Lee Newspaper Chain Takes Stake in Milwaukee Adtech Startup Okanjo

Okanjo's "Product Match" scans articles on publishers’ websites for keywords, and then places ads next to the most relevant content. Readers can then click the "buy now" button and purchase the items without leaving the page. Photo courtesy of Okanjo.

The rise of the Internet has had a drastic effect on print media, and there seems to be no going back.

For today’s journalists, that means nightly or weekly deadlines often don’t loom as large as they did before newspapers gained the ability to publish at all hours.

Their business-side colleagues have also had to navigate a changing landscape, as free online services like Craigslist and eBay (NASDAQ: EBAY) have reduced demand for paid listings in the classifieds. But with the shift from paper to pixels, space for advertisements has become more dynamic. That’s led to the advent of technologies that determine what ads readers should see based on who they are and what content they’re consuming.

One company that’s helping news outlets move toward data-driven ad placement is Okanjo. On Monday, the Milwaukee-based startup announced it was expanding its partnership with Lee Enterprises (NYSE: LEE), a newspaper chain based in Davenport, IA, whose holdings include the Wisconsin State Journal and several other Badger State publications.

Under the terms of the deal, Lee will provide funding to Okanjo in exchange for shares in the startup, says Bethany Grabher, Okanjo’s vice president of marketing and business development. She declined to reveal the size of Lee’s investment or the equity stake it will be receiving.

James Green, vice president of digital at Lee Enterprises, will be joining Okanjo’s board, Grabher says.

Okanjo’s software products are currently being used at six of the 50 daily newspapers Lee owns outright or has a partial stake in, Grabher says. Okanjo leaders hope to bring its products to the remaining 44 publications by September, she says.

Grabher says that the technology the startup has developed places digital ads alongside articles, videos, and other media based on the content and reader data shared by the publication. She says that Okanjo doesn’t create unique identifiers to track the behavior of individual consumers, as some retailers appear to have done.

“We are not keeping profiles,” Grabher says.

But given that Okanjo’s software can also factor in “first-party” data—in other words, information news sites have collected from readers’ clicks, scrolls, and keystrokes—there doesn’t seem to be a complete guarantee of anonymity for users.

Many of the ads on Google (NASDAQ: GOOGL) search results pages are the byproduct of auctions and “quality scores,” meaning their relevance to users and how often they’re clicked on when displayed. Grabher says that while Okanjo has built a tool allowing customers to “run eBay-style auctions” connecting local buyers and sellers, its core ad placement technology does not involve a bidding process.

“We read a publisher’s content for keywords, sentiment, and context,” she says. “Based on what the content says, from our pool of advertiser products we pull in the most relevant products.”

Another feature of Okanjo-generated ads is the presence of an embedded “buy now” button that allows users to purchase a product without having to jump to another Web page.

Before striking the latest agreement with Lee Enterprises, Okanjo had raised $ 3.2 million from investors. Grabher says the startup intends to raise a Series A round later this year or in early 2017.

Some of the headwinds Okanjo might face are competition from other adtech companies, and the general decline in revenues across the print media industry.

Moreover, some publications are putting their content where there are more eyeballs—for instance, on Facebook (NASDAQ: FB), with its 1.6 billion users. Last month, the social network began allowing any publisher to host content directly on Facebook as part of its Instant Articles program.

For now, Okanjo is concentrating on further development of its technology, which Grabher says was built on IBM’s Watson computing technology. She says that the startup currently has about 20 full-time employees and has assembled a five-person data science team that’s working to improve the software’s ability to understand context, among other initiatives.

“We want to shift focus to be more of a data company,” Grabher says.

 

Xconomy

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