Executive summary Considering a content recommendations vendor? You might want to take a step back. Before you cede control of what content is promoted on your site, you should answer a few questions. Are they driving your business or theirs? Are a similar way to how ad distribution has gone? For publishers, the goal of increasing reader engagement is as simple as delivering the most relevant content to user expectations have changed. Part of those user expectations include that you know not only what is important but what is important to them as readers. To be a successful publisher in this new landscape requires an engagement strategy that carefully balances expert curation, real-time collaborative analysis, trending data, deep user insight and noise reduction. The new rhythm is the constant beat of a 24/7 newsroom producing a steady stream of content. Publishers package that content across multiple platforms; however, too many users turn to search, aggregators, third-party apps and pump up the volume of content that s relevant and tune out the noise one important way that publishers can reclaim their direct audience, enhance their position as a trusted news source and engage current users in their product portfolios. Publishers who have successfully implemented such a strategy have typically seen click-through rates increase from a baseline of four percent to 10-12%. Dropping an outside vendor s black-box widget on a website to produce generic content recommendations is clearly not an engagement strategy. To be a successful publisher in this new landscape requires an engagement strategy that carefully balances expert curation, real-time collaborative analysis, trending data, deep user insight and noise reduction. and engaging user experience across a publisher s site(s) and platforms. Cxense helps put the power back in the publisher s hands, where it belongs. 2
Introduction Publishers are waking up to the fact that content recommendations are more successful, and more importantly, more engaging when they are based on audience insights. Why is this important? Publishers have, in the media s rapid move to digital, ceded much of their control in terms of their audiences and their revenues. Being able to take action to regain control through audience-focused, revenue-oriented initiatives is every publisher s quest. than other vendors in this space. Recommendations based on CTRs alone can damage brand integrity and be detrimental to a publisher s future. Recommendations based on behavior alone can trap a user into a retargeted pigeon-hole (which can be annoying and feel intrusive). Poor recommendations can Recommendations based on day-old trending data can ignore the pace of news. Recommending articles a user has already valuable screen real estate. Showing the same articles for multiple visits give users a sense of stale content. between content and users over click-through rates. 3
The challenge Content recommendations should not be treated as an afterthought. They represent valuable real estate that some publishers have ceded control of to upstart companies like Outbrain and Taboola. Publishers brands are a place increased time on-site, repeat visits, increased pages per visit and ultimately, loyalty that drives subscription conversions. recommendations, but those recommendations often drive As Ad Age reported, Recommendation engines attempt to discover and apply patterns in data by learning recommend content that will drive high click-through rates (CTRs) without regard for the publication s respectability as a reputable news source (for example, visually or culturally appealing click-bait). Content recommendations, though, can be so much more. Content recommendations: What s the goal? The challenge with established third-party recommendations programs is their goal. Outbrain s CEO Yaron Galai that program has had on premium publisher inventories? According to a Financial Times interview with Outbrain s managing director in Europe, the network shares about half of any revenue generated with partner sites. The cost per click paid is said to range from $0.15 to $0.30 while click rates are in the neighborhood of 0.50 to 0.75 percent. This subtle form of advertising, known as content marketing, is growing rapidly as digital marketers attempt to reach consumers who ignore classic ad formats. This is a decision point for premium publishers. Should premium As the Washington Post reported,...this news-recommendation eco-system has grown into a gigantic, if largely invisible, part of the digital news business. With millions of clicks each day, news recommendation integrity by taking control of their own content recommendations in a variety of ways. Now that publisher 4
Noise reduction vs. retargeting walls than on the walls. The best is a sub-sub-subset of all of the possibilities. It s as much about what you don t show as what you do. If you are going to be MY newspaper, you ll need to be a destination that knows me and helps me discover the best which is a sub-sub-subset of all of the possibilities. Fighting for single page views from web searches is not a recipe for gaining the kind of loyalty that will convince something. "Fighting for single page views from web-searches is not a recipe for gaining the kind of loyalty that will convince Black-boxed recommendation engines might have some level of audience insight. But, it s not all about the user s ads for months (long after you ve made the buying decision)? That s not the kind of compelling experience that builds trust. Actually, it s kind of creepy. A recommendation engine that adds external content is problematic, especially when sources are out of your control. Recommendation engines that drive on click-through rates alone can erode your brand. Users come to you for what s important. Why keep recommending that Miley Cyrus article for a month, only to gain a few more clicks? You can get more clicks by showing provocative pictures or having sensational headlines, but at what cost? Is that really engagement with your brand? to control how articles are presented. 5
