This feature has been written in partnership with Bridged Media. Hear more in the Media Briefs episode with Bridged Media CEO Maanas Mediratta, discussing why making AI tools more accessible to more publishers will help the whole ecosystem.
For most publishers who haven’t yet adopted AI, identifying a use case they can start with is usually the biggest roadblock, according to Bridged Media’s Maanas Mediratta. However, he also sees a problem with practical access to the tools publishers could use to support their nascent AI ambitions.
It’s no secret that most current AI innovation is being driven by Big Tech. “Whether you’re talking about generative AI, NLP or machine learning algorithms, they’re primarily used by very, very few players – mainly Google and Facebook,” Mediratta says.
The inaccessibility of Big Tech’s black-box algorithms – often targeted at industries like finance and ecommerce – is compounded by the fact that publishers operate with a dizzying array of business models. “Tools designed for media companies often won’t satisfy individual companies’ goals and needs,” Mediratta explains.
He believes that’s why the publishers that have been successful using AI so far are huge brands like The Wall Street Journal or The New York Times. “It can take years to build a proper algorithm and cost millions – 99% of publishers cannot do this,” says Mediratta. “Even building a proof of concept is not a simple thing.”
Access to AI
Spotting the problem during his time as a media consultant, Mediratta founded Bridged Media with the objective of democratising access to AI. He saw that in the media sector AI is most often used to understand what audiences want. “To engage them, to show them an offer, to really analyse them,” he explains. “It might even be used to show them ads, directly or programmatically.”
In that context, Bridged’s initial focus has been to develop publisher-first AI tools to detect where the audience is most likely to engage. Through a single line of code its algorithm introduces action cards that prompt readers to register, subscribe, or read more, helping publishers establish richer relationships.
The company takes a two-pronged approach to making AI functionality available to publishers.
The first is to reduce the level of internal expertise needed to create a proof of concept. The second is to deliver predefined modules, out-of-the box AI solutions, that can be integrated with any content infrastructure with some ‘tweaks and configurations’
Pay-as-you-go AI
Bridged works on a SaaS, pay-as-you-go, model. “We don’t want to charge a bomb, like $300,000 a year, to build these kinds of algorithms,” Mediratta explains. “We want it to be accessible to everyone. Our tools can be used by publishers that have 50,000 impressions through to publishers that have 50 million.”
While Mediratta sees a proliferation of no-code AI solutions, they are not specifically tailored for publishers. He says most of the tools that exist are for e-commerce applications or big market-value industries. “Fashion is one where AI is big, and finance,” he says. “But when you talk about publishers, there is an intrinsic problem when you think about creating no-code solutions.”
That problem, especially in an industry where revenues are generally falling, is the broad range of business models operated by publishers looking to maintain the bottom line.
Mediratta describes this as publishing’s ‘Unicorn’ problem, not in the sense of billion-dollar startups, but from the perspective of the unique revenue mixes deployed within individual organisations. “I don’t know if I’ve met two publishers that have identical business models,” he says.
However, the diversified revenue mix used by most medium to large scale publishers also makes it imperative to know where, when and how to engage audiences. “When you look at these three basic fundamental blocks for a publisher, what we have done is built our own models to solve these three problems.”
ROI positive
A survey of 300 publishers conducted by Bridged showed that 95% wanted to get started with AI. Mediratta says the best way for them to begin taking advantage of AI is to identify a single ROI-positive use case, develop a solution and monitor the return.
“If you’re able to crack that, then it becomes a flywheel. You can create different proof of concepts given the accessibility of AI and really benefit from the AI ecosystem – not being that 95%, being the 5% that has already implemented.”
He uses the example of a sports publisher that wanted to collect more emails. Using Bridged’s AI solutions, they were able to find where visitors were most likely to register an email address. The system then identifies the best offer to deliver depending on the publisher’s focus, from email registration to increased engagement.
Mediratta says the key step is to understand what is working. “When is the user most likely to take this action? What is the right screen to show them? What is the right offer to show them? To learn from that experience, we can analyse it and create a full use case.”
Implementing the AI increased the sports publisher’s email collection rate by 10 times by identifying trigger points for their audience. “Understanding their audience, using AI, we were able to create a very customised and personalised journey,” says Mediratta. “It eliminates the guesswork.”
The same approach works for surfacing high-value content, showing ads or generating additional page views through content recirculation. With recirculation specifically, the AI estimates the exact moment when a site visitor will leave. It then tries to re-engage them by surfacing articles that are very specific to their interest. Spotlighting a Spanish local-news publisher working with Bridged, Mediratta says: “We have increased recirculation 15 times.” That’s a significant increase in first-party data generated by all those new sessions, and a positive impact on the overall engagement funnel.
This Spotlight feature has been written in partnership with Bridged Media, democratising AI for publishers. Through no-code AI solutions, Bridged lets publishers access the power of machine learning and Gen AI to meet their engagement and revenue objectives.
Publisher-first AI tools detect where the audience is most likely to engage and through a single line of code, introduce action cards that prompt readers to register, subscribe, or read more, helping publishers establish richer relationships.
Learn more about Bridged Media’s no-code AI tools on their website.
