# Cresci

*/Startups/Cresci*

## Startup Overview

This data pipeline maps unstructured campaign logs into deterministic attribution graphs. It ingests raw export files from ad networks, email servers, and affiliate channels, translating messy event streams into a unified ledger of marketing touches. Growth and analytics teams use this continuous map to track the exact interaction sequences that drive specific conversions.

Data engineers and marketing operations teams routinely burn weeks writing manual SQL queries to untangle disparate tracking formats. Campaign logs arrive with conflicting timestamps, nested JSON structures, and fragmented session IDs. This engine removes the extraction and transformation burden entirely by parsing the raw logs directly and outputting a clean relational model of user journeys.

Legacy extraction tools like Supermetrics and Funnel.io require teams to manually map fields before data flows, locking organizations into rigid subscription tiers based on arbitrary connector counts. This platform operates with zero-configuration by default, automatically identifying schema changes and plotting new event types into the attribution graph immediately. Billing is strictly priced on processed events, aligning costs directly with the actual volume of ingested campaign data.

## Startup Founding Hypothesis

**Approach**: that maps unstructured campaign logs into deterministic attribution graphs
**Competitors**:
- [Supermetrics](/Competitors/Supermetrics)
- [Funnel.io](/Competitors/Funnel.io)
- [manual SQL queries](/Competitors/manual_SQL_queries)
**Differentiator2x2**: zero-configuration by default and strictly priced on processed events

## Startup Solution Coordinate

**Solution**: [Attribution Graph Engine](/Software/Attribution_Graph_Engine)

## Startup Position2x2

```mermaid
quadrantChart
  title Startup Position: Cresci vs Competitors
  x-axis High Configuration Required --> Zero-Configuration Default
  y-axis Rigid Tiered Pricing --> Strict Event-Based Pricing
  quadrant-1 Usage-Billed Turnkey
  quadrant-2 Usage-Billed Custom
  quadrant-3 Legacy Subscriptions
  quadrant-4 Fixed-Cost Turnkey
  Supermetrics: [0.25, 0.30]
  Funnel.io: [0.40, 0.45]
  manual SQL queries: [0.05, 0.10]
  Cresci: [0.90, 0.85]
```

## Startup Offer

**Proof**:
- Targeting mid-market e-commerce brands aiming to eliminate manual SQL attribution queries.
- Intended for B2B SaaS growth teams seeking to map complex multi-touch lead journeys across 5+ ad networks.
- Designed for performance agencies managing over $100k/mo in ad spend to output automated client ROI graphs.
**Tiers**:
- Name: Base Volume · Price: ~$0.30–$0.50 per 1,000 mapped events · Inclusions: Up to 500k unstructured campaign log events per month, intended standard ad network connectors (Facebook, Google Ads), daily attribution graph compilation.
- Name: Scale Volume · Price: ~$0.10–$0.25 per 1,000 mapped events · Inclusions: Volume between 500k and 5M events per month, intended CRM connectors (Salesforce, HubSpot), hourly attribution graph compilation.
- Name: Custom Volume · Price: ~$0.02–$0.08 per 1,000 mapped events · Inclusions: Volume over 5M events per month, raw SQL graph export, intended custom webhook sinks, 5-minute graph compilation.
**Guarantee**: Cresci guarantees a minimum 95% deterministic match rate for properly formatted UTM parameters against known records; if monthly match rates fall below this threshold, unmapped events are automatically refunded to your usage balance.
**Business Function**: ProvideService
**Objection Handlers**:
- Objection: Unstructured logs are too messy for zero-configuration mapping. Rebuttal: Cresci relies on a strict parsing engine designed to normalize standard tracking parameters, even when appended out-of-order or deeply nested.
- Objection: This will overwrite our existing data warehouse schemas. Rebuttal: The deterministic attribution graph generates as a standalone output table, leaving your raw ingested data and existing schemas completely untouched.
- Objection: Usage-based pricing gets expensive during bot traffic spikes. Rebuttal: We strictly meter based on *processed and matched* campaign events, meaning untracked bot traffic or empty site visits do not inflate your bill.
**Pricing Architecture**: UsageMeter
**Agent Checkout Support**:
- agentic-commerce-protocol

