Jacquard uses a specialized AI engine ("Language") combined with predictive performance modeling ("Neural²") to optimize and tailor messaging for engagement and reliability. The result? Statistically higher open and clickthrough rates and reduced content bottlenecks
- Marketing & Brand Teams: Automate consistent, brand-compliant messaging.
- Growth & CRM Managers: Generate high-performance copy at scale.
- Content Operations: Remove manual bottlenecks in campaign creation.
- Enterprises: Apply uniform tone across international teams.
- Data-Driven Marketers: Leverage predictive models to decide what content to send.
How to Use Jacquard?
- Book a Demo: Start with consulting and onboarding.
- Set Brand Voice Profile: Define tone and guidelines in the platform.
- Import Data & Audience Segments: Connect to CRM or event triggers.
- Generate and Calibrate Copy: AI suggests variants; you refine.
- Deploy Across Channels: Push through email, SMS, in-app, or push.
- Analyze & Optimize: Use stats and predictive analytics to refine messaging.
- Brand-Calibrated AI Copy: Language² generates on-brand copy from a single brief.
- Predictive Engagement Engine: Neural² models forecast top performers before sending.
- Combinatorial Copy Scaling: Automates message permutations tailored to context and segments.
- Performance-First Design: Click and open lift proven via A/B tests and data-driven calibration.
- Creative + Compliance: Ensures brand consistency and legal alignment without manual oversight.
- Delivers measurable uplift in campaign performance.
- Maintains strict brand voice at scale.
- Reduces creative workload with AI efficiency.
- Predictive engine avoids content fatigue and underperformance.
- High cost—enterprise-level pricing required.
- Best suited for large teams—not SMBs.
- Requires initial data integration and setup time.
Base Platforrm
$36k/year
- One Brand Calibration
- One Language Calibration
- One Integration
- One Business Unit
- 200 UMVs
Growth Tiers
Custom pricing/year
- Contact us.
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Editorial Note
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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