# Hollowquay

*/Startups/Hollowquay*

## Startup Overview

This data aggregation engine ingests and normalizes fragmented reporting metrics across ad platforms. Performance marketing teams and data engineers use the system to consolidate disparate campaign data into a unified, query-ready format. Instead of battling platform-specific quirks, engineers map metrics from varied ad networks directly into their central data warehouses.

Legacy connectors like Supermetrics and Funnel.io force teams into predefined data models, while manual CSV exports consume hours of analyst time. This architecture delivers a strictly API-native and fully schema-agnostic pipeline. By bypassing rigid dashboard builders entirely, the system ensures data teams retain total control over how they model and transform their ad spend.

The engine pulls raw metrics dynamically from source APIs without imposing proprietary schemas. Teams feed this normalized performance data directly into downstream business intelligence workflows or custom bidding algorithms.

## Startup Founding Hypothesis

**Approach**: that ingests and normalizes fragmented ad-platform reporting metrics
**Competitors**:
- [Supermetrics](/Competitors/Supermetrics)
- [Funnel.io](/Competitors/Funnel.io)
- [manual CSV exports](/Competitors/manual_CSV_exports)
**Differentiator2x2**: strictly API-native and fully schema-agnostic, bypassing rigid dashboard builders entirely

## Startup Solution Coordinate

**Solution**: [Campaign Data Gateway](/Software/Campaign_Data_Gateway)

## Startup Position2x2

```mermaid
quadrantChart
    title Hollowquay Positioning
    x-axis Dashboard-Centric --> API-Native
    y-axis Rigid Schema --> Schema-Agnostic
    quadrant-1 Programmable & Flexible
    quadrant-2 Manual but Flexible
    quadrant-3 Out-of-the-Box Rigid
    quadrant-4 Developer Strict
    Supermetrics: [0.35, 0.25]
    Funnel.io: [0.20, 0.40]
    Manual CSV Exports: [0.10, 0.85]
    Hollowquay: [0.90, 0.90]
```

## Startup Offer

**Proof**:
- Targeting performance marketing agencies aiming to eliminate 100% of manual CSV formatting.
- Designed for data engineering teams seeking to reduce ingestion pipeline maintenance by 40 hours per month.
- Built to process millions of cross-platform ad spend rows daily with zero dashboard-rendering overhead.
**Tiers**:
- Name: Developer Meter · Price: ~$0.01–$0.03 per 1,000 normalized rows · Inclusions: Access to standard ad-platform connectors (Meta, Google, LinkedIn), schema-agnostic JSON outputs, and up to 5M normalized rows per month.
- Name: Agency Volume · Price: ~$200–$400/mo base + ~$0.005 per 1,000 rows · Inclusions: Unlimited platform connectors, custom schema mapping endpoints, priority API rate limits, and support for unlimited downstream client accounts.
- Name: Enterprise Pipeline · Price: Custom: ~$15k–$25k/yr · Inclusions: Dedicated ingestion infrastructure, intended VPC peering, SLA on normalization latency, and custom metric-calculation mappings.
**Guarantee**: If the API fails to normalize supported ad-platform metrics into your defined target schema with 99.9% uptime, you receive a full credit for that month's ingestion usage.
**Business Function**: ProvideService
**Objection Handlers**:
- Objection: 'We already use Supermetrics for our reports.' Rebuttal: Hollowquay feeds your data warehouse directly via API without forcing you into rigid spreadsheet templates or dashboard widgets.
- Objection: 'What if an ad platform changes its API?' Rebuttal: Hollowquay is designed to absorb upstream endpoint changes automatically, maintaining your target schema without breaking downstream queries.
- Objection: 'Our schema is highly customized for internal attribution.' Rebuttal: The system is entirely schema-agnostic, mapping raw platform metrics directly to your proprietary definitions rather than enforcing a standard model.
- Objection: 'Is this secure for client data?' Rebuttal: We operate strictly as a pass-through ingestion layer; we normalize in memory and do not permanently store your proprietary ad performance data.
**Pricing Architecture**: UsageMeter
**Agent Checkout Support**:
- agentic-commerce-protocol

