Outlier raises $22.1 million to spot anomalies in business data with AI

Machine learning algorithms aren’t merely technological novelties relegated to tasks like picking out faces in crowded places. Indeed, in the enterprise, they’ve shown an aptitude for surfacing patterns and relationships that otherwise might have gone uncloaked. Oakland, California-based exemplifies this — its business analysis platform extracts data from internal and external sources and analyzes it to spot critical changes in behavior. Investors see potential — a year after experiencing 400% growth, Outlier today announced that it has raised $22.1 million in a series B funding round led by Emergence with participation from existing investors Ridge Ventures, 11.2 Capital, First Round Capital, Homebrew, Susa Ventures, and SV Angel, bringing its total raised to over $30 million.

Cofounder and CEO Sean Byrnes says the funding will be used to accelerate growth and make strategic hires across Outlier’s Oakland headquarters, Virginia Beach, Virginia, and European offices. “Today’s businesses are wrestling with increasing volumes of data and an inability to analyze all of it to glean powerful insights. Outlier enables business leaders across various functions to make smart decisions quickly by providing … insights daily,” he said. “We appreciate the support of our investors who understand the importance and value of automated business analysis.”

Outlier — which Byrnes, who sold analytics startup Flurry to Yahoo six years ago for north of $200 million, founded in 2017 with former Googler Michael Kim — develops and maintains an eponymous service that watches over business data in real time and lets managers, executives, and team members know when unexpected things occur. It plugs into platforms like Google Analytics, SendGrid, Mandrill, Snowflake, Mixpanel, Adobe Cloud, Salesforce, Stripe, and Zendesk to extract key dimensions and make sense of trends involving various customer segments, using this information to highlight only the four to five most important changes happening daily.

Among other use cases, Outlier can optimize marketing programs, track changes in buyer segments, find product development issues, and identify large patterns of fraud. Byrnes says that to date, the platform has analyzed over four billion metrics from customers like Jack Rogers and Swarovski in segments including consumer packaged goods, e-commerce, retail, hospitality, life sciences and financial services, and he noted that Outlier this year partnered with nonprofit In-Q-Tel to identify unexpected patterns in government agency data sets.

“Outlier has improved the way we use our data. Celebrity Cruises has more than 30,000 partners, 30 cabin types and over 1,000 cruises on sale at any given time,” said vice president of business intelligence at Celebrity Cruises Matt Maule, an Outlier client. “Quickly analyzing all that data and the various combinations of data would be impossible without Outlier. It helps us understand without bias or a hypothesis what we should focus on and what we shouldn’t be concerned over.”

In its recent Augmented Analytics Is the Future of Analytics report, Gartner predicts that by 2021, “augmented analytics” like that of Outlier will drive new purchases of analytics and business intelligence well as data science and machine learning platforms. Assuming this comes to pass, Outlier’s prospects in the $168.8 billion business analytics market look bright.

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