PRD Agent logoPRDAgent

Estimate your ROAS before ever spending a dollar.

COMPLETE
ASAP
$10,000
4 features
3 milestones
1 role

Project Overview

Problem Statement
Ad attribution is unreliable; companies spend on ads/creator deals without knowing if spend will be profitable (ROAS).
Ideal Customer Profile
Primary user persona: Growth marketer at a brand/company buying paid ads or creator sponsorships who needs pre-deal ROI estimates and post-deal learning.
App Audience
Public-facing SaaS anyone can sign up for.
Project Type
Greenfield (new build).

N/A

Integrations
TBD (discussion topic)
Tech Stack Preferences
Next.js + Postgres.
Deployment Preferences
Hosted on Render.
Design Status
No designs yet; engineer can create a simple clean MVP UI.

Features

Authentication & user accounts
Require sign-up/login so users can save business profiles, creator profiles, and simulation runs/results.
  • Implement auth (email/password or magic link)

    Add authentication flows in Next.js and backend sessions/JWT; choose provider/library suitable for Next.js.

  • User workspace & ownership model

    Associate business profiles, creator profiles, and simulation runs with a user account in Postgres.

  • Basic account management

    Profile page, logout, and minimal settings needed for MVP.

Business & creator data intake (all required)
Collect comprehensive business-side and creator/channel-side inputs required to run simulations, with validation and storage. For MVP, require all input fields rather than optional defaults.
  • Design input forms and validation

    Implement UI + backend validation requiring product/pricing, margins/COGS, AOV, refund rate, funnel conversion rates, LTV/repeat assumptions, attribution window, and target geo/language.

  • Creator/channel input capture

    Require creator audience size, demographics, engagement patterns, and historical ad performance (manual entry or upload for MVP).

  • Input storage model

    Create Postgres schema to store business profiles and creator profiles and link them to simulation runs.

YouTube creator sponsorship simulation (MVP)
Support running a simulation for a proposed YouTube creator sponsorship deal using business inputs + creator/channel inputs, producing low/medium/high recommended price points with ROI/breakeven probabilities.
  • Define required inputs schema

    Specify business inputs (product, pricing, margins, funnel conversion rates, LTV assumptions) and creator inputs (audience size, demographics, engagement, historic performance) for MVP.

  • Create simulation runner service

    Implement backend service that runs thousands of synthetic audience agent simulations through the funnel and aggregates outcomes.

  • Pricing recommendation outputs

    Compute and return low/medium/high deal price recommendations with associated probability of positive ROI/breakeven.

  • Frontend workflow

    Build Next.js UI to enter inputs, start a run, show progress/status, and display the three recommended prices and summary charts.

  • Persist runs and results

    Store inputs, run metadata, and outputs in Postgres for retrieval and comparison later.

Simulation results visualization (ROAS distribution)
Results page should visualize the predicted ROAS distribution from the synthetic audience simulations, alongside the recommended deal price points.
  • Aggregate distribution data

    From simulation outputs, compute ROAS samples and summary stats; build histogram/bucketed distribution for UI rendering.

  • Results UI chart

    Implement ROAS distribution chart on results page (e.g., histogram/violin) with clear labeling and ability to compare scenarios later.

Milestones

Milestone 1

Milestone 1 — MVP skeleton + data models
Set up Next.js app, Postgres schema, Render deployment pipeline, and core data models for users, business profiles, creator profiles, and simulation runs.
$2,500

Assigned Features

  • Authentication & user accounts
  • Business & creator data intake (all required)

Milestone 2

Milestone 2 — Run simulation + price recommendations
Implement the simulation runner and pricing recommendation outputs for YouTube creator sponsorship deals; allow users to create and execute runs end-to-end.
$4,500

Assigned Features

  • YouTube creator sponsorship simulation (MVP)

Milestone 3

Milestone 3 — Results visualization + polish
Add ROAS distribution visualization, improve UX, and deploy a usable public SaaS MVP on Render.
$3,000

Assigned Features

  • Simulation results visualization (ROAS distribution)

Skills Needed

Full-Stack Engineer
Own the MVP end-to-end: Next.js app, APIs, simulation orchestration, Postgres data model, and Render deployment.
Next.jsReactTypeScriptAPI designPostgreSQLBackground jobs/queuesRender

Open Questions

How should post-campaign actuals be ingested for predicted-vs-real comparisons and training (manual entry vs CSV upload vs API integrations)? What metrics are the source of truth?
User marked post-campaign ingestion as a discussion topic. Needed to implement learning loop and evaluation reporting for MVP.
Which integrations should the MVP support (ad platforms, creator platforms, Shopify, GA4, Mixpanel, etc.) and what data access method is feasible (API, exports, manual upload)?
User flagged integrations as a discussion topic. The product relies on ingesting business + channel/creator data; need to decide MVP integrations vs manual CSV inputs and prioritize platforms.