## Startup Brand

**Voice**: Developer-focused and precise, favoring raw data mechanics over marketing abstraction.
**Tagline**: Unified ad platform data delivered as clean API payloads.
**Icon Concept**: receipt
**Palette Intent**: electric-signal
**Visual Identity**: A dark-mode aesthetic dominated by terminal black and neon green accents, using monospaced typography to reflect the raw JSON payloads it processes.
**Archetype Reference**: the-sage

## Startup Buyer Chain

**Chain**: Hollowquay → Data Engineering → Growth Marketing
**Gtm Motion**: Acquires technical buyers through self-serve API documentation and free-tier access for single-source ingestion. Expands account value based on the volume of rows synced as data teams connect additional ad networks to the central pipeline.
**Agent Channel**: Designed to publish OpenAPI specifications to the LangChain Tool Registry and OpenAI schema directories, allowing autonomous analytics agents to discover and query normalized ad metrics.
**Primary Channel**: Developer communities and technical SEO capturing search intent for headless Supermetrics alternatives or schema-agnostic ad spend extraction APIs.

## Startup Customer Journey

```mermaid
flowchart LR; A[Developer Community] --> B[API Documentation]; B --> C[Free-Tier Ingestion Pipeline]; C --> D[Standard Ad-Platform Connector]; D --> E[Custom Schema Endpoint]; E --> F[Agency Volume Meter]; F --> G[LangChain Tool Registry]
```

## Startup Proof Points

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**Pilot Goals**:
- A 30-day sandbox pilot with an agency data team, aiming to ingest and map 5 million rows from Meta and Google Ads into a custom Snowflake schema with zero mapping errors.
- A two-week parallel-run pilot for an e-commerce brand, intending to prove the API normalizes ad metrics into their custom attribution tables with lower latency than their existing widget-based reporting tool.
**Target Metrics**:
- Target: 100 percent elimination of manual spreadsheet exports for campaign reporting
- Aim: 40 engineering hours per month recovered from broken data pipeline maintenance
- Target: 99.9 percent uptime on schema-mapped data delivery to the warehouse
- Aim: Zero broken downstream queries following a major upstream ad-platform API endpoint update
**Target Case Studies**:
- Target: Mid-sized performance marketing agency replacing manual weekly CSV pulls across 50 client accounts with direct API-to-warehouse ingestion, aiming for zero hours spent on raw data formatting.
- Target: In-house data engineering team at a D2C brand swapping fragile custom-built ad platform ETL scripts for a resilient schema-agnostic API that absorbs upstream API changes automatically.
- Target: Enterprise marketing analytics vendor routing raw cross-platform ad spend into their proprietary attribution models via VPC peering, validating predictable sub-minute latency under high volume.
**Testimonial Targets**:
- Role: Head of Data Engineering. Sentiment to earn: Relief that the team no longer spends sprints updating ingestion scripts every time Meta or Google changes a reporting endpoint.
- Role: VP of Analytics at an Agency. Sentiment to earn: Confidence that millions of rows of client ad spend data land in the warehouse daily, already formatted to their proprietary schema.
- Role: Director of Data Security. Sentiment to earn: Assurance that the in-memory pass-through architecture satisfies strict compliance requirements by not permanently storing client performance data.

## Startup Top Risks

**Risks**:
- Severity: existential · Description: Major ad platforms like Meta or Google permanently revoke or severely rate-limit third-party API access for aggregation tools. · Mitigation Status: unmitigated
- Severity: high · Description: Marketing teams reject the product because they lack the internal data engineering resources required to consume a strictly API-native data feed without a dashboard UI. · Mitigation Status: in-progress
- Severity: moderate · Description: Undocumented schema changes from secondary ad networks break the normalization engine and cause data misalignment in downstream warehouses. · Mitigation Status: in-progress
- Severity: low · Description: Legacy competitors like Supermetrics expose raw API endpoints that adequately replicate the schema-agnostic data delivery model. · Mitigation Status: unmitigated

## Startup Competitors

- [Supermetrics](/Competitors/Supermetrics) — Incumbent
- [Funnel.io](/Competitors/Funnel.io) — Incumbent
- [Manual CSV Exports](/Competitors/Manual_CSV_Exports) — Status Quo
- [Fivetran Connectors](/Competitors/Fivetran_Connectors) — Data Pipeline
- [Improvado Platform](/Competitors/Improvado_Platform) — Marketing Data Platform

