The Win-Win
Consumer Data Economy

People

Data ownership.
Real compensation.

Users get paid when they consent to a brand's offer — the first real path to owning and monetizing your own data.

⇄

Brands

Intelligence that builds brand affinity.

Find real audiences. Earn their trust and favor. Target with unparalleled precision — and an implicit preference your competitors can't buy.

12-Month Projections — $2M Pre-Seed

Click any card or number to see its formula and source.

The Moment

The old model collapsed.
No one has rebuilt it yet.

The market

$365B

The infrastructure it was built on no longer exists.

Device IDs, third-party cookies, cross-app signals — shut down by platform policy.

Mordor Intelligence, 2026

The signal collapse

80–90%

Of iOS users declined app tracking — permanently.

~50% targeting accuracy remained. The baseline nobody questioned.

Adjust ATT Opt-In Rates, 2025 · Truthset/CIMM, Oct 2023

The waste

1 in 3

Impressions still reach the wrong person entirely.

Ad waste grew 34% in two years. The spend stayed. The signal didn't.

ANA Programmatic Benchmark, 2025

The unlock

99.6%

Of consumers would share data willingly, for the right deal.

Not anti-data. Anti-exploitation. The willingness for a fair exchange has always been there.
The infrastructure to deploy it at scale hasn't — until now.

Attentive Personalization Study, 2024

Whoever earns user trust first
owns the rails for the next decade.

User Growth Strategy

The first platformwhere your consentpays you.

01 — User Value Prop

Nearly free money,
minimal friction,
maximum payout

One-time 30-second onboarding. Model updates live — zero lift. Users earn by accepting push notifications.

9:41●●●

Our goal is to get people paid
as much as possible, as safely as possible.

02 — Distribution Strategy

150K users.
That’s what $2M buys.

@theantitechbro is the channel — a movement, not an ad. Gen Z doesn’t trust platforms. They trust people. That’s the strategy.

Founder-led consumer brands convert at 3–4× the rate of traditionally marketed equivalents.

Morning Consult Creator Economy Report, 2023

The movement dynamic

Push, not pull

The offer comes to the user.

No app to open. No habit to build. No reason to leave.

Value in every touch

Every notification has money in it.

Not engagement bait. A financial offer.

Structural retention

0.2% monthly churn.

There’s no reason to delete it — it never bothers you until it brings you money.

The Marketplace Mechanic

Every marketplace has a cold start.
Behavioral clustering dissolves it.

Brand Acquisition Engine

Agents matching users to brands at scale.

Automated email outbound matches verified users to qualified brands —
three channels find them, one flywheel compounds them.

Here’s the engine running in real time.

Ch 1

Cluster Targeting

Users cluster automatically by shared behavior. The engine detects each group, finds competing brands, and opens a sequence.

Ch 2

Coverage Balancing

Every segment tracks its own offer frequency. When a slice goes underserved, the engine identifies the missing brands and routes them into the pipeline.

Ch 3

High-Spend Meta Advertisers

Targets brands spending $100K+/yr on Meta. Unlocks at Month 3, once first-cohort ROAS lift is confirmed.

Brand Acquisition Engine

Running

Channel 1

Cluster Targeting

●

→

Conversion rates updating in dashboard

Emails / mo

375K

Conv rate

0.02%

Brands / mo

~30

Channel 2

Coverage Balancing

⚠️2.0 offers · 2 weeks

fitness · 25–34 · urban · low coverage detected

→

Conversion rates updating in dashboard

Emails / mo

675K

Conv rate

0.02%

Brands / mo

~45

🔒Unlocks at Mo 3 · requires early cohort ROAS data

Channel 3 — High-Spend Meta Advertisers

Target

$100K+/yr Meta spend

Volume

450K emails / mo

Infrastructure

Same stack · higher intent

Unlock condition

20–40% ROAS lift confirmed in cohort 1

Brand Growth Strategy

Ad targeting has always been guesswork.
We built the infrastructure that delivers the answer.

01 — Platform Mechanism

Search. Deploy.
Target.

Find verified audiences in your target market and request their consent directly.

Deploy an AO — users accept or decline within 24 hours
Query the ChatGPT of your live target market
Export to ad platforms. Target with unparalleled precision.

How an Audience Order Works

A brand sets a floor price. Users consent or decline. Everyone gets what they want.

Users keep 100% of the payout. mymodel fee is charged on top — additive, not extracted.

Consent architecture

100% explicit opt-in. Every time.

