E-commerce Google Ads live or die on margin management: Shopping campaigns, Performance Max, and search must be calibrated against your actual product margins, not average ROAS. QuantForge HQ deploys agents that build Google Ads infrastructure around your margin architecture — protecting high-margin SKUs, suppressing low-margin products, and optimizing LTV cohorts rather than blended ROAS.
PMAX campaigns serve across all Google surfaces including branded search — often cannibalizing traffic you would have gotten at near-zero cost organically. Without brand exclusions and campaign priority controls, PMAX inflates reported ROAS by claiming credit for returning customers.
Standard ROAS targets apply equally to your 70% margin bestseller and your 12% margin clearance item. Agents that optimize against blended ROAS push budget toward high-AOV, low-margin products instead of high-margin, lower-AOV ones.
Google Shopping campaigns are only as good as your product feed. Missing attributes, inconsistent titles, and poor image quality degrade ad relevance, increase CPCs, and prevent your products from appearing for high-intent shopping searches.
Standard campaigns serve ads to existing customers returning to buy again — inflating ROAS with transactions that would have happened organically. True new customer CAC is often 2–3× reported CAC when existing customer transactions are excluded.
Product groups segmented by actual margin. High-margin SKUs get aggressive ROAS targets; low-margin products excluded or managed separately. Bidding strategy optimizes for gross profit, not revenue.
PMAX set up with brand exclusions, asset group segmentation by product category, audience signals from your highest-LTV customer cohorts, and search theme guidance to prevent broad waste.
Agents audit and optimize your feed: title structure (primary keyword + product type + brand), attribute completion, image quality scoring, and price competitiveness vs. Shopping auction benchmarks.
Separate campaigns with customer match suppression for existing buyers. New customer ROAS targets set independently. True acquisition cost calculated against first-order margin, not blended account ROAS.
Dynamic product ads serve exact SKUs abandoned in cart or viewed without purchase. Agents manage bid multipliers by recency tier: 1-day abandoners vs. 30-day window shoppers.
Agents monitor Shopping auction insights weekly — Impression Share, Overlap Rate, and Outranking Share by product category. Budget concentration shifts toward categories where you can outbid competitors on high-margin searches.
| Dimension | QuantForge HQ | Generic PPC Agency |
|---|---|---|
| Bidding Strategy | Margin-weighted ROAS targets by product group | Blended ROAS target across all products |
| PMAX Management | Brand exclusions, audience signals, search theme control | Default PMAX; brand cannibalization unchecked |
| Feed Quality | Agents audit and optimize feed weekly | Feed checked at launch; stale attributes common |
| New vs. Returning | Existing customers suppressed; new CAC tracked separately | All conversions counted equally; true CAC inflated |
| Remarketing | Dynamic SKU ads with recency-tiered bid multipliers | Static remarketing; same bid for all window visitors |
| Reporting | Gross profit ROAS, new customer CAC, LTV by channel | Blended ROAS, CPL, conversion volume |
Map product catalog by margin tier. Audit feed quality: title structure, attribute completeness, image requirements, pricing competitiveness.
Rebuild campaign structure: margin-segmented Shopping, PMAX with proper controls, search for high-intent terms, and remarketing segmented by cart abandonment recency.
Customer match suppression lists built. New customer campaigns launched with independent ROAS targets. Baseline new customer CAC established in first 30 days.
Bid agents optimize hourly by margin tier. Feed agents update product titles and attributes weekly. Auction intelligence agents flag spend shifts by category.
Monthly LTV cohort analysis by channel: which campaigns drive customers with highest 90-day and 180-day repeat purchase rates. Budget allocation follows LTV, not just ROAS.
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