# tvScientific - Marketing Research Report

Generated on: April 7, 2026
**Industry:** Marketing
**Website:** https://www.tvscientific.com

## The Takeaway

tvScientific's moat is risk-sharing — by absorbing media spend risk through CPA pricing, it aligns incentives with performance-obsessed D2C brands who've exhausted cheaper channels.

---

# Company Research

## Company Summary

tvScientific is a connected TV advertising platform that makes TV advertising accessible and measurable for brands and apps of all sizes through AI optimization and performance-driven campaigns [2]

**Founded:** Founded in 2016 [3]

**Founders:** Not publicly disclosed [1]

**Employees:** 51-200 employees [1]

**Headquarters:** New York, United States [1]

**Funding:** Acquired by Pinterest in February 2024 for an undisclosed amount [5]

**Mission:** To power Performance TV advertising that drives sales through AI optimization, measurement, and provable outcomes [6]

**Strengths:** The company's strengths rely on the combination of AI-driven optimization technology, transparent performance measurement, and CPA-based risk-sharing models. [7]

• **AI Optimization**: Campaigns automatically learn and adapt in real time with sophisticated technology that improves ROAS by as much as 50% [7]
• **Performance Transparency**: Delivers radical transparency in reporting with clear attribution and ROI measurement, giving marketers full confidence in campaign performance [18]
• **Risk-Sharing Model**: Only CTV platform offering advertising on a pure CPA model, taking on media risk to prove effectiveness [15]

## Business Model Analysis

### 🚨 Problem

****Traditional TV advertising lacks measurability and accessibility for performance-driven marketers** [2]**

• TV advertising has historically been difficult to measure and attribute to actual business outcomes [16]
• Connected TV advertising requires sophisticated technology and expertise that many brands lack internally [7]
• Performance marketers struggle to prove TV's impact within their broader media mix [18]
• Traditional TV buying lacks the transparency and control that digital marketers expect [11]

### 💡 Solution

****AI-powered connected TV platform that automates buying, optimization, and measurement for performance marketers** [16]**

• Self-serve platform combines integrated media buying and measurement with full campaign control [7]
• AI optimization technology that automatically learns and adapts campaigns in real time [18]
• Advanced audience targeting using 1st and 3rd party data, including 150M credit card user transactions [14]
• Transparent reporting with clear attribution and ROI measurement [18]

### ⭐ Unique Value Proposition

****The first and only CTV platform purpose-built for serious performance marketers with guaranteed outcomes** [16]**

• Only CTV platform offering advertising on a pure CPA model, taking on media risk [15]
• AI optimization improves ROAS by as much as 50% compared to traditional approaches [7]
• Radical transparency in reporting with full attribution confidence [18]
• Advanced audience capabilities leveraging 150M credit card transactions for competitive targeting [14]

### 👥 Customer Segments

****Performance-driven brands and apps of all sizes seeking measurable TV advertising outcomes** [2]**

• Direct-to-consumer brands looking to scale beyond digital channels [13]
• Mobile app companies seeking user acquisition through connected TV [16]
• E-commerce brands requiring attribution and measurable ROI [13]
• Regional businesses and organizations like The Y in Central Maryland targeting local communities [13]
• Australian-born brands expanding into the U.S. market [13]

### 🏢 Existing Alternatives

****Competes with major programmatic TV and DSP platforms in the connected TV advertising space** [10]**

• The Trade Desk - leading programmatic advertising platform with broad reach [11]
• Samsung DSP - enterprise-focused connected TV advertising platform [12]
• MNTN - performance TV advertising platform targeting SMB market [12]
• Vibe - self-serve CTV platform for enterprise brands [12]
• Traditional TV networks and cable advertising [6]

### 📊 Key Metrics

****Focuses on performance metrics including ROAS improvement and customer acquisition costs** [7]**

• ROAS improvement of up to 50% through AI optimization [7]
• Access to 150M credit card user transactions for audience targeting [14]
• Campaign performance measured through transparent attribution and ROI reporting [18]
• Customer acquisition and retention metrics through CPA model [15]