Compliance

CCPA/CPRA compliant by design.

User payout

Users keep 100%. No revenue split.

① Brand inputs

Filter & deploy

Search verified behavioral profiles. Set floor price. Deploy an AO to matched users.

Takes ~5 minutes

→

② User response

24-hour consent window

Users accept or decline. 100% of payout goes directly to them. Declined offers auto-redeploy.

Fill rate: 100% structural — declined AOs auto-redeploy to next matched user

→

③ Brand receives

Verified audience + intelligence

Consented audience exported to ad platforms. Live behavioral data queryable via dashboard. 30-day access window.

AO cost to brand

$35–$60

floor + fee · per AO (avg 50 users)

ROAS uplift

2–4×

vs. Meta baseline · BCG/Google 2021; LiveRamp 3.5× case study

Intelligence moat

Compounds

Every AO deepens the signal

Why brands stay

1.2%

monthly churn · 83-mo avg tenure

02 — The Market

The Brands With the Most to Gain
Become the Proof That Unlocks the Rest

Market Size

154K

US brands — Phase One addressable

Their Pain

~30%

Ad waste — wrong audience, zero consent

Speed to Sale

Decision-maker — CMO-approved, self-serve

Phase One — 154K US brands.

Entry cohort proves the model. Performance data unlocks the rest of the market.

Entry Cohort

Mid-Market DTC Brands

$5K – $100K / mo on Meta

Highest ad waste sensitivity — most motivated to switch

High ROAS sensitivity, no in-house identity resolution stack

Early-adopter influence that sets category norms

Phase One Market

154K

US brands spending $100K+/yr on Meta
Source: Meta Q4 2025 earnings

Entry cohort ROAS proof unlocks full Phase One via Ch3 (Mo 3+)

All performance advertisers in scope — not only DTC

Expansion beyond Meta: Year 2+

Mo 12 capture

03 — Unprecedented ROI

Immediate return.
Then it compounds.

Without mymodel

With mymodel

Meta ad spend

$30K/mo

Signal source

Where targeting intelligence comes from

Inferred

3rd-party cookies and behavioral models construct a profile. No consent. No verification.

Direct & consented

Behavioral signals verifiably attributed to a real, consented identity. Not modeled — confirmed.

Audience quality

What that signal produces at targeting time

Probabilistic

The system guesses who you are. No verification, no consent, no confirmation loop.

Verified & deterministic

Behavioral signals are verifiably attributed to a consented identity. ICP-matched — not inferred.

Audience readiness

Before the first impression

Cold

No consent. No prior relationship.

Pre-warmed

Matched, consented, and paid before the first impression. Users arrive with built-in trust and favorability — they already chose to engage with this brand.

Payback period

Time to positive ROI

Never

Spend resets each cycle.
No intelligence retained.

Month 1

Consent-verified targeting produces ROAS lift immediately. Membership fee recovered in the first campaign cycle.

Net impact on $30K/mo budget

Wasted spend

~$9K/mo

30% of $30K Meta budget reaches wrong audience · NC State / CSCW 2022

ROAS lift on cold traffic

20–40%

$6K–$12K additional value from same budget · ZigPoll / WordStream

Business Model

Low barrier to entry.
Immediate ROI.
A closed system built forlongevity and scale.

	Starter	Growth	Scale
Monthly fee	$199/mo → $499/mo Q1 2027	$999/mo	$1,999/mo
Audience Orders	1	Up to 5 (avg 3)	Unlimited (avg 5–8/mo)
Floor per user	$5.00 100% to user	$3.50	$3.00
Transaction fee charged on top of user payout	12%	10%	8%
Users per AO (avg est.)	~500	~1,000	~1,000+
API Access	—	—	H2 2026

Take Rate Model

Declines as brands scale — 12% → 8%. Brands that grow pay less. Built for retention, not extraction.

GMV Definition

GMV = floor price × users per AO × AOs deployed
mymodel revenue = GMV × take rate, charged on top

Unit Economics

What each brand is worth.
By the numbers.

LTV:CAC Ratio

Growth tier · base case

7,514:1

$263,000 LTV ÷ $35 CAC. Brands pay for themselves before their first AO completes — then stay an average of 83 months.

Churn basis: 1.2%/mo — higher than Klaviyo (0.83%) and LiveRamp (0.42%). The model is more conservative than its comps. The moat is why they stay.

Acquisition Cost

$35

per brand · base case

~$130K Y1 cost ÷ brands acquired. First invoice exceeds CAC at every tier.