## Startup Brand

**Voice**: Analytical and precise, focusing entirely on data provenance and mathematical certainty.
**Tagline**: Map unstructured campaign logs to exact revenue attribution.
**Icon Concept**: receipt
**Palette Intent**: institutional-cool
**Visual Identity**: Deep slate backgrounds and crisp white typography emphasize structural clarity, utilizing tight table layouts that mirror exact attribution records.
**Archetype Reference**: the-sage

## Startup Buyer Chain

**Chain**: Cresci → Marketing Operations → Growth Marketing Team
**Gtm Motion**: Acquires initial users through a self-serve, zero-configuration sandbox where marketing ops teams test the mapping engine on a single unstructured campaign log. Expands revenue directly tied to usage as the team pipes in additional ad networks and scales the total volume of processed events.
**Agent Channel**: Designed to list in the LangChain Tools registry and OpenAI GPT Store as a structured attribution endpoint, allowing autonomous data-analyst agents to query deterministic campaign ROI data without writing custom SQL.
**Primary Channel**: Technical SEO targeting highly specific data-engineering search queries like 'map TikTok Ads unstructured UTMs to BigQuery SQL', routing searchers to playable documentation.

## Startup Customer Journey

```mermaid
flowchart LR; A[Technical Search Query] --> B[Playable Documentation]; B --> C[Campaign Log Sandbox]; C --> D[Ad Network Connector]; D --> E[Attribution Graph]; E --> F[CRM Connector]; F --> G[Agent Registry];
```

## Startup Proof Points

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

**Pilot Goals**:
- 30-day historical log ingestion test: Process up to 500k unstructured campaign events from a previous month to validate the 95% deterministic match rate guarantee against known CRM records.
- 14-day dual-run live attribution pilot: Execute daily attribution graph compilation alongside the client's manual reporting to prove match parity without disrupting active data warehouse schemas.
**Target Metrics**:
- Target: 95% minimum deterministic match rate for properly formatted UTM parameters against known records.
- Aim: 0 unmapped events billed during untracked bot traffic spikes, metering strictly processed and matched events.
- Target: 5-minute compilation latency for custom-volume graph updates via custom webhook sinks.
**Target Case Studies**:
- Mid-market e-commerce brand: Maps unstructured campaign logs to daily standalone attribution tables, replacing manual SQL query execution.
- B2B SaaS growth team: Compiles complex multi-touch lead journeys across 5+ ad networks and a CRM into a unified, hourly deterministic attribution graph.
- Performance marketing agency managing over $100k/mo ad spend: Outputs automated client ROI graphs natively without overwriting existing client data warehouse schemas.
**Testimonial Targets**:
- VP of Growth at a B2B SaaS company: Confirms the strict parsing engine normalizes deeply nested or out-of-order tracking parameters without requiring data engineering requests.
- Lead Data Engineer at an e-commerce brand: States the generated attribution graph functions as a cleanly formatted standalone output table that leaves raw ingested data untouched.
- Director of Performance Media at an agency: Expresses satisfaction that usage-based pricing exclusively meters processed and matched events rather than inflating bills with empty site visits.