### 🎯 High-Level Product Concepts

****Self-serve platform with integrated media buying, AI optimization, and measurement capabilities** [7]**

• Connected TV advertising platform with automated buying and optimization [6]
• Advanced audience targeting using first-party and third-party data [17]
• Real-time campaign optimization and learning algorithms [18]
• Comprehensive measurement and attribution reporting [7]
• Customer and prospect data activation for targeting and retargeting [17]

### 📢 Channels

****Direct sales, self-serve platform, and technology partnerships drive customer acquisition** [15]**

• Self-serve platform for direct customer onboarding [7]
• Technology partnerships with affiliate networks like Awin [15]
• Content marketing through insights and educational resources [8]
• Case studies and customer success stories [13]
• Industry positioning as Trade Desk alternative [11]

### 🚀 Early Adopters

****Performance marketers seeking measurable TV advertising with guaranteed outcomes** [16]**

• Direct-to-consumer brands requiring attribution and ROI measurement [13]
• Mobile app companies looking for user acquisition beyond traditional digital channels [16]
• Marketers frustrated with traditional TV's lack of measurability [18]
• Brands willing to work with CPA-based pricing models [15]

### 💰 Fees

****Offers unique CPA-based pricing model alongside traditional media buying fees** [15]**

• Pure CPA (Cost Per Acquisition) model where tvScientific takes on media risk [15]
• Self-serve platform pricing structure [7]
• Traditional media buying fees for standard campaigns [7]
• No disclosed specific pricing tiers publicly available [6]

### 💵 Revenue

****Revenue generated through media buying fees and performance-based CPA pricing** [15]**

• Media buying platform fees from advertiser spend [7]
• Performance-based revenue through CPA model arrangements [15]
• Technology platform subscription or usage fees [7]
• Acquired by Pinterest in February 2024, contributing to Pinterest's Q1 revenue forecast [5]

### 📅 History

****Founded in 2016 and acquired by Pinterest in 2024 after establishing CTV leadership** [3]**

• 2016: Company founded to address TV advertising measurability challenges [3]
• 2019-2021: Developed AI optimization technology and self-serve platform [7]
• 2022: Launched CPA-based pricing model as industry first [15]
• 2023: Expanded customer base across multiple verticals [13]
• February 2024: Acquired by Pinterest to enhance their connected TV advertising capabilities [5]
• 2024: Integration with Pinterest's advertising ecosystem begins [5]

### 🤝 Recent Big Deals

****Acquired by Pinterest in February 2024 to strengthen Pinterest's connected TV advertising offerings** [5]**

• Pinterest acquired tvScientific in February 2024 for undisclosed amount [5]
• Acquisition led Pinterest to raise Q1 2024 revenue forecast due to partial-quarter contribution [5]
• Integration expected to enhance Pinterest's advertising platform with CTV capabilities [5]
• Partnership with Awin for affiliate marketing technology integration [15]

### ℹ️ Other Important Factors

****Operating in rapidly growing connected TV advertising market with increasing cord-cutting trends** [8]**

• Connected TV market benefits from shift from traditional cable to streaming services [8]
• AVOD platforms like Hulu and Peacock integrate advertisements, creating inventory opportunities [8]
• Positioned in SMB CTV market segment alongside Vibe and MNTN [12]
• Focus on transparency and performance measurement addresses industry trust issues [11]

---

# ICP Analysis

## Ideal Customer Profile

tvScientific's ideal customer is a **performance-driven D2C brand** with $10M-$100M annual revenue that has exhausted traditional digital channels and seeks **measurable TV advertising outcomes**. These **data-obsessed marketers** operate e-commerce or subscription businesses with established attribution systems and customer acquisition funnels.

They value **transparent reporting** and are willing to experiment with **CPA-based models** where tvScientific shares media risk. The ideal customer has dedicated performance marketing teams experienced with programmatic advertising who can leverage **AI optimization technology** to achieve 50% ROAS improvements while proving TV's impact within their broader media mix.