## Startup Story Brand

**Hero**:
- **Need**: to be the architect of proprietary attribution models, not a pipeline repair technician
- **Want**: to feed clean, cross-platform ad metrics directly into a private data warehouse
- **Identity**: the data engineer at a performance marketing agency
**Plan**:
- Step: Define schema · Detail: Specify your target JSON structure for cross-platform spend and conversion metrics.
- Step: Review payloads · Detail: Validate normalized data streams from Meta and Google Ads through our testing endpoint.
- Step: Scale ingestion · Detail: Stream millions of rows per month directly into your warehouse with zero dashboard overhead.
**Guide**:
- **Empathy**: Billion-dollar campaign decisions are won in milliseconds — but broken Funnel.io mappings and upstream API changes leave your analysts staring at empty tables.
**Problem**:
- **Villain**: rigid dashboard connectors
- **External**: Maintaining custom pipelines across Meta, Google, and LinkedIn requires forty hours of manual CSV formatting and API endpoint patching every month.
- **Internal**: You feel like you are babysitting brittle scripts instead of building actual data products.
- **Philosophical**: Why should a data engineer accept locked-in spreadsheet templates when raw metrics belong in a clean, queryable schema?
**Success**: Your data warehouse receives unified, normalized ad metrics automatically, allowing you to build custom dashboards without ever touching a CSV export.
**One Liner**: Every month, performance agencies lose weeks to broken API connectors. Hollowquay delivers unified ad platform data as clean API payloads so you can focus on analysis instead of pipeline repair.
**Positioning**:
- **So That**: ingest normalized cross-platform metrics without rigid spreadsheet templates
- **Unlike**: Supermetrics or manual CSV exports
- **For Whom**: performance marketing agency data engineers
- **Category**: API-native ad data ingestion
**Call To Action**:
- **Direct**: Fetch API key
- **Transitional**: View JSON schema
**Failure Stakes**:
- Forty hours lost to maintenance monthly
- Stale data in client reports
- Broken downstream attribution queries
**Transformation**:
- **To**: one of the few data engineers who owns their entire marketing stack
- **From**: a script-fixer trapped in Supermetrics templates
**Controlling Idea**: Ad platform data should be an API-native utility, not a dashboard-locked product.

## Startup Token Hero

**Genre**: founding-hypothesis
**Rendered**: Every month, performance agencies lose weeks to broken API connectors. Hollowquay delivers unified ad platform data as clean API payloads so you can focus on analysis instead of pipeline repair.
**Mechanism**: spine-derived-v1
**Template Id**: spine-founding-hypothesis
**Vocab Fingerprint**: 050b165133e0b061

## Startup Token Positioning

**Genre**: moore-positioning
**Rendered**: API-native ad data ingestion for performance marketing agency data engineers. Unlike Supermetrics or manual CSV exports — ingest normalized cross-platform metrics without rigid spreadsheet templates.
**Mechanism**: spine-derived-v1
**Template Id**: spine-moore-positioning
**Vocab Fingerprint**: 338d3b19583bdab9

## Startup Token Pitch Deck

**Genre**: pitch-deck
**Rendered**: Problem: Maintaining custom pipelines across Meta, Google, and LinkedIn requires forty hours of manual CSV formatting and API endpoint patching every month.
Solution: Every month, performance agencies lose weeks to broken API connectors. Hollowquay delivers unified ad platform data as clean API payloads so you can focus on analysis instead of pipeline repair.
Customer: performance marketing agency data engineers
Unlike: Supermetrics or manual CSV exports
**Mechanism**: spine-derived-v1
**Template Id**: spine-pitch-deck
**Vocab Fingerprint**: f458ffc872a6b043

## Startup Token M E D D P I C C

**Pain**: Maintaining custom pipelines across Meta, Google, and LinkedIn requires forty hours of manual CSV formatting and API endpoint patching every month.
**Metrics**: Target: Your data warehouse receives unified, normalized ad metrics automatically, allowing you to build custom dashboards without ever touching a CSV export.
**Rendered**: Pain: Maintaining custom pipelines across Meta, Google, and LinkedIn requires forty hours of manual CSV formatting and API endpoint patching every month.
Economic buyer: Data Engineering
Metrics: Target: Your data warehouse receives unified, normalized ad metrics automatically, allowing you to build custom dashboards without ever touching a CSV export.
Competition: Supermetrics or manual CSV exports
**Mechanism**: spine-derived-v1
**Competition**: Supermetrics or manual CSV exports
**Economic Buyer**: Data Engineering
**Vocab Fingerprint**: 7a41f42c8dce662d