## Startup Top Risks

**Risks**:
- Severity: existential · Description: Ad platforms like Meta and Google deprecate log-level data exports entirely, severing the core unstructured input pipeline. · Mitigation Status: unmitigated
- Severity: high · Description: Zero-configuration mapping fails on ad-hoc taxonomy changes by marketing teams, causing attribution graphs to break silently and destroying customer trust. · Mitigation Status: in-progress
- Severity: moderate · Description: High-volume enterprise customers churn because strict event-based pricing scales higher than flat-rate tiers at established competitors like Supermetrics. · Mitigation Status: unmitigated
- Severity: low · Description: Onboarding stretches out when customers upload deeply corrupted or completely undocumented historical log formats that require manual mapping intervention. · Mitigation Status: in-progress

## Startup Competitors

- [Supermetrics](/Competitors/Supermetrics) — Incumbent Connector
- [Funnel.io](/Competitors/Funnel.io) — Marketing Pipeline
- [manual SQL queries](/Competitors/manual_SQL_queries) — Status Quo
- [Triple Whale](/Competitors/Triple_Whale) — Attribution Platform
- [Improvado](/Competitors/Improvado) — Enterprise Pipeline

## Startup Solution Stack

- [Attribution Graph Service](/Services/Attribution_Graph_Service) — Service-as-Software
- [Unstructured Log Agent](/Agents/Unstructured_Log_Agent) — Agent
- [Campaign Mapping Worker](/Agents/Campaign_Mapping_Worker) — Agent
- [Deterministic Graph Engine](/Software/Deterministic_Graph_Engine) — Software
- [Event Ingestion API](/Software/Event_Ingestion_API) — Software

## Startup Story Brand

**Hero**:
- **Need**: to be the growth strategist who proves ROI with mathematical certainty
- **Want**: to map messy ad campaign logs to exact revenue outcomes
- **Identity**: the performance marketing lead at a mid-market e-commerce brand
**Plan**:
- Step: Submit logs · Detail: Input your unstructured campaign event logs from Facebook or Google Ads directly into our ingestion engine.
- Step: Inspect graphs · Detail: Review the deterministic attribution graph for any anomalies or unmapped multi-touch customer journeys.
- Step: Export revenue · Detail: Push the final attribution table into your warehouse or use it to generate exact client ROI reports.
**Guide**:
- **Empathy**: When UTM parameters arrive out of order or deeply nested, your attribution models break and reporting halts.
**Problem**:
- **Villain**: manual SQL queries
- **External**: Calculating ROAS across Facebook and Google Ads requires writing custom scripts to join unstructured tracking logs with HubSpot records.
- **Internal**: You feel like a database admin rather than a marketer when spreadsheets don't balance.
- **Philosophical**: Strategic marketing expertise belongs in campaign optimization, not in cleaning broken tracking parameters.
**Success**: Every ad dollar is tracked to a specific transaction in a deterministic graph that updates as often as every five minutes.
**One Liner**: Instead of wrestling with manual SQL queries, Cresci maps unstructured campaign logs into deterministic attribution graphs — providing exact ROI for every ad dollar spent.
**Positioning**:
- **So That**: map unstructured logs to exact revenue with zero configuration
- **Unlike**: Supermetrics or manual SQL queries
- **For Whom**: performance marketing leads at mid-market brands
- **Category**: Deterministic Attribution for E-commerce
**Call To Action**:
- **Direct**: Map campaign events
- **Transitional**: View sample attribution graph
**Failure Stakes**:
- Wasting ad spend on misattributed channels
- Hours lost to manual data cleaning
- Inaccurate ROI reporting to stakeholders
**Transformation**:
- **To**: scaling revenue through deterministic attribution instead of guessing which ads worked
- **From**: a growth marketer writing manual SQL joins
**Controlling Idea**: Marketing attribution should be a deterministic graph, not a manual spreadsheet exercise.

## Startup Token Hero

**Genre**: founding-hypothesis
**Rendered**: Instead of wrestling with manual SQL queries, Cresci maps unstructured campaign logs into deterministic attribution graphs — providing exact ROI for every ad dollar spent.
**Mechanism**: spine-derived-v1
**Template Id**: spine-founding-hypothesis
**Vocab Fingerprint**: 17e3adfe41e41181

## Startup Token Positioning

**Genre**: moore-positioning
**Rendered**: Deterministic Attribution for E-commerce for performance marketing leads at mid-market brands. Unlike Supermetrics or manual SQL queries — map unstructured logs to exact revenue with zero configuration.
**Mechanism**: spine-derived-v1
**Template Id**: spine-moore-positioning
**Vocab Fingerprint**: cc48e07f6324ccfb