## ICP Identification Framework

| No. | Question | Answer | References |
|-----|----------|--------|------------|
| 1 | Which of our current customers makes the most out of our products and services? Who uses it the most? Who are your best users? | Best customers are **performance-driven direct-to-consumer brands** and **mobile app companies** seeking measurable TV advertising outcomes [13] [16]. They typically operate **e-commerce businesses** or **subscription services** requiring clear attribution and ROI measurement [13]. These customers actively leverage the **AI optimization technology** and **CPA-based pricing model** to prove TV's impact within their broader media mix [15] [18]. | [13], [16], [15], [18] |
| 2 | What traits do those great customers have in common? | Common traits include **data-driven marketing approaches** with focus on performance metrics and attribution [16] [18]. They operate **digital-first businesses** that understand programmatic advertising and value **transparent reporting** [18]. These customers typically have **established customer acquisition funnels** and are willing to experiment with **CPA-based risk-sharing models** [15]. Most are **scaling brands** moving beyond traditional digital channels to reach broader audiences [13]. | [16], [18], [15], [13] |
| 3 | Why do some people decide not to buy or stop using our product? | Primary barriers include **traditional mindset toward TV advertising** and preference for established platforms like **The Trade Desk** [11]. Some prospects are hesitant about the **CPA model's risk-sharing approach** or lack internal expertise for connected TV campaigns [15] [7]. **Enterprise brands** may prefer **Samsung DSP** or other established enterprise-focused platforms over SMB-positioned solutions [12]. Additionally, some advertisers require **offline capabilities** not available in cloud-based platforms [7]. | [11], [15], [7], [12] |
| 4 | Who is easiest to sell more to, and why? | Easiest expansion comes from **existing D2C brands** adding more campaigns and **mobile app companies** scaling user acquisition efforts [13] [16]. These customers already understand the **AI optimization value** and **transparent attribution benefits** [18]. **Growing e-commerce brands** naturally expand spend as they scale, while customers using **CPA models** often increase budgets based on proven performance [15]. Success breeds expansion through **measurable ROAS improvements** of up to 50% [7]. | [13], [16], [18], [15], [7] |
| 5 | What do our competitors' best customers have in common? | Competitor customers often prefer **enterprise-scale solutions** with The Trade Desk serving large agencies and brands [11]. **Samsung DSP customers** typically need **enterprise-grade support** and established vendor relationships [12]. Many competitor customers prioritize **broad programmatic reach** over specialized CTV performance optimization [10]. Opportunity exists with **performance marketers frustrated** by lack of transparency and attribution in traditional platforms, seeking **outcome-driven alternatives** [11] [18]. | [11], [12], [10], [18] |

## Target Segmentation

### 🥇 Primary Performance-Driven D2C Brands

**Industry:** E-commerce, Consumer Goods, Subscription Services

**Company Size:** $10M-$100M annual revenue, 50-500 employees

**Key Characteristics:** • **Data-driven attribution focus**: Brands requiring measurable ROI and clear attribution across all marketing channels
• **Digital advertising expertise**: Teams experienced with programmatic platforms and performance marketing
• **Scaling customer acquisition**: Companies expanding beyond Facebook/Google seeking new growth channels

**Rationale:** Highest revenue potential with proven willingness to adopt CPA models and AI optimization technology.

### 🥈 Secondary Mobile App Companies

**Industry:** Mobile Apps, Gaming, SaaS

**Company Size:** $5M-$50M annual revenue, 25-200 employees

**Key Characteristics:** • **User acquisition focus**: Apps requiring cost-effective user acquisition and retention campaigns
• **Performance metrics expertise**: Teams tracking LTV, CAC, and other mobile-specific KPIs
• **Cross-platform advertising**: Companies already using multiple acquisition channels beyond app stores

**Rationale:** Strong growth potential with natural fit for performance-based TV advertising models.

### 🥉 Tertiary Regional Service Businesses

**Industry:** Healthcare, Fitness, Professional Services

**Company Size:** $2M-$20M annual revenue, 10-100 employees

**Key Characteristics:** • **Local market targeting**: Organizations serving specific geographic regions or communities
• **Membership/acquisition focus**: Businesses needing to reach targeted local audiences for growth
• **Limited TV advertising experience**: Companies new to connected TV but seeking measurable local advertising

