Media & Publishing: Boost Mobile Engagement Strategy with AI Recommendations
Why Publishers Need A Winning Mobile Engagement Strategy
Mobile phones today are almost an extension of our bodies. 80% of smartphone owners look at their phones the first thing after we wake up. Today’s consumers spending an average of 11.1 hours per week streaming TV and video content on their laptops, tablets, mobile and gaming devices. Of the 140 billion odd emails that get sent in a day, and more than half are opened on cell phones, making a good mobile engagement strategy essential to a brand’s success.
Open Rate Distribution: Email Monday
If you send your customers emails, over a billion emails a month are opened on mobile phones alone, and mobile email will account for 15 to 70% of email opens, depending on your target audience, product and email type.
The Age of AI: Alexa, Cortana, and More
After Siri, virtual assistants like Amazon’s Alexa and Microsoft’s Cortana brought the convenience of the digital assistant experience to our homes. Now, Alexa is moving into cars and optimizing the driving experience as well. Adding AI algorithms to mobile apps revolutionize the way brands work, and provide a way to build a deeper connection with every user. These virtual assistants can help you do your shopping, navigate in your car, remind you to do errands and a whole lot more.
AI-based assistants will very likely in the future make suggestions on your restaurant choices, attire, social gatherings and a whole lot more. But before we get so far ahead, let’s take a look at how the AI powered recommendations we have today can be brought into publishers’ apps and mobile engagement strategy to boost engagement.
Artificial Intelligence In Digital Media and Publishing
In their paper on Digital Publishing Trends for 2017, Canadian publisher Valnet declares that experimental technology and programmatic advertising would be trends, as well as fewer words on smaller screens. (Read: more content consumed on mobile.)
In App Experience: Flightlist
“As more ad dollars shift to the digital and mobile environments, content is being created around algorithms and formulas that make it highly searchable, more relevant for reaching advertisers’ target markets and able to drive organic traffic at lower costs,” – Joe Alderson, Director of Ad Operations at Valnet.
With the growth of artificial intelligence tech across industries, AI powered recommendations are the way to stand out and engage users in the mobile sphere. Getting a customer to download your app and sending them personalized push messages is difficult. Using it the wrong way is lethal for your brand. In media and publishing, instead of bombarding your customers with notifications, the best mobile engagement strategy is to provide relevant, contextual content that keeps customers on your website for longer. AI helps you do this.
How Personalized Recommendations Can Boost Publishers’ Mobile Strategy
The publishing industry today is seeing tumultuous times. Revenues and ad share is dropping, and audiences are always hungry for more free content. A dynamic recommendation strategy will generate unique content, personalized according to every app user’s persona – for their eyes only. You aren’t serving one-size-fits-all content to your audience anymore. Instead, you are using the information they give you to make their experience better at every step.
Segmented push notifications already make up 65% of all push messages sent, so why not take it one step further and personalize based on AI? This is exactly what publishers like News Republic, Marvel, Match.com, Vogue and a whole lot more are already doing.
How Publishers Leverage AI Powered Recommendations Today
News Republic, an AI powered content recommendation app uses an algorithm to analyze user preferences to help discover their interests. With the introduction of Spark (their influencer reach and content distribution platform) users can not only get breaking news from 2,000+ top news providers, like Reuters, Associated Press, Agence France-Presse, and BBC International, but also stay on top of exciting content from their favorite YouTubers and bloggers. The app now has over 10,000,000 installs and this number continues to grow.
Image: News Republic / Stark Insider
The app won the “Best Mobile Media and Publishing App” in the year 2015 at the Mobile World Congress, and will now release on HTC and Samsung platforms as well. This shows that a successful app can and needs to move beyond popular operating systems and devices to truly reach the right group of people.
“Spark harnesses the power of artificial intelligence, helping all influencers reach a highly personalized set of potential audiences.”
— Charles Fan, Chief Technology Officer of Cheetah Mobile
In China, the Qing Mang Magazine, a reading app launched in July 2016, has attracted significant attention from Chinese internet old timers. The app uses an interest-based subscription model: users subscribe to a specific interest and receive collections of articles curated by an algorithm based on that interest. A similar machine-powered scheme is behind one of the fastest unicorns in China over the past couple of years—Toutiao.
Image: Toutaio Market Share/Engagement
Some of the most prominent features of these chinese reading applications are
- Personalized News Aggregation: Show customers information and news that they want to hear about, powered by artificial intelligence algorithms.
- Chatbot Integration: The Qing Mang app offers a chatbot-based subscription scheme. Users can subscribe to certain themes by messaging the app’s chat bot.The bot will reply with a series of recommended articles along with a collection built on the theme.
- Communal Reading: Make notes and highlights on articles that others can see, similar to Medium.
Metrics that Publishers Need To Track and Leverage
As a marketer, the final question you ask about the content you publish is: how are folks engaging with your recommended content? Here are some of the basic factors publishers could must track to leverage their advantage of competitors. This will help you fine tune your mobile engagement strategy and create better content that makes user’s stay on your website longer.
- Clicks on Recommended Content Alone
- Time Spent on Recommended Content
- Conversions that result through this writing.
- Interactions on the page – comments, likes etc.
- Social sharing values for recommended content vs. popular content.
Optimizing your mobile engagement strategy with AI recommendations is the first step towards migrating into the world of AI and Personalization. As mobile as a channel becomes more essential to win at everyday and competition increases, AI based recommendations can help your brand stand out and engage users better.