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Content discovery platform Dable closes $12 million Series C at $90 million valuation to accelerate its global expansion

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A photo showing articles recommended by content discovery platform Dable on a smartphone
Image Credits: Dable (opens in a new window)

Launched in South Korea five years ago, content discovery platform Dable now serves a total of six markets in Asia. Now it plans to speed up the pace of its expansion, with six new markets in the region planned for this year, before entering European countries and the United States. Dable announced today that it has raised a $12 million Series C at a valuation of $90 million, led by South Korean venture capital firm SV Investment. Other participants included KB Investment and K2 Investment, as well as returning investor Kakao Ventures, a subsidiary of Kakao Corporation, one of South Korea’s largest internet firms.

Dable (the name is a combination of “data” and “able”) currently serves more than 2,500 media outlets in South Korea, Japan, Taiwan, Indonesia, Vietnam and Malaysia. It has subsidiaries in Taiwan, which accounts for 70% of its overseas sales, and Indonesia.

The Series C brings Dable’s total funding so far to $20.5 million. So far, the company has taken a gradual approach to international expansion, co-founder and chief executive officer Chaehyun Lee told TechCrunch, first entering one or two markets and then waiting for business there to stabilize. In 2021, however, it plans to use its Series C to speed up the pace of its expansion, launching in Hong Kong, Singapore, Thailand, mainland China, Australia and Turkey before entering markets in Europe and the United States, too.

The company’s goal is to become the “most utilized personalized recommendation platform in at last 30 countries by 2024.” Lee said it also has plans to transform into a media tech company by launching a content management system (CMS) next year.

Dable currently claims an average annual sales growth rate since founding of more than 50%, and says it reached $27.5 million in sales in 2020, up from 63% the previous year. Each month, it has a total of 540 million unique users and recommends five billion pieces of content, resulting in more than 100 million clicks. Dable also says its average annual sales growth rate since founding is more than 50%, and in that 2020, it reached $27.5 million in sales, up 63% from the previous year.

Before launching Dable, Lee and three other members of its founding team worked at RecoPick, a recommendation engine developer operated by SK Telecom subsidiary SK Planet. For media outlets, Dable offers two big data and machine learning-based products: Dable News to make personalized recommendations of content, including articles, to visitors, and Dable Native Ad, which draws on ad networks including Google, MSN and Kakao.

A third product, called karamel.ai, is an ad-targeting solution for e-commerce platforms that also makes personalized product recommendations.

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Dable’s main rivals include Taboola and Outbrain, both of which are headquartered in New York (and recently called off a merger), but also do business in Asian markets, and Tokyo-based Popin, which also serves clients in Japan and Taiwan.

Lee said Dable proves the competitiveness of its products by running A/B tests to compare the performance of competitors against Dable’s recommendations and see which one results in the most clickthroughs. It also does A/B testing to compare the performance of articles picked by editors against ones that were recommended by Dable’s algorithms.

Dable also provides algorithms that allow clients more flexibility in what kind of personalized content they display, which is a selling point as media companies try to recover from the massive drop in ad spending precipitated by the COVID-19 pandemic. For example, Dable’s Related Articles algorithm is based on content that visitors have already viewed, while its Perused Article algorithm gauges how interested visitors are in certain articles based on metrics like how much time they spent reading them. It also has another algorithm that displays the most viewed articles based on gender and age groups.

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