Payback Period

Day 1

Starter $199 > $35

Growth $999 > $35

Scale $1,999 > $35

Memberships

~99%

Gross margin. SaaS-like — no delivery cost. Recurring monthly subscription.

Transaction Fees

10–12%

Take rate on GMV. Additive — brands pay on top of user payout. Scales with AO volume.

Lifetime Value

Revenue ÷ 1.2% monthly churn → 83-month avg brand lifetime. Steady-state ARPU.

Starter

$93,000

$1,120/mo × 83mo

Growth

$263,000

$3,173/mo × 83mo

Scale

$661,000

$7,961/mo × 83mo

Brand Retention

1.2% monthly churn → ~99% monthly retention. Brands who leave permanently lose their consent-verified audience data — it cannot be exported. The exit cost is the intelligence itself.

Closest Comp

Klaviyo

90%+

dollar-based NRR · S-1, 2023

Closest Comp

LiveRamp

95%+

NRR · Annual Report, 2023

Same structural lock-in mechanic as both comps — audience intelligence built on the platform cannot be replicated externally. This is why the 1.2% churn assumption is conservative, not optimistic.

Click any card to see its formula and source.

12-Month Projections

Capital is the activation event.

This is what it produces.

Budget & Runway

$2M raise → 14 months of runway

$2M Allocation

Team & Hiring Timeline

Runway: 14 months · $127K avg monthly opex

Month	Phase	Personnel	Consultants	Marketing	Infra	Legal	Other	Total Spend	Revenue	Net Burn	Cash Left

Platform Cost / User
$0.08 one-time onboard · $0.09/mo active · $0 inactive

LLM Cost as % of AO Revenue
~1.5% at Starter tier · ~2.5% at Scale tier

Source
Claude Haiku 4.5 ($0.80/$4 per M tokens) · Sonnet 4.6 ($3/$15 per M tokens)

The Raise

One founder built this.
Here's what $2M turns it into.

The infrastructure is built. The pilot is next.
Here's what $2M sets in motion.

What one person built without it

✓

Product

Two functional frontends (brand + consumer) and a working backend. Audience targeting, offer creation, consumer onboarding, and the Gmail data pipeline are production-complete. What remains: payment rails and offer delivery wiring. Architecture done. Wiring left.

✓

Brand outreach stack

Instantly + Inframail. Built, tested, and warmed. 50K/day capacity ready to deploy.

✓

Trust layer — @theantitechbro

The best consumer brands build their audience before they launch their product. @theantitechbro builds the audience before mymodel launches. Gen Z doesn't trust platforms — they trust people. The $2M turns an early audience into a 150K+ user waitlist.

✓

Consent architecture mapped

CCPA/CPRA compliant by design. Legal framework in final review.

✓

Financial model

Pure formula chain. Every number sourced, every input documented, every scenario stress-tested.

✓

Design Partnership Program

Outreach live across 7 competitive DTC niches — category-leading brands targeted for exclusive pre-launch access. Case studies before July.

7 niches. One slot each. The proof that unlocks 154K brands starts with seven.

The Strategy

Every niche has one slot. Every brand in that niche knows their competitor is being offered the same access. The first to move gets exclusive pre-launch positioning with an audience intelligence architecture that doesn't exist anywhere else — and their competitor doesn't. This isn't a beta test. It's a 30-day sprint that delivers something no brand has ever received: 360-degree intelligence from users who opted in, consented, and trust the platform enough to tell the truth about how they feel about a brand. Behavioral data. Honest attitudinal feedback. Campaign performance — all in one document. The brands in this program are spending $30K+/mo on Meta and facing the exact targeting degradation this platform was built to solve. They were chosen because their names on a case study set the standard for every brand that follows.

What capital activates — the chain

$2M capital lands

Team + CTO hired (May)

Content machine activates → user acquisition begins

Matched audiences assembled toward design partner profiles

Design partnerships go live (June)

360° intelligence collected — behavioral + attitudinal + performance

Named case studies in hand (before July launch)

Tier 3 brand outreach fires with proof, not promises

What capital unlocks — in sequence

Phase 1 · Apr–May 2026

Build.

CTO joins. Legal finalized. Team assembled and outreach sequences loaded for launch.

Team in place. Product complete. Outreach ready to fire.

Phase 2 · Jun 2026

Prove.

Design partners live. 360° intelligence delivered — the first time a brand has received behavioral, attitudinal, and performance data from a consented audience in a single document. Named case studies in hand before Tier 3 outreach fires.

