Policymakers have been pushing back against platforms that collect consumer data, while implementing laws requiring companies to be transparent about the details and business purposes they collect. For example, last year, Virginia passed the Colorado Data Protection Act, which requires businesses to obtain consent before processing sensitive information, when that information can be sold, and customer opt-outs. While California, Colorado and the European Union have similar frameworks, other states and countries are considering similar.
Some marketers argue that these protections make it difficult to suggest or predict the products that customers might want. But Alex Elias says it shouldn’t be like that. He is the founder of Qloo, a brand that uses AI to analyze customer preference data to make recommendations, including entertainment and fitness recommendations.
“The regulatory and platform environment surrounding privacy has severely limited methods of understanding consumers based on identity. This has had seismic implications across sectors from tech to consumer packaged goods, and has led many companies to seek to collect their own first-party data, which is at great risk,” Elias said. “At the same time, consumer tastes are becoming more fragmented and granular in their profile, with increased media and music consumption making it harder to reach consumers,” he told TechCrunch in an email interview.
Elias co-founded Qloo with Jay Alger to solve these dual problems. “Qloo can illuminate audience preferences, data improves sales efficiency, drives conversions and increases the bottom line,” he said. Most companies interested in better understanding consumer tastes can benefit from Qloo.
As part of a Series B round led by Eldridge and AXA Venture Partners, Qloo today secured a new round of funding of $15 million to demonstrate the confidence it received from investors. It brings the company’s total revenue to $30 million, which includes celebrities such as actor Leonardo DiCaprio, Elton John and Starwood Hotels founder Barry Sternlich.
Qloo says its API matches more than 575 million “entities,” including movies, books, restaurants and songs, to predict consumer tastes for “dozens” of corporate clients such as PepsiCo and Elton John’s music company Rocket Enterprise. The API powers TasteDive, a social media app with a built-in entertainment recommendation engine for movies, TV shows, music, video games and books purchased by Qloo in 2019.
According to Elias, Qloo does not use any personally identifiable information, keeps all inquiries “fun” and refuses to store the identities of potential customers. The data is anonymized and encrypted, and the platform’s data handling is “fully compliant” with regulations, including the GDPR and California’s Consumer Privacy Act, says Elias.
The details are a little fuzzy, but at a high level, Qloo uses a knowledge base of customer preferences to fine-tune algorithms that provide product recommendations and insights. For example, Qloo can create “taste associations” for entities (such as music artists) that overlap geographically. The platform can also generate statements about the difference in music taste between a Nike sneaker customer and a Vans customer about the choice of component set or comparison of components.
Customers armed with Qloo and with Snowflake, Tableau and other existing data platforms can better solve problems such as sales, reducing ad spend and choosing retail locations, Elias said.
Image Credits: Hello
“[Qloo’s] AI is aligned with many criteria, so end customers can flexibly adjust the algorithm’s weighting based on how ‘new’ or ‘expected’ they want the flavor correlation to be for the end consumer. “For example, a streaming client in Asia was able to prioritize region-specific results over global popular recommendations and adjust the algorithm accordingly.
Elias acknowledges that countless companies, including Mastercard-owned Dynamic Yield and RichRelevance, have tried to break into personalization and recommendations through AI. But it sees Qloo’s platform as complementary to competitors that operate more general recommendation engines, such as Amazon Personalize, Azure Recommendations API and Google Cloud’s Recommendations AI.
“Qloo is differentiated by its deep data set and knowledge base across domains including music, products, travel and more. This allows Qloo to help its customers achieve significant personalization with the least amount of context provided,” said Elias. “Qloo is a valuable competitor to traditional, more expensive awareness tools like focus groups or surveys because it can quickly and efficiently provide ad hoc insights based on much larger panels, such as ‘What movies do people on the Upper East Side watch?’ Do you like it as much as Lululemon?’
The Series B proceeds will support the launch of Qloo’s new product, Elias said—a “lite” version of the platform that offers subscriptions with a visual interface designed for tech-savvy users. Beyond that, the funding will bolster product development, expand Qloo’s 30-person team by more than 30% in the coming months, and build the company’s sales channels.
Elias grumbled when asked about his income. But Qloo says it has bucked the economic trend so far, thanks in part to recovering demand in industries like travel and entertainment.
“In the two years since the outbreak, Qloo has seen increased demand for its services, leading to higher levels of revenue and API usage,” said Elias. “Fundamental tailwinds, including a move toward privacy, focus on revenue growth, and widespread adoption of AI, have far outweighed headwinds from the macro environment and broader technology reviews. Qloo has managed very lean burn rates and is approaching profitability.”