**Rationale:** Future opportunity as CTV adoption grows among local businesses seeking measurable outcomes.

## Target Personas

### Persona 1: Sarah, The Scale-Up Performance Marketing Director

*Segment: 🥇 Primary*

**Demographics:**

- Name: **Sarah, The Scale-Up Performance Marketing Director**
- Age: **👤 Age**: 28-35
- Job Title: **💼 Job Title/Role**: Performance Marketing Director or VP of Growth
- Industry: **🏢 Industry**: E-commerce and D2C Consumer Brands
- Company Size: **👥 Company Size**: $25M-$75M revenue, 100-300 employees
- Education: **🎓 Education Degree**: Bachelor's in Marketing or MBA
- Location: **📍 Location**: Major metropolitan areas (NYC, LA, Austin, Seattle)
- Years of Experience: **⏱️ Years of Experience**: 5-10 years in performance marketing

**💭 Motivation:**

Sarah needs to **diversify customer acquisition channels** beyond saturated Facebook and Google platforms. She's frustrated by **rising digital ad costs** and attribution challenges. Her company demands **measurable ROI** from every marketing dollar.

**🎯 Goals:**

- Reduce customer acquisition costs by 30% through new channels
- Achieve 4:1 ROAS on TV advertising campaigns within 6 months
- Build comprehensive attribution model including TV impact

**😤 Pain Points:**

- Facebook and Google CPCs increasing 40% year-over-year
- Cannot prove TV advertising ROI to executive team
- Traditional TV agencies lack transparency and performance focus

### Persona 2: Marcus, The Mobile App Growth Manager

*Segment: 🥈 Secondary*

**Demographics:**

- Name: **Marcus, The Mobile App Growth Manager**
- Age: **👤 Age**: 26-32
- Job Title: **💼 Job Title/Role**: User Acquisition Manager or Head of Growth
- Industry: **🏢 Industry**: Mobile Apps, Gaming, Fintech
- Company Size: **👥 Company Size**: $10M-$40M revenue, 50-150 employees
- Education: **🎓 Education Degree**: Bachelor's in Computer Science or Marketing
- Location: **📍 Location**: Tech hubs (San Francisco, Seattle, Austin, Boston)
- Years of Experience: **⏱️ Years of Experience**: 3-8 years in mobile marketing

**💭 Motivation:**

Marcus must **scale user acquisition** beyond app store optimization and social media. He's pressured to **reduce blended CAC** while maintaining user quality. **Connected TV offers untapped reach** for mobile app discovery.

**🎯 Goals:**

- Acquire 50,000 high-quality users through CTV campaigns
- Decrease blended CAC by 25% across all channels
- Improve Day-30 retention rates for TV-acquired users

**😤 Pain Points:**

- App store ads becoming increasingly competitive and expensive
- Difficulty measuring TV impact on app installs and LTV
- Limited experience with traditional TV advertising buying

### Persona 3: Jennifer, The Regional Healthcare Marketing Manager

*Segment: 🥉 Tertiary*

**Demographics:**

- Name: **Jennifer, The Regional Healthcare Marketing Manager**
- Age: **👤 Age**: 32-45
- Job Title: **💼 Job Title/Role**: Marketing Manager or Director of Business Development
- Industry: **🏢 Industry**: Healthcare Systems, Fitness Centers, Professional Services
- Company Size: **👥 Company Size**: $5M-$15M revenue, 25-75 employees
- Education: **🎓 Education Degree**: Bachelor's in Marketing or Healthcare Administration
- Location: **📍 Location**: Mid-size metropolitan areas and suburbs
- Years of Experience: **⏱️ Years of Experience**: 5-15 years in local marketing

**💭 Motivation:**

Jennifer needs **measurable local advertising** to compete with national chains and online services. She's frustrated by **traditional TV's lack of accountability** and targeting precision. **Community-focused messaging** requires sophisticated local targeting capabilities.

