Share on facebook
Share on linkedin
Share on twitter
Share on facebook
Share on linkedin
Share on twitter

How Digital Publishers Can Capitalize on Data Monetization

In the world of publishing, times are tough. In Asia Pacific, advertising is dominated by online search and social media platforms (accounting for 92 cents of every dollar spent) – so is it any wonder that digital publishers are increasingly turning to subscriptions for more revenue?

However, there is a way to stem the tide. As a digital publisher, you are sitting on a treasure trove of customer data that can be made to work for you, especially when combined with external data to provide you with holistic insight on customer behavior. It helps with more effective ad placement for a higher return on advertising spend (ROAS) while also providing a granular view of your customers’ interests and behaviors in order to drive subscriptions.

Used correctly, artificial intelligence (AI) can help in both areas, breathing new life into the digital publishing business and making your publication a brand readers and advertisers alike will keep coming back to.


Journeying Towards Personalized Content to Drive Subscriptions

Subscriptions are increasingly important for digital publishers. According to a recent study ‘Journalism, Media, and Technology Trends and Predictions 2019’, subscriptions will be the main revenue focus for 52 percent of publishers. Used correctly, AI can help you achieve that without your costs ballooning.

The reality is that you probably already have some basic information about your readers based on your customer data, such as age, sex, reading habits, etc., but you need to dig deeper and develop a more holistic customer view for effective targeting and personalization.

Combine your own customer data with extra data from external websites using a data science platform such as AIXON, and let AI crunch the data to give you a complete picture of your audience, including their cross-screen behavior and interests outside of your publications.

AI can then segment the readers based on their interests for you to tailor your marketing messages using a range of mediums, including EDM, push notifications, in-app messaging and so on, in order to increase stickiness and drive subscriptions.

For example, if you are a diet and healthy living publisher and you discover a certain segment of your website customers also love treating themselves to sweet snacks once or twice a week, you could push occasional ‘cheat day’ content like recipes and restaurant reviews as a new way to appeal to them. If you know one particular restaurant or gym is popular with your customers, you could even offer money off discounts as part of a collaborative deal.


Thinking Outside the Box: Leveraging External Data to Increase Ad Revenue

Of course it is not just about subscriptions. Advertising is still a valuable source of revenue for digital publishers. So, how can you unlock the potential of data to drive ad revenue?

Leverage AI to analyze your web traffic, as well as your customers’ behaviors on other websites run by third parties, so your customer data isn’t limited to interactions with the website and the app of your own publication. This helps you identify the keywords that indicate the top interests among your audience, and segment them accordingly. You can then sell advertising space to advertisers based on these segments in order to generate or increase ad revenue.

For example, if the diet and healthy living publisher mentioned earlier discovered that dairy-free foods are a big area of interest for its readership, this would be an easy sell-in for manufacturers of dairy-free milk and cheese. Confronted with hard data proving that a sizeable proportion of your customers buy dairy-free alternatives, the manufacturers can be more confident of a high ROAS, and hence more likely to spend their advertising budget with your publication.

The publishing landscape has changed inexorably in recent years, bringing plenty of fresh challenges, but that doesn’t mean digital publishers have to suffer. Those that innovate by adopting emerging technologies like AI will develop a better understanding of their customers, and be better enabled to serve their diverse range of interests. By leveraging AI and data science, you can make yourself a more disruptive digital publisher, and find new ways to appeal to your customers, both website readers and advertisers alike.


* Discover how AIXON, Appier’s Data Science Platform, can help you drive revenues from both subscription and advertising. Contact us for a personalized discussion today!



Let us know the marketing challenges that you’re facing, and how you want to improve your marketing strategy.


How to Minimize Booking Abandonment in Online Travel

Cart abandonment remains a major issue in online travel business. Proactive customer engagement platforms powered by artificial intelligence (AI), however, are making it possible to catch and convert cart abandoners, effectively and efficiently, through brands’ owned media channels. According to a recent research, 92 percent of all travel bookings in Asia Pacific were abandoned at checkout, with online travel agencies suffering from the highest rate at 95.5 percent, followed by hotels (90.4 percent), airlines (91.6 percent) and vehicle hire companies (88.9 percent). There are many reasons why shoppers abandon cart. Some are just browsing, still comparing prices or simply distracted. Others become frustrated with slow-to-load pages, or are put off by high credit card fees. While some cases of abandonment can be avoided by improving your website or app UX, many can be overcome by remarketing via paid media channels, such as Facebook and Google Ads. While such remarketing can be effective in winning back lost carts and boosting sales, it is also costly, and relies on strong retargeting tech and infrastructure that many companies lack internally.   AI, Owned Media and Cart Abandonment Can travel brands tap into the potential of owned media and leverage data to tackle cart

Are Data Scientists Evolving With the Rise of Artificial Intelligence?

As developments in machine learning (ML) are expected to progress at a phenomenal pace, it is set to become one of the most powerful tools for businesses to enhance productivity and drive innovation. While ML, one of the most popular artificial intelligence (AI) applications, holds a lot of promise for businesses, is the role of data scientist today already evolving in order to keep up with the change?   What Is Next in AI Continued advances in AI will see autonomous systems perceive, learn, decide, and act on their own, but to ensure the effectiveness of these systems, the machine will need to be able to explain their decisions and actions to humans. This is so called explainable AI. “In the future, many AI systems are going to interact with people, especially those who will take responsibilities, hence the reason why AI needs to be explainable, meaning that the behavior of the system needs to be easily expected and interpreted by people,” said Min Sun, Chief AI Scientist at Appier. Sun also pointed out that in the future, AI is going to be less supervised, which means that it will require less human inputs, and be more creative. Data science

Five years down, and many, many more to come!

When I started Appier five years ago, artificial intelligence (AI) was not a hot topic. It’s hard to imagine that the first few business ideas were actually brainstormed in our dorm room in Harvard, and we will always remember the joy of the very first time that our customers trusted us and gave us our first order. In those first few years, we faced a lot of challenges, and we learned a lot, too. The first lessons we learned as entrepreneurs was to dream big and embrace failure. We keep this entrepreneurial spirit alive as our company grows, and we encourage our employees to develop their own entrepreneurial mindsets. When you’re not open to risks and failure, bold new ideas will never take off. Over the past 5 years, we were always thinking about how to make a real impact to human society and industry with AI when our products go on the market. We experienced eight pivots, from AI-based social games to the marketing and data intelligence platforms for enterprises that led to our initial success. We will never give up and we will always have the faith of continuously innovating. We have grown from a 4-person startup to