The ‘Drama’ of Sifting through Marketing Data

The ‘Drama’ of Sifting through Marketing Data

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Claravine’s expressed goal in acquiring AI content-classification company Netra this month is to take “the drama out of marketing data.” Using its Data Standards Cloud platform, Claravine ensures that data is accurate, which in turn enables teams to measure results, pivot on execution, and improve performance within a consistent framework. The Utah-based Series B company also establishes and applies data standards for workflows, execution platforms, and analytics systems.

Netra is an AI-powered content classification company that can auto-generate robust and clean data classification for content assets (text, imagery, and video).

Claravine Chief Growth Officer Chris Comstock talked more in-depth about how the two companies will work together.

Explain what data standards are and how it can be automated.

Data standards create a common language of naming conventions, values, and other aspects of individual data assets. It’s a concept crucial for any marketing, data, or measurement strategy to be effective and competitive.

Data standards are the key to breaking down data silos and creating interoperability, or the ability to exchange data between systems and teams. The application of these standards by each customer allows all the data platforms to work together more effectively. By having a single source of truth, teams can spend less time cleaning up data and more time on the customer and their business.

What business problem does Claravine solve for its customers?

Claravine [is known as] The Data Standards Company and aims to give people, teams, and technology a shared understanding of their data. Brands and agencies can deliver on the promise of modern marketing by standardizing taxonomies, naming conventions, and metadata across all digital experiences at the source of data creation. The Data Standards Cloud empowers a proactive approach to marketing metadata for fast, accurate, and rich business insights that help deliver personalized experiences that customers want.

How do marketing, operations, and creative teams benefit from data standards and their automation?

Data quality has evolved from a nice-to-have to a need-to-have. The single greatest factor in improving data quality and data use lies in consistent, repeatable, and sticky data standards. By creating a common language of naming conventions, values, and other aspects of individual data assets, data standards become an irreplaceable asset of any marketing, data, and measurement strategy. Even the most diligent of data-science and marketing teams can’t retroactively clean every error and inconsistency; fixing the issues at the source is the most effective way to alleviate this burden from marketing, operations, and creative teams.

Why did Claravine select Netra to acquire as opposed to another company in the space?

Netra shared a common approach to creating a standard set of metadata and taxonomy outputs from digital assets with their API. Both companies were aligned on working across technology platforms and understanding the need for a way to centrally control metadata. Netra initially focused on video, making it well-positioned to help both advertisers and publishers as user-generated content continues to increase. This latest acquisition supports Claravine’s goal of taking the drama out of marketing data by putting AI in the hands of marketing teams for data classification across text, creative, audio, and video assets – which are growing dramatically with the rise of generative AI platforms.

Could marketing professionals not analyze and extract metadata from videos and images before the Netra acquisition?

There are capabilities for extracting metadata and tagging content from Google and Amazon, but they are often used by different teams. Many platforms have some of these capabilities as well, but it has been difficult for marketing and content teams to control how the metadata is used and applied. The fragmentation, much like the martech and adtech ecosystem, creates problems for measurement and analytics teams as they are the ones left to make sense of all the datasets. Lots of companies are still wasting mountains of marketing data and don’t know where to start making better data-driven decisions because this is still a human-powered process.

Netra is among a few companies that is focused on helping marketers to better use digital assets, which are only growing in importance for marketers. With generative AI being increasingly adopted, visual assets are growing in number for every marketing team. Claravine saw a need to enhance its capabilities in this area and offer clients the best technology out there to set data standards for digital assets.

Will this acquisition create redundancies of staff or add staff?

The full Netra team, including its CEO, Amit Phansalkar, is joining Claravine’s remote workforce. With the inclusion of Netra’s team, Claravine will have over 50 employees. Netra’s series of APIs will be seamlessly integrated into Claravine’s The Data Standard Cloud with Claravine branding and interface. All Claravine employees will be trained on Netra’s APIs too.

How can Netra support Claravine’s customers?

Automating the tagging for teams is only the beginning, as Claravine believes there are many other ways to help automate the activation of data standards for marketing and creative teams. The problem facing these teams today is only growing more critical as privacy-centric marketing becomes the reality in the next year and as Google finally resets the measurement landscape with the depreciation of third-party cookies in Chrome.

Who are Claravine’s customers?

Used by Fortune 1000 companies such as Carhartt and Under Armour, Claravine’s collaborative user interface and strategic integrations with top marketing and advertising platforms enables global organizations to define, apply and connect standards across their ecosystem for faster decisions, greater agility and increased return-on-investment for their digital advertising dollars.

Kathleen Sampey