**🎯 Goals:**

- Increase new patient/member acquisition by 40% in target zip codes
- Track advertising ROI with clear attribution to new customers
- Compete effectively against national chains in local market

**😤 Pain Points:**

- Local TV stations cannot provide detailed performance metrics
- Digital ads getting lost among national competitors
- Budget constraints require proven ROI before increasing spend

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# Positioning & Messaging

## Positioning Statement

**tvScientific** is a **performance TV advertising platform** for **data-driven D2C brands and mobile apps** that **delivers guaranteed outcomes through AI optimization and transparent measurement** with/because of **risk-sharing CPA models that improve ROAS by up to 50%**

## Positioning Framework

### 1. Needs and Pain Points

What are their customer's needs and pain points around the problem the product is trying to solve?

• Rising digital advertising costs with Facebook and Google CPCs increasing 40% year-over-year [2] [16]
• Inability to measure and attribute TV advertising ROI to actual business outcomes [18]
• Lack of transparency and control in traditional TV advertising buying processes [11]
• Need to diversify customer acquisition channels beyond saturated digital platforms [13]
• Limited internal expertise for connected TV campaign management and optimization [7]

### 2. Product Features

What product features will address these needs and solve these pain points?

• Self-serve platform combining integrated media buying and measurement with full campaign control [7]
• AI optimization technology that automatically learns and adapts campaigns in real time [18]
• Advanced audience targeting using 150M credit card user transactions for competitive conquest [14]
• Transparent reporting with clear attribution and ROI measurement capabilities [18]
• Pure CPA pricing model where tvScientific takes on media risk to guarantee outcomes [15]

### 3. Key Benefits

What are the key benefits (rational and emotional) of those product features?

• ROAS improvement of up to 50% through sophisticated AI optimization technology [7]
• Complete transparency and confidence in campaign performance with radical reporting clarity [18]
• Risk-free TV advertising through CPA model where platform shares media investment risk [15]
• Accessible TV advertising that makes connected TV campaigns manageable for any team size [2]
• Measurable growth beyond digital channels with proven attribution to business outcomes [16]

### 4. Benefit Pillars

Which of those benefits would be categorized as benefit pillars?

🎯 Performance Guarantee, 🤖 AI-Powered Optimization, 📊 Radical Transparency

### 5. Emotional Benefits

What emotional benefits would the user have when they engage with or use the product?

Core Emotional Promise:
Confidence and control in TV advertising with guaranteed outcomes that eliminate the fear of wasted media spend [15] [18]

Supporting Emotions:
• Relief from digital advertising saturation and rising costs [16]
• Empowerment through accessible TV advertising without requiring agency expertise [2]
• Trust through radical transparency and clear attribution measurement [18]

### 6. Positioning Statement

What are some positioning statements that could reflect its key benefits, product features, and value?

tvScientific is a performance TV advertising platform for data-driven D2C brands and mobile apps that delivers guaranteed outcomes through AI optimization and transparent measurement with risk-sharing CPA models that improve ROAS by up to 50%

### 7. Competitive Differentiation

How do they differentiate from other competitors?

tvScientific is the only CTV platform purpose-built specifically for performance marketers with guaranteed outcome-based pricing [15] [16]

vs. The Trade Desk: Focuses on performance outcomes rather than broad programmatic reach, with CPA risk-sharing model [11]
vs. Samsung DSP: Targets performance-driven SMB market rather than enterprise-scale solutions [12]
vs. MNTN: Offers radical transparency and attribution measurement with AI optimization technology [18]

Key Differentiators:
• Only CTV platform offering pure CPA model with media risk sharing [15]
• AI optimization technology improving ROAS by up to 50% [7]
• Advanced audience targeting using 150M credit card transactions for competitive conquest [14]

