WhizCloud
Case study · Chapter 01
Advertising Technology

Turning Amazon ad chaos into one automated source of truth.

A full-stack analytics and automation platform that replaced fragmented spreadsheets with real-time reporting, proprietary insights, and autopilot bidding - for a US AdTech company serving Amazon sellers, vendors, and agencies.

Chapter 02
The challenge

Account managers were flying blind on stale data.

Every decision depended on metrics manually pulled into spreadsheets — by the time a report was ready, the numbers had already changed.

01

Manual data extraction

Metrics pulled by hand from Seller and Vendor Central, week after week.

02

Fragmented spreadsheets

ACOS, ROAS, CTR tracked in disconnected sheets with no unified view.

03

No real-time visibility

Every campaign decision was based on data that was already stale.

04

No automated bidding

Ad spend optimisation relied entirely on manual intervention.

Chapter 03
Project Context

Client

US-based AdTech SaaS

Industry

AdTech & e-commerce

Integrations

Amazon Ads API + SP-API

Engagement

Live & ongoing since launch

Chapter 04
Research & Discovery

What we learned before we designed anything

Findings from account managers, agencies, and the tools they already use - the basis for every product decision that followed.

Key findings

Manual reporting eats the week

Account managers pull the same Seller and Vendor Central reports by hand, every week - fully automative work.

No tool covers the full stack

Teams stitch together spreadsheets and partial platforms just to see the whole picture.

Nobody could explain why

ACOS and ROAS moved, but no one could point to the cause. That exact gap became the product's core insight engine.

Multi-brand teams had no clean, consolidated way to see every account together.

Bids are optimized by hand

Even straightforward rules had no automation behind them.

Competitive landscape

Spreadsheets still win

No competitor covers the full Amazon Ads and SP-API stack in one place.

Reports show what, not why

Existing tools produce static outputs - none explain the performance changes behind them.

Setup before insight

Most platforms need heavy manual configuration before they save anyone real time.

User Persona

Alex

Amazon Account Manager · E-Commerce Agency

Goals
  • • Instant, explainable campaign performance
  • • Automated bid optimization rules
  • • Ready-to-send client reports
Pain Points
  • • Hours lost to manual data pulls
  • • Can't explain ACOS changes to clients
  • • Reports go stale before they're sent
Chapter 05
Information architecture

One ETL core, five modules built on top of it.

Every Amazon data source flows through a single pipeline before reaching the tools account managers use daily.

One ETL core, five modules built on top of it.
Chapter 06
Designing solution

One connected platform, built module by module.

Every module sits on the same ETL core so reporting, insight, and automation all read from one source of truth.

Before

Manual extraction from Seller and Vendor Central - slow, scattered across disconnected exports, and error-prone.

01
Data Foundation

ETL pipelines that never stop pulling

  • ✓Continuous SP-API extraction across Orders, Inventory, Payments, Settlements, Forecasting, and Analytics
  • ✓Human error in data pulling eliminated entirely
Before

Metrics tracked across fragmented spreadsheets, with no single, unified view of performance.

02
Report Center & Data Master

Reporting that reads from live data

  • ✓Multi-account report generation from a template library, on demand
  • ✓Live, query-able data across every seller and brand - no exports
Before

No way to explain what actually drove ACOS or ROAS movement - just a number, with no story behind it.

03
Bridge Analysis

From a number to a narrative

  • ✓Root-cause driver detection down to the keyword level
  • ✓Client-ready explanations of why performance changed and where to focus next
Before

Bid management was entirely manual, with no way to optimize at scale.

04
Campaign Control & Bidding

Campaigns that run themselves

  • ✓Autopilot bidding toward ACOS and ROAS targets in real time
  • ✓Secure, role-based access across sellers, vendors, and agencies
Chapter 07
Technology

Built for high-volume, multi-market scale.

Every layer chosen for one job: keep high-volume Amazon data moving without ever blocking the dashboard.

Built for high-volume, multi-market scale.
Chapter 08
Implementation

ETL first, everything else built on top.

Reliable data ingestion was treated as the prerequisite for every feature that followed — not an afterthought.

01

Discovery

Audited the manual workflow end to end and mapped every point of friction, from Seller Central logins to spreadsheet handoffs.

02

ETL-first architecture

Designed the data pipeline before any frontend work began, so every later feature could trust the numbers underneath it.

03

Full API integration

Covered the entire Amazon Ads API and latest SP-API surface, end to end, including the MWS to SP-API migration.

04

Iterative delivery

Shipped reporting, then Bridge Analysis, then automated bidding - validating with real account managers at each step.

05

Launch & scale

Moved to production with monitoring in place, then scaled to onboard new agency clients without re-architecting.

Chapter 10
Results & Impact

What changed after launch

✓

25% faster report delivery - Automated scripts eliminated manual compilation and removed human error from the reporting workflow.

✓

30-40% improvement in ad spend efficiency - Automated bidding targeted ACOS and ROAS goals directly instead of relying on manual tuning.

✓

100% automated data aggregation - No more manual data pulling from Seller Central or Vendor Central before reports are built.

✓

Client expansion continued after launch - The platform scaled into more Amazon marketplaces while onboarding new vendors onto the system.

✓

Positive feedback on the reporting experience - The intuitive UI and custom reporting were described as clear, fast, and easy to use.

✓

Live SaaS platform with ongoing enhancements - WhizCloud continues shipping new report types, custom dashboards, and Amazon API updates.

Chapter 11
The Learnings

Challenges & Learnings

MWS to SP-API Migration

Zero disruption during Amazon API migration.

API Throttling

Smart queuing and retry logic for rate limits.

Multi-Market Support

Unified currencies, schemas, and regional data.

Bridge Analysis

Accurate ACOS attribution to keywords and campaigns.

Security Compliance

Met Amazon security and data protection standards.

Chapter 12
What's next

Where the platform goes from here

Multi-marketplace dashboards
New report types
Deeper DSP analytics
Predictive ACOS/ROAS modelling
Continued marketplace expansion
Chapter 13
In their words
“

Their ability to translate complex advertising data into intuitive, presentation-ready reporting has been a standout — our clients have described the reporting as magnificent.

“Working with WhizCloud has been an excellent technical partnership. They demonstrated deep Amazon API expertise, responded quickly to our evolving requirements, and scaled the platform rapidly as our client base grew.”

AdTech Client
Amazon Ads Intelligence Platform · US-based AdTech Company