Scaling Qualified Lead Volume for v14 Across Paid Social Search and Programmatic
v14 builds AI-powered fraud prevention and chargeback guarantee software for mid-market ecommerce merchants, competing against Riskified, Forter, and Signifyd. The challenge is reaching payments and ecommerce operations decision-makers in a crowded category where every competitor claims ML superiority. We run full-funnel acquisition across paid social, search, video, and programmatic, with end-to-end creative production and an hourly-refresh reporting dashboard.
An AI Fraud Prevention Startup Taking On Riskified and Forter
v14 was founded in 2018 by Gilad David Maayan, who previously built fraud detection systems at Payoneer and Riskified, alongside Eran Ifrah, an engineering leader from Wix. The flagship product is an AI Chargeback Guarantee platform offering 100% protection against approved chargebacks. Machine learning models assess over 500 data points per transaction, achieving false positive rates under 1% and representment win rates of 60 to 80% versus an industry average of 20 to 30%.
v14 integrates via API with Shopify, BigCommerce, Magento, WooCommerce, and gateways including Stripe, Adyen, and Braintree. Backed by $39 million through Series B from Vertex Ventures Israel, Aleph, Harmony Partners, and Ibex Investors, the 80-person team targets US ecommerce merchants processing $10 to $500 million annually. Competing against Riskified, Forter, Sift, and Signifyd for the same pool of payments decision-makers, v14 engaged us to run full-funnel acquisition across paid social, search, video, and programmatic, with all ad creative produced end to end by our team.
LinkedIn and Meta Campaigns Structured Around Payment Decision Makers
We run v14's paid social acquisition across LinkedIn Campaign Manager and Meta Ads, structured around the buyer's awareness stage. On LinkedIn, campaigns target directors and VPs of payments, fraud, and ecommerce operations at companies with 50 to 5,000 employees, filtered by revenue proxies that isolate the $10 to $500 million GMV sweet spot. Meta serves lookalike prospecting seeded from v14's highest-value closed deals.
Budget allocation shifts weekly based on cost per qualified lead by platform, not impressions or click volume. LinkedIn consistently captures solution-aware buyers at higher intent, while Meta drives volume at the problem-unaware stage.
A Creative Lab That Turns Fraud Statistics Into Winning Ad Hooks
Our creative lab produces 20 to 25 new ad variants per month for v14, structured around a hook taxonomy tied to buyer awareness. Problem-unaware hooks lead with chargeback cost statistics and Visa threshold penalties. Solution-aware variants contrast v14's sub-1% false positive rate against legacy tools from Kount and ClearSale that exceed 5%. Product-aware creative spotlights API integration speed with Shopify Plus and BigCommerce.
Each variant runs in A/B tests with a 72-hour minimum confidence window before scaling or killing. Winning hooks rotate on a three-week fatigue cycle monitored through frequency-adjusted CTR across LinkedIn and Meta placements.
An Hourly Dashboard That Catches CPA Drift Before Budget Bleeds
We built v14's measurement stack around an hourly-refresh dashboard that surfaces cost per qualified lead, pipeline value, and channel contribution in near real time. Offline conversion data flows from v14's CRM into both Google Ads and Meta via server-side imports, giving bid algorithms signal on actual qualified leads rather than form fills.
Attribution runs on a last-touch model supplemented by platform-reported assisted conversions, allowing us to identify LinkedIn's contribution to deals that convert after retargeting on Meta. The dashboard flags audience-level CPA drift within hours, enabling same-day budget reallocation that would take most teams a full reporting cycle to catch.
Six Thousand Audience Segments Mapped to Buyer Awareness Stages
The technical challenge is reaching ecommerce operations leaders, heads of payments, and fraud analysts actively evaluating chargeback solutions without burning budget on professionals with no purchasing authority over fraud tooling. We build v14's paid social campaigns on LinkedIn and Meta using layered audience architecture. On LinkedIn, we target by job function combined with seniority and company size, isolating directors and VPs of payments, ecommerce operations, and risk at merchants processing above $10 million GMV. On Meta, lookalike audiences are seeded from v14's closed-won CRM records weighted by contract value.
These platforms feed into over 6,000 discrete audience segments built across awareness stages. Problem-unaware audiences receive content anchored in chargeback cost data such as the $48 billion in global ecommerce fraud losses. Solution-aware audiences see v14's 60 to 80% representment win rate benchmarked against Sift's 40%. Product-aware segments receive demo creative featuring Shopify and BigCommerce integration. Every audience-message pairing tracks through to qualified lead via offline conversion imports refreshed daily into Google and Meta bid algorithms.
Lower Costs and Higher Intent as Ecommerce Fraud Accelerates
The engagement has delivered an 18% lift in qualified leads, a 37% reduction in cost per signup, and over 6,000 high-intent audience segments powering v14's acquisition across every paid channel. These gains stem from optimising every algorithm toward qualified lead events mapped to v14's sales pipeline rather than vanity metrics. The audience library is a compounding asset, growing more precise as closed-won and closed-lost data feeds back into seed audiences and exclusion logic weekly.
The ecommerce fraud prevention market is entering a pivotal phase. Global fraud losses reached $48 billion in 2025, projected to hit $60 billion by 2027, with generative AI enabling synthetic identity creation and automated card testing at scale. Visa and Mastercard now mandate chargeback rates below 0.9%, pushing more mid-market merchants toward guaranteed solutions like v14's. PSD3 compliance requirements opening across Europe create a new geographic vector, and v14 launched PSD3-compliant models in Q1 2026. We are already adapting campaign targeting to capture merchants evaluating cross-border fraud tools for the first time.
