Google Ads Shopping — Optimization Protocol

Product-led optimization: validate feed → classify items → manage structure → scale or cut.

Step 0: Feed Health (BLOCKING — fail = STOP)

Before any optimization, verify:

• ≥ 80% products approved in Merchant Center
• Purchase conversion tracking is active (conversions_value > 0 in data)
• Price and availability are accurate (requires manual verification or Merchant Center check)

If ANY check fails → STOP all optimization. Fix feed first.

Step 1: Data Pull

Query using google_ads_run_gaql:

1. Account AOV: total conversions_value / total conversions from customer resource, LAST_30_DAYS
2. Item-level performance: product_item_id, product_title, product_brand, cost, conversions, conv_value, clicks, impressions from shopping_performance_view. Sort by cost DESC, limit 200. Filter: SHOPPING campaigns.
3. Campaign-level: campaign id/name/status, budget, cost, conversions, conv_value from campaign. Filter: SHOPPING, ENABLED.
4. Search terms: search_term, cost, clicks, conversions from search_term_view. Filter: SHOPPING. Sort by cost DESC, limit 200.
5. Daily budget utilization: campaign id, date, cost from campaign. Filter: SHOPPING, LAST_14_DAYS.

Lookback: 14 days if ≥ 100 purchases/month, otherwise 30 days.

Ask user for target ROAS. Default: historical 30-day ROAS.

Step 2: Item-Level Classification

Sort items by cost (highest first). For each item:

Items not matching any rule: monitor, no action needed.

Step 3: Product Group Structure

• Maximum 3 product groups per campaign
• Split ONLY when economics differ (different margins, price bands, seasonal risk)
• If groups don't have meaningfully different ROAS targets → consolidate

Step 4: Search Term Negatives

Add negatives ONLY for wrong-intent terms:

• Price objection: free, cheap, budget, discount code, coupon
• DIY/repair: diy, repair, fix, how to, tutorial
• Used/second-hand: used, second hand, refurbished, pre-owned
• Products not in feed (compare search terms to product titles)
• Irrelevant attributes (colors/sizes not offered)

Do NOT negate high-intent commercial terms even if they haven't converted yet.

Step 5: Budget & Bid Decisions

SCALE (increase budget 10–20%)

ALL must be true:

• Campaign ROAS ≥ target
• Budget utilization ≥ 90% on 10+ of last 14 days
• Top 20% of SKUs by conversions account for ≥ 60% of spend (winners getting the budget)

CUT/CAP (reduce budget or exclude SKUs)

ANY true:

• Campaign ROAS < target
• SKUs with ROAS < 0.7× target receiving increasing spend share WoW

→ Reduce budget OR exclude underperforming SKUs first, then reassess.

Step 6: Device & Location (last)

Only analyze if segment spend ≥ 2× AOV (enough data to judge).

• Exclude device/location ONLY if ROAS ≤ 0.6× account average AND no operational explanation (e.g., mobile site is broken)
• Check for technical issues before excluding (site speed, checkout flow)

Step 7: Campaign Kill Conditions

Pause the Shopping campaign if:

• ROAS < 0.6× target after total spend ≥ 2× AOV
• Shopping ROAS consistently worse than Search ROAS over 30+ days

Prohibitions

• Never optimize by CTR alone (Shopping is ROAS-driven)
• Never let cheap, low-converting SKUs dominate spend
• Never scale without confirming winners are getting the budget

Output must include: item classification summary (KILL/DOWNGRADE/PROMOTE counts + savings), search term negatives, budget recommendation with rationale, expected 7-day ROAS impact.