## Startup Token Cold Email

**Genre**: cold-email
**Rendered**: Subject: API-native ad data ingestion for performance marketing agency data engineers

performance marketing agency data engineers — Maintaining custom pipelines across Meta, Google, and LinkedIn requires forty hours of manual CSV formatting and API endpoint patching every month. Every month, performance agencies lose weeks to broken API connectors. Hollowquay delivers unified ad platform data as clean API payloads so you can focus on analysis instead of pipeline repair.
**Mechanism**: spine-derived-v1
**Template Id**: spine-cold-email
**Vocab Fingerprint**: 8a9f0aabcdb123a9

## Startup Token Agent Spec

**Genre**: ai-agent-spec
**Rendered**: API-native ad data ingestion. Every month, performance agencies lose weeks to broken API connectors. Hollowquay delivers unified ad platform data as clean API payloads so you can focus on analysis instead of pipeline repair. Serves performance marketing agency data engineers.
**Mechanism**: spine-derived-v1
**Template Id**: spine-ai-agent-spec
**Vocab Fingerprint**: 1026b842f4e3f7ce

## Neighborhood

### Candidate solutions

- [Grower Packout Settlement Disputes](/Problems/Grower_Packout_Settlement_Disputes) — candidate solution for · Problems

### What it offers

- [Yield Prism Ledger](/Software/Yield_Prism_Ledger) — offers · Software
- [Lineage Vault](/Software/Lineage_Vault) — offers · Software
- [Campaign Data Gateway](/Software/Campaign_Data_Gateway) — offers · Software

### Competitors

- [Manual CSV Exports](/Competitors/Manual_CSV_Exports) — competes with · Competitors
- [Supermetrics](/Competitors/Supermetrics) — competes with · Competitors
- [Improvado Platform](/Competitors/Improvado_Platform) — competes with · Competitors
- [Fivetran Connectors](/Competitors/Fivetran_Connectors) — competes with · Competitors
- [Funnel.io](/Competitors/Funnel.io) — competes with · Competitors
- [Manual Spreadsheet Concessions](/Competitors/Manual_Spreadsheet_Concessions) — competes with · Competitors
- [Famous Software](/Competitors/Famous_Software) — competes with · Competitors
- [Produce Pro ERP](/Competitors/Produce_Pro_ERP) — competes with · Competitors
- [Sensitech ColdStream](/Competitors/Sensitech_ColdStream) — competes with · Competitors
- [Spreadsheet Concessions](/Competitors/Spreadsheet_Concessions) — competes with · Competitors
- [Produce Pro](/Competitors/Produce_Pro) — competes with · Competitors
- [manual ledger concessions](/Competitors/manual_ledger_concessions) — competes with · Competitors
- [Manual Spreadsheets](/Competitors/Manual_Spreadsheets) — competes with · Competitors
- [Spreadsheet Ledger Concessions](/Competitors/Spreadsheet_Ledger_Concessions) — competes with · Competitors

### Embodies

- [Software](/Theses/Software) — embodies · Theses

### Who it serves

- [Agricultural Cold Storage Operators](/CompanyTypes/Agricultural_Cold_Storage_Operators) — serves · CompanyTypes

### Composed of

- [Cull Attribution Agent](/Agents/Cull_Attribution_Agent) — composes · Agents
- [Lineage Audit Agent](/Agents/Lineage_Audit_Agent) — composes · Agents
- [Conveyor Vision Engine](/Software/Conveyor_Vision_Engine) — composes · Software
- [Packout Arbitration Service](/Services/Packout_Arbitration_Service) — composes · Services
- [Harvest Lot API](/Software/Harvest_Lot_API) — composes · Software
- [Grower Settlement Service](/Services/Grower_Settlement_Service) — composes · Services
- [Packout Ledger API](/Software/Packout_Ledger_API) — composes · Software
- [Settlement Arbitration Service](/Services/Settlement_Arbitration_Service) — composes · Services
- [Cull Allocation Agent](/Agents/Cull_Allocation_Agent) — composes · Agents
- [Lot Lineage Worker](/Agents/Lot_Lineage_Worker) — composes · Agents

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