## Messaging Guide

| # | Type | Message | Priority |
|---|------|---------|----------|
| 1 | 🎯 Top-Line Message | The first and only CTV platform that guarantees TV advertising outcomes for performance marketers through AI optimization and risk-sharing CPA pricing [15] [16] | Primary |
| 2 | 🎯 Performance Guarantee | We're so confident in making TV work for your brand that we take on the media risk with pure CPA pricing [15] | High |
| 3 | 🎯 Performance Guarantee | Purpose-built for serious performance marketers who demand measurable outcomes from every advertising dollar [16] | High |
| 4 | 🎯 Performance Guarantee | Connected TV advertising that proves its impact within your broader media mix with clear attribution [18] | Medium |
| 5 | 🤖 AI-Powered Optimization | Campaigns automatically learn and adapt in real time, improving ROAS by as much as 50% [7] [18] | High |
| 6 | 🤖 AI-Powered Optimization | Sophisticated optimization technology that makes every TV dollar work harder for your business [7] | High |
| 7 | 🤖 AI-Powered Optimization | AI-driven audience targeting using 150M credit card transactions to reach your competitors' customers [14] | Medium |
| 8 | 📊 Radical Transparency | Full confidence in performance, attribution, and ROI with reporting that shows exactly where your money goes [18] | High |
| 9 | 📊 Radical Transparency | Self-serve platform gives you complete control over campaigns while our AI handles the optimization [7] | High |
| 10 | 📊 Radical Transparency | Clear reporting and automation that helps marketers prove TV's impact with measurable business outcomes [18] | Medium |

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# References

[1] tvScientific - 2025 Company Profile, Team, Funding & Competitors - Tracxn
   https://tracxn.com/d/companies/tvscientific/__QsMXKdIBXQ7vFy7eZ3KgKPbT2cH3yAiCXYZgdsB9iQI

[2] tvScientific - Crunchbase Company Profile & Funding
   https://www.crunchbase.com/organization/tvscientific

[3] tvScientific 2026 Company Profile: Valuation, Funding & Investors | PitchBook
   https://pitchbook.com/profiles/company/462393-55

[4] tvScientific Stock Price, Funding, Valuation, Revenue & Financial Statements
   https://www.cbinsights.com/company/tvscientific/financials

[5] tvScientific - Products, Competitors, Financials, Employees, Headquarters Locations
   https://www.cbinsights.com/company/tvscientific

[6] tvScientific: TV Advertising That Drives Sales
   https://www.tvscientific.com

[7] Connected TV Platform | tvScientific
   https://www.tvscientific.com/connected-tv-platform

[8] Connected TV Advertising | tvScientific
   https://www.tvscientific.com/insight/connected-tv-advertising

[9] Connected TV Advertising Platform | tvScientific Platform
   https://www.tvscientific.com/tvscientific-platform

[10] 7 Best The Trade Desk Competitors For Advertising
   https://www.vibe.co/blog/how-to/trade-desk-competitors

[11] The Trade Desk vs. tvScientific: Who’s leading the way in Performance TV optimization?
   https://www.tvscientific.com/insight/the-trade-desk-alternative

[12] r/advertising on Reddit: Vibe vs Samsung DSP vs The Trade Desk: which self-serve CTV platforms are capable of serving enterprise brands?
   https://www.reddit.com/r/advertising/comments/1rdishx/vibe_vs_samsung_dsp_vs_the_trade_desk_which/

[13] Customer Case Studies | tvScientific
   https://www.tvscientific.com/customers

[14] What makes tvScientific different?
   https://www.tvscientific.com/insight/what-makes-tvscientific-different

[15] tvScientific affiliate technology spotlight | Awin
   https://www.awin.com/us/publishers/case-studies/technology-partner-spotlight-tvscientific

[16] tvScientific B2B Case Studies & Customer Successes
   https://www.casestudies.com/company/tvscientific

[17] Audience Targeting | Premium TV Advertising with tvScientific
   https://www.tvscientific.com/targeting

[18] tvScientific Reviews 2025: Details, Pricing, & Features | G2
   https://www.g2.com/products/tvscientific/reviews

[19] How to Measure Customer Satisfaction (+Key Metrics to Track)
   https://learn.g2.com/measuring-customer-satisfaction

[20] Featured Customers | Find B2B & SaaS Software & Services - Reviews, Testimonials & Case Studies
   https://www.featuredcustomers.com/vendor/tvscientific