campaign, answer three questions:

1. What is the CM2 / POAS?
2. Is the return rate abnormal? If return rate is 1.5x your baseline or higher, flag for brief change. The campaign is reaching the wrong audience or setting the wrong expectation. Scale decisions must be paused until return rate is understood.
3. Is the campaign in Learning Phase? If yes and it's been less than 7 days, no action. Do not touch. If yes and it's been more than 10 days without exiting — diagnose delivery (budget too low? Cost cap too restrictive? Insufficient purchase events?).

CM2 / POAS Decision Matrix:

The output of this block: a clear status for every campaign. Scale / Hold / Diagnose / Kill. Written down, not just discussed.

Creative is the biggest lever in D2C Meta performance. Dedicate real time to it every week.

• Check frequency first: For every active campaign, what is the 7-day frequency on the top-performing creative assets?
  • Above 2.5 for cold audiences → fatigue risk. Plan new creative for next week.
  • Above 4.0 for cold audiences → in fatigue. New creative must launch within 7 days.
• Review the creative queue: What new creative is in production for next week? Every scaling campaign should have fresh creative in the pipeline — if scaling and fatiguing at the same time, performance will collapse within 2–3 weeks.
• Identify one learning from last week's creative tests: Which creative format, hook, or offer performed best this week, and why? Write it down. One learning per week compounds into a significant creative intelligence advantage over 6 months.

Every review ends with a concrete, written plan. Not a list of observations — a list of actions with owners and deadlines.

Aim for 3–5 specific actions per week. More than 5 usually means decisions are being fragmented — consolidate.

Once a month (not every week), use the last five minutes for one structural question about the business model — not campaign tactics:

• "Are we too dependent on Meta? What would happen to our business if Meta CPMs rose 30%?"
• "Our new customer CAC has risen 20% over the last 6 weeks. Is this a campaign problem or a market saturation problem?"
• "We've been running the same campaign structure for 4 months. Should we test a fundamentally different approach?"

These questions don't get answered in five minutes. But they get raised and answered over the following weeks with data, not intuition.