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Award-Winning Data Science Startup conDati Completes $4.75 Million A Round

The Conclusion of the Round Is the Latest in a Series of Recent Highlights for conDati

conDati  Inc., a provider of next-generation analytics for digital marketing, announced on Tuesday the completion of its Series A financing, bringing the total round to $4.75 million.

The conclusion of the round is the latest in a series of recent highlights for conDati, including receiving an award for applying machine learning to marketing ROI and bringing multiple customers into pre-launch deployments. The completed financing positions the company for a commercial launch of its Big Data as a Service (BDaaS) solutions for digital marketing later this spring.

“We already have companies in e-commerce, higher education, B2B and digital media actively using our solution,” noted CEO and founder Ken Gardner in an interview. “Our momentum is building, and we are eager to get to the broader market and help companies improve their return on marketing. The complete and current visibility we deliver in conDati Marketing Analytics gives marketers entirely new abilities to understand, predict and improve the financial performance of all their digital marketing campaigns.”

Also Read: Move Over Conventional SEO Conferences, It’s Time We UnGagged!

Founded in summer 2017, conDati’s latest financing was led by The Entrepreneurs’ Funds (TEF), of San Mateo, California. “Marketing departments have been forced to make do with screen-scraping, spreadsheets, and DIY projects for far too long,” notes Jeff Webber, Managing Director of TEF, who also led conDati’s previous financing. “conDati has made great progress in applying data science to Marketing to create what is going to be a transformational solution.”

“We focused the initial funding on applying our data science and machine learning techniques to marketing and building them into the application,” said Gardner. “With this second round of funding, we are ready to shake up the martech landscape.”

Recommended Read: The Great Rush: Preparing for the Data Science Success

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