Paris-based ecommerce analytics platform ContentSquare has raised a $42 million Series B round from a series of investors including US VC firm Canaan and Highland Europe.
ContentSquare previously had raised $20 million, bringing it to a total of $62 million after this round.
The company will use the financing to support research and development of machine learning and AI. ContentSquare already employs about 70 developers and data scientists.
The company will also leverage its new financing to expand its sales, marketing and product teams globally with an emphasis on expanding US operations.
Last year, ContentSquare hired about 30 people in the US, according to founder and CEO Jonathan Cherki.
“We plan to keep growing in the US because it is our main market today and the biggest market not just in ecommerce and retail, but luxury, banking, cosmetics and automotive,” Cherki said.
Instead of competing with larger enterprise companies like Adobe, which also offer web experience and analytics tools within a marketing cloud stack, ContentSquare claims it’s more likely to partner with them.
“Most of our customers use Adobe Analytics or Google Premium,” Cherki said. “Today, the cost of acquisition is very high. And while mobile traffic is strong, conversions are low. So we see more and more brands wanting to understand user behavior more deeply.”
ContentSquare uses machine learning to serve up recommendations for consumers or suggestions for the user experience based on behavioral data onsite or in-app, such as clicks, swipes or time spent on a video or article content.
The platform claims that unlike large enterprise analytics tools, its solution is designed for the average business user, not data scientists or systems experts.
ContentSquare also aims to meet the needs of different business users, including CRM and customer acquisition teams, design, ecommerce and digital marketing.
“If you’re a site experience designer and you want to understand [different paths to conversion], you do not need a data scientist to obtain a report every week,” Cherki said. “A lot of analytics technologies are built for analysts, not everyone.”