Cxense enables you to engage users one on one. And, most importantly, you maintain control over your assets and your audience. Your content insights (in real-time) Your audience insights (in real-time) curate the content for each individual user based on the context of where they are. It s that simple. In other words, Cxense turns up the volume on relevant content and reduces the noise. This provides each user a publisher business goals. Cxense marries a deep understanding of audience, content and semantic analysis that informs highly tailored, content Deep user insights allow content to be weighted based on user s behaviors Impression capping on recommendations amplify freshness of content displayed Flexibility of the engine and a deep understanding of content resources allow recommendations to include high-value content, photo galleries, videos, section-fronts, blog-posts, cross-publisher sites and more Fine tuning recommendations to be more behavioral on section fronts, contextual on article pages and the user experience launches, and high value content 6
Real-time matters Leverage real-time analytics for real-time, trending recommendations and the ability to tune trending data to look at what s trending in last 20 minutes on the home page or the last 10 days on a lower with higher boost or new product launches) variable impression capping to ensure users don t see the same content repeatedly while de-weighting content a user never engages with Being able to leverage user data on the next page views allows Cxense to exclude content the user has already read UX matters experience Money matters User data remains in publisher s control Data can be leveraged for insights on users to make informed choices and design decisions Data can be leveraged for ad targeting and increased engagement can be leveraged to position marketing programs to advertisers Solution: a tangible way to reduce noise on their sites by empowering them to focus on being premium content providers and leaving the heavy data lifting to the Cxense platform. Armed with the real-time user data, semantic content analysis, 50 percent as a result of leveraging recommendations. Case studies articles to have a four to six percent click-through rate. After adding interest/behavioral-based recommendations (e.g. from Cxense), the click-through rate is often increased to between six and seven percent. Finally, after removing the noise - based on the individual reader - the click-through rate can increase to 10 to 12 percent. Typical Results Recommendation Method CTR CMS based 4-6% Interest/behavior based 6-7% Noise removed(real time data) 10-12% 7
Adresseavisen: Cxense helps increase audience engagement by enabling personalized, contextual and trending-based content recommendations. in which they could use audience/user insights and editorial recommendations to deliver individual, user-tailored content to create a better user experience and generate revenue. Their hypothesis was that, with time and proven relevance of recommended content, readers would show greater had on page views and digital revenue while increasing the visibility of their editorial content (easing discoverability). Adresseavisen chose Cxense to help them perform these tests. With Cxense s unique capabilities, Adresseavisen was recommendations. For Adresseavisen, the three key has already read or has not clicked on after several recommendations control of recommendations to the publisher are fresh and relevant, while the reader is still on In partnering with Cxense, Adresseavisen reached an average daily CTR of as high as 18 percent in its recommended advertising. Yomiuri: Cxense helps optimize content recommendations, leading to dramatically improved CTR Yomiuri, the world s largest newspaper with a daily circulation of ten million wanted to increase their digital readership and provide a better online user experience for their online news site Yomiuri Online. Their plan was Cxense. for front and sub-category pages while also giving Yomiuri s editorial team valuable insight to implement content recommendations throughout the site. For Yomiuri, the results of their collaboration with Cxense were dramatic. Yomiuri s CTR rate improved markedly. 8
Conclusion Now more than ever, publishers have the opportunity to harness the power of audience engagement by leveraging their own web properties and audience data to recommend the relevant, right content to the right user at the right time. This sounds like a great, forward-thinking proposition, but most publishers have not been able to tune out keeping users on-site, for longer visits, interacting with more content and increasing relevant content discoverability engagement, publishers can potentially generate new paid digital subscriptions. Cxense can help tune out the noise and focus publishers squarely on creating quality recommendations for the quality audience they want to retain. References 9
For more information about content recommendation strategies, contact Cxense: www.cxense.com