Case studies

What happened in the room.

Three anonymized accounts where the problem, the approach, and the numbers are on the record. Not hero decks — operating notes, with the threads that moved them.

Recorded outcomes

  • $250K+First-month salesConsumer electronics launch
  • $100K+Second-month salesPet brand new-SKU launch
  • ACoS → TACoSOperating KPIPPC account rebuilt by keyword role
  1. 01Consumer electronics · Amazon US

    Product decisions changed before the listing went live.

    The client wanted a new electronics SKU but lacked conviction on color, spec, and GTM path. We engaged from the product-dev stage — Helium 10 market data, buyer surveys, TikTok + Instagram seeding — and handed Amazon a pre-validated product ready to convert. Month-one sales crossed $250K.

    Signal
    A capable product team and a manufacturing plan, but no conviction on colour, spec, or target buyer — the choices a factory locks for good at the BOM freeze.
    Operating change
    Helium 10 category data plus buyer surveys and interviews fed back into product development; TikTok and Instagram seeding ran 30+ days before go-live; Amazon was built as the conversion layer.
    Recorded outcome
    $250K+First-month sales post-launch
    Read the full case study
    #launch-room
    Week −6 → Day 31
    1. WAYAMZ principalResearch back

      Survey and interviews are in. One colour and the mid spec tier win clearly, and the willingness-to-pay holds. Recommend locking that direction before Friday's BOM freeze.

    2. Client · product lead

      Factory wants the decision by Friday. If we lock it now, are we still on track for seeding?

    3. WAYAMZ principal

      Yes. TikTok and Instagram seeding starts at day −30; the listing and PPC are built to absorb that traffic and convert from day one.

    4. Client · product leadResult

      Month one closed. $250K+. What do we read next?

    5. WAYAMZ principal

      Warm demand did the work. Day 45 we read BSR and review velocity before we decide on the next push.

    Month one, post-launch$250K+
    Exchange reconstructed from the engagement record · names withheld.
  2. 02Pet supplies · US · CA · UK · DE

    Sixty days run as one campaign, not a launch date.

    Amazon's natural review rate sits near 1% — too slow to rank a new pet SKU against entrenched competitors. A coordinated launch + multi-marketplace Vine + ads plan broke the review-conversion-velocity loop inside 60 days.

    Signal
    Amazon's organic review rate sits near 1%; on a new SKU, conversion, rank, and orders were trapped in the same feedback loop.
    Operating change
    Listing, A+, and storefront production-grade before the first paid impression; Vine enrolled on four marketplaces in parallel; PPC calibrated to the launch curve; one principal owning the weekly numbers.
    Recorded outcome
    $100K+Second-month sales post-launch
    Read the full case study
    Launch window · 60 daysNew SKU · one principal across listing, ads, and Vine
    • US
    • CA
    • UK
    • DE
    1. Day 0
      Listing, A+, and storefront production-gradeReady before the first paid impression — no placeholder page.
    2. Day 0
      Vine enrolled on four marketplacesUS · CA · UK · DE in the same window, not months apart.
    3. Days 1–30
      Auto campaigns buy search-term signalMonth one is bought for signal, not efficiency.
    4. Day 31
      Converting terms move to manual SPThe highest-converting terms get tight manual campaigns.
    5. Day 60
      Month two crosses $100K+Review base and conversion reach the range where organic rank compounds.

    ClientReviews are finally moving — do we keep the auto campaigns running?

    WAYAMZMigrate the converting terms to manual SP this week. Autos stay on as research, not as the efficiency line.

    Milestones and exchange reconstructed from the engagement record · names withheld.
  3. 03Multi-category consumer goods · Amazon US

    The constraint was the architecture, not a bid.

    Low PPC order volume wasn't the real problem. The real problem was a fragmented ad account where some campaigns at 10% ACoS were starved for impressions and others at 60% ACoS were wasting spend on undifferentiated head terms. We rebuilt the whole architecture around TACoS.

    Signal
    Campaigns at 10% ACoS had over-negated themselves into no impressions while 60% ACoS head terms consumed most of the daily budget. The account looked busy and wasn't converting.
    Operating change
    Diagnosed by keyword role, not campaign name; head terms isolated into a bounded budget group; years of defensive negatives removed; the operating KPI moved from per-campaign ACoS to account-level TACoS.
    Recorded outcome
    A controllable, scalable architectureBaseline for subsequent quarters
    Read the full case study
    Architecture read · PPC / US / 024Read by keyword role, not by campaign name
    Architecture approved
    Keyword roleBeforeAfter
    Head terms60% ACoS, unbounded budgetOwn group, capped budget, own target
    Low-ACoS campaigns10% ACoS, almost no impressionsOver-negation removed, delivery restored
    Brand defenseShared one account-wide targetIts own ACoS target for its job
    Operating KPIMinimize ACoS per campaignAccount-level TACoS

    ClientCan we just lower the head-term bids?

    WAYAMZThe constraint is the architecture, not a bid. Isolate the budgets by keyword role first, then read TACoS.

    Read and exchange reconstructed from an anonymized client record.
How a record is kept

Signal, intervention, outcome — in the same frame.

Client identities are withheld. Threads shown are reconstructed from engagement notes and labeled as such; figures are anonymized case-study summaries, not guaranteed outcomes.

  1. 01

    The signal

    What the account was telling us before anyone touched it: the number, the constraint, the thing that looked fine and wasn't.

  2. 02

    The intervention

    The owned change set — who did what, in which order, inside which window. Written down before it shipped.

  3. 03

    The recorded outcome

    What moved, by when, and the next read. Figures are anonymized case summaries, never guaranteed results.

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