Claravine: Use-Cases, Insights and Reviews | 2024 Cuspera

Claravine Launches Industry-First Data Standards Metric and New Solutions to Optimize Data Quality

Claravine introduces new data standards metrics and AI solutions to enhance data quality and content management. The company is recognized as a fast-growing firm and partners with Slalom to tackle marketing taxonomy challenges.

4 new ways to speed, deepen, and extend marketing metadata value

Claravine introduces AI to enhance marketing metadata, launches new data standards, and partners with Slalom to tackle marketing challenges. It ranks 479th on Deloitte's Fast 500 and appears on the Inc. 5000 list for the fifth year.

Claravine Ranked Number 479 Fastest-Growing Company in North America on the 2024 Deloitte Technology Fast 500

Claravine is recognized as the 479th fastest-growing company in North America in the 2024 Deloitte Technology Fast 500.

Capabilities for Detailed, Connected Asset Metadata

Claravine enhances content and creative management with new AI capabilities and acquires Netra, an AI-powered content classification company.

The Claravine Approach to Data Design

Trying to organize your marketing metadata is a complex endeavor. But there’s a key element working behind the scenes that can make or break an organization’s ability to leverage marketing data effectively: data design. Data design is at the heart of everything we do here at Claravine, and we believe this unsung hero deserves its moment in the spotlight. So in this article, we’ll explore what data design is, why it matters for marketers, and how our time-tested approach to data design can help every team improve the quality and consistency of their marketing data.   Defining data design — and why it matters Data design is a critical aspect of creating efficient and well-structured datasets that allow you to store and manage data effectively. Thoughtfully designing the architecture, tables, relationships, and constraints within a dataset can help ensure data integrity and optimal performance. For marketing organizations, this means creating datasets that can seamlessly handle vast amounts of campaign data, customer information, and performance…

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Overcoming the Challenges of Scaling Generative AI in the Enterprise

Generative AI is ushering in a new era of possibility for enterprise marketers — and increasing the urgency to solve long standing challenges. GenAI promises a fast, efficient path forward to meet the ever-increasing demand for personalized content. But as enterprise marketers understand, managing large volumes of content assets across complex systems is no simple task. Tagging, tracking, serving, and measuring content across its lifecycle is already a significant roadblock to optimizing campaign performance. According to our latest State of Modern Marketing Data Standards report, only 13% of advertisers were very confident in their ability to tie campaign performance or ROI back to specific ad creative. With an influx of AI-generated content on the horizon, marketers have zero time to waste. Without a better approach to scaling content management, enterprise orgs will struggle to ensure the quality of their content and the accuracy of their campaign execution, support increased personalization, and keep pace with reporting needs. Read on for a deep dive: where we…

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