First ROAS case study in hand before public launch.

Phase 3 · Jul 2026

Launch.

Full public launch. Waitlist converts. Email outreach at scale. Intelligence moat compounds with every AO.

Mo 1 begins. Every chart above starts here.

The sequence above produces $125.5M ARR at Month 12.

Base case · Here's what that's worth to you.

The Return

$2M Pre-Seed Round

$10M pre-money • $12M post-money • 16.7% dilution

Your Check Size $100K

$50K$2M

ARR multiples: 10x conservative, 15-20x current median, 25x premium. Source: PitchBook 2024.

The Team

Built by domain experts.
Backed by the right people.

Every person in this room was chosen for what they bring to a specific layer of this problem. That continues into who invests, who advises, and who we hire.

Founder & CEO

Jordan Smith

Worked with hundreds of brands across both sides of the data economy. Building the trust moat required for a consent-native exchange — through culture, content, and product, simultaneously. The raise scales an engine already in motion.

Users trust who is building this as much as what is being built.

Founding Engineer

Chris Madison

ex-Microsoft · Data Architect

Built the backend infrastructure powering myModel's data pipeline, audience targeting, and consumer onboarding. Production-complete architecture, designed for scale and CCPA compliance from day one.

Domain Support

No equity. No formal arrangement. These are the domain experts who've been in the room while this was built — because they believe in what it is.

Brand Sales

Jordan Cushman

Director, SMB Sales — Reddit Ads

The brand buyer's perspective — SMB advertiser sales at Reddit maps directly to myModel's DTC ICP and covers the GTM motion until a Growth Lead formalizes it.

AI & Behavioral Modeling

Chris Anzalone

3× Founder, CEO — NextLM

Serial founder operating at the intersection of human behavior modeling and AI — directly informs myModel's intelligence layer and provides battle-tested scaling judgment.

iOS · Consumer Behavior

Shahin Zangenehpour

Principal Mobile Engineer | Neuroscience PhD

iOS architect and behavioral neuroscientist whose expertise in consumer-native mobile experience directly informs the consent model and user engagement design.

Fintech · Social Impact

Lynn Liss

Social Impact Executive & Fintech Leader

Contribution economy architect whose work on equitable data exchange mirrors myModel's founding thesis — and informs the user earnings infrastructure.

First Hires Post-Raise

CTO

Technical leadership from day one.
Owns product architecture, data pipeline, and compliance infrastructure.
Hire #1 — actively recruiting.

Content Producer

Scales brand-facing content across video, social, and editorial.
Hire #2 — funded at close, ramps into pilot.

Growth Lead

Owns the brand acquisition pipeline.
Email outreach, channel partnerships, and inbound conversion.
Hire #3 — pipeline building toward launch.

How You Can Be Included

Every investor, advisor, and hire
accelerates a specific layer.

Investors

Capital + domain acceleration

Advisors

Organic domain validation

Hires

Full-time execution

What You'd Accelerate

Not a specific fund type — a specific contribution. Every investor in this round should naturally move at least one of these forward:

Brand & Advertiser Access Data & AI Consumer & Distribution Media & Creator AI for Good

Brand Sales & GTM AI & Behavioral Modeling iOS & Consumer Behavior Fintech & Social Impact Data & Partnerships Retail & DTC Media & Creator Economy

CTO Hire #1 — actively recruiting

Content Producer Hire #2 — at close

Growth Lead Hire #3 — Mo 3

What You Bring

Capital that comes with built-in acceleration on both sides of the market. Domain-specific pattern matching. Warm intros to brands or users already in your network.

Expert guidance in a layer we're actively building. Network access in your domain. Help us move faster and avoid the known pitfalls in your area.

Full-time execution of a specific layer of the business. Each role is sequenced by phase — you join when the business is ready for your function to scale.

How to Participate

Pre-seed round. $2M target at $10M pre-money. Moving fast matters as much as the check size.

No equity, no formal arrangement — organic engagement with domain experts who believe in what this is. Active conversations across the stack.

Post-raise hire, sequenced by phase. Three roles open. CTO is actively recruiting — first to join.

Questions? jordan@getmymodel.com

The Win-WinConsumer Data Economy

The old model collapsed.No one has rebuilt it yet.

Every marketplace has a cold start.Behavioral clustering dissolves it.

Ad targeting has always been guesswork.We built the infrastructure that delivers the answer.

Low barrier to entry.Immediate ROI.A closed system built forlongevity and scale.

What each brand is worth.By the numbers.