Audience Town Financial Model

Audience Town consolidates 14 traditionally separate marketing functions (DSP, identity, creative builder, media, data management, consumer data, attribution, search, analytics, social, ad agency, data science/tech, service) into a single self-serve platform. It targets the 40 million annual US home movers across the full home journey (pre-move → in-market → close → confirmed → post-move → settled home) using proprietary mover-intent data and an ML engine.

Revenue claim: 5x ROI for advertisers.

Customers span enterprises, realtors, SMBs, home furnishings, CPG, and retail. Named clients include Toll Brothers, Lennar, HomeLight, Invitation Homes, Serhant, Guaranteed Rate, Sunrun, 1-800-PACK-RAT, Plymouth Rock, and others.

Payment model: subscription / MRR.

• TAM: $1T (global online advertising)
• SAM: $95B
• SOM: $1B
• AdTech public market caps grew from $5B (2017) to $160B (2021)
• PropTech record funding: $4.5B in Q1 2021
• 40 million home movers targeted annually
• 83% of searchers have looked for homes with no intention of buying
• Average B2C business loses 20% of customers per year to moving

AdTech comps cited: TripleLift ($1.4B PE M&A, 2021), Viant (IPO, $1.7B market cap, 2021), The Trade Desk (IPO, $27B market cap, 2021), PubMatic (IPO, $1.7B market cap, 2021).

PropTech comps cited: Opcity ($210M exit to News Corp, 2018), Homesnap ($250M exit to CoStar, 2020), Porch (IPO, $1.7B market cap, 2020), Top of Mind ($250M exit to Black Knight, 2021).

Two-layer model:

1. Subscription / MRR - platform access fee for self-serve ads UI, data management, and analytics. Specific price points not disclosed.
2. Media / ad spend - managed or self-serve ad campaigns across all formats and channels (DSP, search, social, display). Revenue likely taken as a margin on media or as CPM/CPC fees. Specific take-rate not disclosed.

Channels: direct sales (enterprise/realtor) and self-serve (SMBs). Self-service platform launched in 2021.

No ARPU, contract size, or pricing tiers disclosed in the deck.

• 200% YoY revenue growth in 2020
• 212% YoY revenue growth in 2021
• First client: 2018
• Pre-seed round completed: 2019
• Self-service platform launched: 2021
• Named client logos spanning real estate, home services, insurance, energy, and moving categories

No absolute revenue figures, ARR, MRR, customer count, or retention rates disclosed.

Competitive framing: existing marketing vendors (Meta, Zillow, Google, RealPage, Porch) each cover only a narrow slice of the mover journey and require fragmented stacks. Audience Town's moat claims:

• Proprietary home-journey intent data spanning the full pre-/post-move window
• Consolidated platform (14 functions in one) reduces vendor fragmentation
• ML engine for audience targeting and data management
• First-mover positioning in home-mover vertical adtech

No formal competitive matrix or defensibility metrics in the deck.

• Raising: up to $6M (Seed)
• Use of funds:

1. Hire engineering and marketing leadership
2. Accelerate self-serve ads UI, data infrastructure, and marketplace architecture
3. Acquire unique data to accelerate offering

• Founded: 2016 (idea stage)
• Team composition not disclosed in this deck (no team slide).

Archetype + why: AdTech SaaS + Media Marketplace hybrid. Revenue splits across (a) subscription MRR from platform access and (b) media revenue (take-rate or gross media margin on ad spend). Given the self-serve launch and MRR language, the primary model archetype is a SaaS ARR / MRR build with a media revenue layer. This is standard for vertical AdTech platforms that monetize both software access and managed/self-serve media.

Forecast horizon & granularity:

• 5-year annual model (2022–2026) with monthly detail for Year 1 (matching the fundraise close).
• Monthly for the first 12 months to track MRR ramp and ad spend; annual thereafter.

Key drivers & assumptions:

*Revenue - Subscription / MRR:*

• Starting MRR: $50K/month (2022 base); rationale: implied by ~200%+ growth trajectory from a small base starting ~2018–2019, no actuals given.
• New logos per month: 3–5 SMB/self-serve + 1 enterprise; rationale: self-serve platform just launched, early ramp expected.
• Monthly subscription ARPU - SMB: $1,000–$3,000/month; enterprise: $5,000–$15,000/month. Rationale: typical AdTech SaaS for mid-market.
• Monthly churn rate: 2–3% (SMB), 1% (enterprise). Rationale: AdTech vertical benchmarks; deck claims retention benefit from mover-data stickiness.

*Revenue - Media / Ad Spend:*

• Media revenue as % of subscription revenue: 1.5–2.5x. Rationale: managed media revenue typically exceeds subscription revenue in early-stage AdTech platforms.
• Net take-rate on media: 20–30% of gross ad spend. Rationale: programmatic AdTech industry standard.
• Ad spend per client per month: $5,000–$50,000 range. Rationale: no deck data; based on named client profiles (homebuilders, insurance, CPG).

*Growth:*

• YoY revenue growth: 200% ('20), 212% ('21). Applied as a decelerating curve: 150% in 2022, 80% in 2023, 50% in 2024, 30% in 2025, 20% in 2026. Rationale: growth compression typical post-Series A buildout; SOM of $1B implies room but sales motion will mature.

*Costs:*

• Gross margin: 55–65% blended (software ~80%, media net ~30%). Rationale: typical for SaaS+media mix.
• Headcount: 2022 plan focused on engineering and marketing leadership hires. Starting headcount: ~10–15 FTEs; ramp to ~30 by end-2022 with $6M raise.
• S&M as % of revenue: 40–50% in early years, declining to 25% by Year 5. Rationale: customer acquisition investment during self-serve launch.
• R&D as % of revenue: 25–35% Year 1, declining to 15% by Year 5. Rationale: platform and data infrastructure build-out.
• G&A: 15% of revenue, declining to 8% by Year 5.

*Data acquisition:*

• One-time / recurring data acquisition capex: explicitly called out in use of funds.: $500K–$1M Year 1, $200K–$500K recurring. Rationale: proprietary mover-data moat is a core strategic asset.

*Raise:*

• Seed raise: up to $6M. Model starting cash: $6M + existing cash.
• Runway target: 18–24 months to Series A. Rationale: standard seed burn horizon.

Scenarios (Base / Bull / Bear - which variables flex):

• Base: 150% YoY 2022, churn 2.5% SMB, take-rate 22%, 30 FTEs by year-end 2022.
• Bull: 200%+ sustained into 2022 (self-serve flywheel kicks in early), churn 1.5%, enterprise mix higher, data monetization adds a third revenue stream.
• Bear: Growth compresses to 80% in 2022 (macro/rate sensitivity hits real estate ad budgets), churn 4%, media take-rate compresses to 15% under competitive pressure, extends burn rate requiring bridge.

Required sheets / outputs:

1. Assumptions dashboard (all drivers in one place)
2. MRR / ARR build (cohort-based: SMB self-serve + enterprise; new/expansion/churned)
3. Media revenue build (clients × spend/client × take-rate)
4. P&L (IS): Revenue, COGS, Gross Profit, OpEx by category, EBITDA, Net Income
5. Headcount plan (department × role × start month × salary)
6. Cash flow & runway (monthly, 24 months)
7. Scenario toggle (Base / Bull / Bear switchable)
8. Cap table (pre/post Seed; include pre-seed dilution)