E-commerce HALAL | 250 M€ générés sur Google Ads | Hijra

Business execution summary (e-commerce + Google Ads)

1) Google Ads vs Meta: which lever to start with

• Google Ads is the “main engine” for many large spenders: major companies invest far more in Google than Meta, implying most ad-driven cash generation comes from Google.
• Not a “war” between platforms: success depends on the product and where it performs best in the funnel:
  • Google is typically more bottom-of-funnel / demand capture
  • Meta is often more upper-funnel / discovery
• Beginner guidance
  • Google may be easier operationally: fewer creative/design cycles compared to Meta.
  • Once Google finds product-market fit via ads, results can become more stable over time (while Meta can face faster fatigue and more account/creative churn).

2) Scale/ROI claims + what “works” in campaigns

• Key performance story
  • Early experience claimed: ~€10–15M investment to generate ~€250M revenue for clients (not “in his pocket”).
• Observed ROI levels (directional)
  • ROIs ~10 were “easily achievable” in earlier Google Ads times due to more keyword/search-term control.
  • More recently, he reports testing Demand Gen vs Shopping:
    • Demand Gen ROI: ~6
    • Shopping ROI: ~3
• Campaign types for e-commerce beginners
  • Shopping (standard / essential baseline)
  • Demand Gen (positioned as more mid-funnel than pure bottom-funnel tools like PMax; heavily distributed on YouTube)
  • PMax remains valuable, but he stresses account/feed segmentation matters more than “Feed-only vs full PMax” mechanics.

3) PMax / Demand Gen / Shopping playbooks (how to structure and test)

Framework: “bottom-of-funnel vs mid-funnel” mapping

• Google tooling positioning:
  • PMax / “similar” = bottom-of-funnel (even if it broadcasts broadly)
  • Demand Gen = mid-funnel (meant to help “feed” the overall funnel)

Actionable testing advice

• Demand Gen
  • Testing is ongoing (reported as ~2 months).
  • Creative matters more than “stats”; he warns that statistics alone won’t transfer—the video format requirement is central.
  • Structure testing by formats, then prune locations that don’t perform.
• PMax feed-only vs full PMax
  • No universal rule; it depends on the account.
  • Accounts react differently: “only the data is right.”
  • Most important lever: how PMax is segmented (segmentation impacts outcomes more than feed-only vs classic).

4) Google Ads account structure for beginners (single product & multi-audience)

Account segmentation principle

• For a single product, build for multiple audiences inside the same product:
  • Some audiences can perform at ROI ~1–2
  • Others at ROI 3–7+

Brand protection

• Run brand campaigns focused on:
  • Max conversions
  • and impression rate
  • Otherwise CPC can rise and bidding can become inefficient.

Audience layers he recommends

• Power of the audience
  • Use in-market audiences
  • plus retargeting audiences (he calls retargeting especially sensitive/relevant for PMax settings)
• Example logic: retargeted users may be willing to pay higher bids because they’ve already seen/engaged with the site (example given: “sofa”; retargeted conversion probability increases → higher bid acceptable).

5) Troubleshooting bans and account integrity (operational risk playbook)

Ban prevention playbook

• If banned:
  • Don’t recreate accounts to “work around” controls.
  • Instead: identify the root cause and fix it with Google.
• He claims account “multiplying” can lead to permanent lock, including:
  • IP blocking
  • banning associated with mailbox/address/name reuse.

Why bans happen (consistency checks)

• Ensure consistency across:
  • website commercial name vs legal name used in account settings (example given).
• Be as transparent as possible.
• Validation requirements are increasing:
  • more advertiser verification steps (identity/validation) becoming mandatory over time.

6) Measurement & micro-conversions (debugging the funnel)

Framework: diagnose where users drop

• Common mistake: setting purchase tag only.
• Add micro-conversions to localize issues:

1. Clicks → no site visit
   • e.g., ~100 clicks but only ~50 site visits → likely poor traffic quality or site speed issues.
2. Product page views → no add-to-cart
   • likely a product or product page UX/content issue.
3. Add-to-cart → drop at delivery/checkout
   • likely checkout/delivery friction.

7) Search network growth & impression rate fatigue

Framework: manage impression rate and keyword expansion

• He describes “fatigue” for Google Search as:
  • If impression rate reaches ~70–80%, treat it as near saturation.
  • Brand can reach ~90–95% without the same problem.
• When saturated:
  • expand to new keywords/audiences
  • avoid overly narrow specificity that blocks discovery of new searches.

Tools mentioned for broadening semantics

• DSA: automated targeting to find relevant new semantics (noting Google changes/transition away from it).
• “IMAX”: a successor feature that casts a wider net, surfacing incremental keywords
  • initial waste is expected, but cleaning improves performance.

8) Incremental expansion channels: Bing and geo-market logic

• Bing Ads is recommended when you hit limits on Google Search impression share/reach.
  • He says it’s relatively easy to copy/import Google campaigns to Bing.
• Market logic (high level):
  • Bing share can be meaningful in certain geographies (example: US volume/age demographics).

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Entrepreneurship mindset (business-relevant takeaways)

“Structured experimentation” as the growth path to expertise

• He argues you don’t become “expert” by toggling settings randomly.
• Core process
  • be curious → test features on multiple accounts → read data each time
  • analyze where it works/doesn’t and why → incrementally “crack the algorithm”

“Why → utility” logic

• Persistence comes from a strong “why”:
  • keep motivation tied to being useful, especially to family/long-term goals.
• Practical version:
  • do the work to find a good product, present it well, improve service → sales follow.

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Concrete recommendations checklist (actionable)

• Start e-commerce with Shopping as a baseline; test Demand Gen for mid-funnel acceleration.
• Build account structure around:
  • PMax/PMax-like segmentation by audience
  • brand campaigns with conversion + impression rate focus
  • in-market + retargeting audiences (retargeting emphasized)
• Always implement micro-conversions to diagnose funnel breakpoints:
  • traffic quality, site speed, PDP issues, and checkout/delivery issues.
• Avoid ban workarounds:
  • identify root cause, correct transparency/consistency, and don’t recreate accounts.
• When Search impression rate saturates (~70–80%):
  • expand semantics/keywords with automated/broadening features to discover new search queries.
• If scaling stalls:
  • test Bing and replicate Google learnings (import/copy approach).

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Key metrics / targets referenced

Financial outcomes (claimed)

• ~€250M revenue from ~€10–15M investment (historical client case)

ROI benchmarks mentioned

• Google historical ROI: ~10 achievable
• Demand Gen ROI: ~6
• Shopping ROI: ~3
• PMax audience ROI spread: ~1–2 to 3–7+ across different audiences

Saturation thresholds

• Search impression rate saturation: ~70–80%
• Brand can reach: ~90–95%

Time to recover from issues

• Google review/ban resolution claimed: ~20 days minimum (context: waiting for responses)

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Presenters / sources

• Mounib (speaker; Google Ads background; main technical/e-commerce/ads guidance)
• Host / podcast interviewer (unnamed in subtitles; opens and guides the discussion)