## Startup Token Pitch Deck

**Genre**: pitch-deck
**Rendered**: Problem: Calculating ROAS across Facebook and Google Ads requires writing custom scripts to join unstructured tracking logs with HubSpot records.
Solution: Instead of wrestling with manual SQL queries, Cresci maps unstructured campaign logs into deterministic attribution graphs — providing exact ROI for every ad dollar spent.
Customer: performance marketing leads at mid-market brands
Unlike: Supermetrics or manual SQL queries
**Mechanism**: spine-derived-v1
**Template Id**: spine-pitch-deck
**Vocab Fingerprint**: 65229c5084950358

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

**Pain**: Calculating ROAS across Facebook and Google Ads requires writing custom scripts to join unstructured tracking logs with HubSpot records.
**Metrics**: Target: Every ad dollar is tracked to a specific transaction in a deterministic graph that updates as often as every five minutes.
**Rendered**: Pain: Calculating ROAS across Facebook and Google Ads requires writing custom scripts to join unstructured tracking logs with HubSpot records.
Economic buyer: Marketing Operations
Metrics: Target: Every ad dollar is tracked to a specific transaction in a deterministic graph that updates as often as every five minutes.
Competition: Supermetrics or manual SQL queries
**Mechanism**: spine-derived-v1
**Competition**: Supermetrics or manual SQL queries
**Economic Buyer**: Marketing Operations
**Vocab Fingerprint**: 609e0e4f412f2e20

## Startup Token Cold Email

**Genre**: cold-email
**Rendered**: Subject: Deterministic Attribution for E-commerce for performance marketing leads at mid-market brands

performance marketing leads at mid-market brands — Calculating ROAS across Facebook and Google Ads requires writing custom scripts to join unstructured tracking logs with HubSpot records. Instead of wrestling with manual SQL queries, Cresci maps unstructured campaign logs into deterministic attribution graphs — providing exact ROI for every ad dollar spent.
**Mechanism**: spine-derived-v1
**Template Id**: spine-cold-email
**Vocab Fingerprint**: 9503e5c71bb71e80

## Startup Token Agent Spec

**Genre**: ai-agent-spec
**Rendered**: Deterministic Attribution for E-commerce. Instead of wrestling with manual SQL queries, Cresci maps unstructured campaign logs into deterministic attribution graphs — providing exact ROI for every ad dollar spent. Serves performance marketing leads at mid-market brands.
**Mechanism**: spine-derived-v1
**Template Id**: spine-ai-agent-spec
**Vocab Fingerprint**: fafd0c30e20b33e3

## Neighborhood

### Candidate solutions

- [Unpredictable Die Tooling Wear](/Problems/Unpredictable_Die_Tooling_Wear) — candidate solution for · Problems

### Composed of

- [Unstructured Log Agent](/Agents/Unstructured_Log_Agent) — composes · Agents
- [Deterministic Graph Engine](/Software/Deterministic_Graph_Engine) — composes · Software
- [Event Ingestion API](/Software/Event_Ingestion_API) — composes · Software
- [Attribution Graph Service](/Services/Attribution_Graph_Service) — composes · Services
- [Campaign Mapping Worker](/Agents/Campaign_Mapping_Worker) — composes · Agents

### Embodies

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

### What it offers

- [Attribution Graph Engine](/Software/Attribution_Graph_Engine) — offers · Software

### Competitors

- [Improvado](/Competitors/Improvado) — competes with · Competitors
- [Funnel.io](/Competitors/Funnel.io) — competes with · Competitors
- [manual SQL queries](/Competitors/manual_SQL_queries) — competes with · Competitors
- [Triple Whale](/Competitors/Triple_Whale) — competes with · Competitors
- [Supermetrics](/Competitors/Supermetrics) — competes with · Competitors

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