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

Keep Your Audience Engaged With AI-Powered Push Notifications

Transform your app marketing with artificial Intelligence (AI), making your messaging and notification strategy personalized, relevant and customer-centric.

Did you know that around 52 percent of app users find push notifications annoying? An unpleasant experience around app messaging can easily result in a user opting out of notifications they find interruptive. Worse – they could even uninstall your app, especially if they find the notifications completely irrelevant.

The solution does not lie in completely doing away with notifications. When used wisely, these are an important element of your brand’s messaging strategy. Notifications help keep your app top-of-mind; they encourage users to open and re-engage with the app. Ultimately, a well thought through notification strategy encourages app usage, growing the lifetime value of the customer.

 

Effective Notifications Are Personalized, Relevant and Timely

In a world where 35 percent of notifications are generic broadcasts to all users, useful notifications are those that offer real value to customers, and are personalized, relevant and timely.

Netflix is often cited as an example of a brand that has nailed successful messaging through notifications. It only sends out notifications announcing the launch of a new season of a show that you follow, or recommending a newly available movie that is similar to others you have watched. Evidently, Netflix’ recommendations are personalized to your preferences.

To make notifications relevant, marketers must use the swathes of data that they have around user behavior, interest areas and past purchases to offer information that is actually valuable to the user. AI can enable this kind of insight.

 

Using AI to Understand Each User at a Granular Level

AI is making it easier than ever for marketers to personalize user experiences, and encourage engagement and retention. It enables proactive recommendations or notifications on products, services or features that are aligned with user interests, pushing up the likelihood that they will engage with the app and complete the conversion KPI.

AI helps personalize messaging through:

Segmentation

Effective personalization starts with accurate user segmentation. AI tools can help you minutely segment your audience by enabling you to:

  • Analyze data around in-app user behavior, past purchase history, action on push notifications, etc.
  • Learn about individual preferences and interest areas
  • Detect patterns, and
  • Predict future behavior

Relevance

Use AI to also ensure the relevance of the notifications. AI tools can analyze vast amounts of user data around preferences and interest areas, and use this to recommend content that they would most likely to engage with. Seventy-five percent of what Netflix users consume is a result of recommendations that are triggered in this way, and 35 percent of Amazon’s revenues come from recommended purchases.

Solutions like Appier’s AIQUA, an AI-powered marketing automation tool, allow brands to hyper-personalize their messaging by analyzing the user’s in-app behavior and journey, and mapping this onto their interests outside the brand’s platforms. Insights from onsite-offsite user interest mapping enable a single customer view, facilitating a better user experience through relevant and personalized messaging.

Timeliness and frequency

How many notifications should a brand send out? Studies have shown that 37 percent of respondents would disable push notifications if an app sent between two to five notifications a week, while 22.3 percent of them would stop using the app.

This means that no matter how personalized or relevant your notifications are, if they are too many in number, chances are that your users will perceive them as disruptive and screen them out. Hence alongside relevance, marketers must also consider frequency and timeliness of notifications.

Here again, AI has a role to play – by analyzing data patterns around when users engage with your app, for example. This will help you send out notifications at the optimal time, when users are seen to be most responsive and more likely to take the looked-for action. For instance, marketers who use AIQUA not only use the platform to personalize notifications, but also to identify the right moment and right way of reaching each user.

Thanks to the power of AI, marketers today can ensure that messages and campaigns are based not on guesswork or intuition, but hard data. The kind of proactive personalization described here is just one way in which you can use AI to enhance your messaging strategy. When it comes to leveraging AI in marketing, the possibilities are limitless.

 

* AIQUA – Our marketing automation platform runs most-advanced AI models to help you understand and predict your customers’ future behavior. Request your free demo now.

WE ARE HERE TO HELP

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

YOU MIGHT ALSO LIKE

Appier Celebrates 5 Years in AI

Appier celebrates our 5th Anniversary this year.  We share some milestones of the company’s progress in our journey towards Enterprise AI in this infographic. Appier – then and now About Appier Appier is a technology company which aims to provide artificial intelligence (AI) platforms to help enterprises solve their most challenging business problems. Appier was established in 2012 by a passionate team of computer scientists and engineers with expertise in AI, data analysis and distributed systems. Appier serves around 1,000 global brands and agencies from offices in 14 markets across Asia, including Taipei, Singapore, Kuala Lumpur, Tokyo, Osaka, Sydney, Ho Chi Minh City, Manila, Hong Kong, Mumbai, New Delhi, Jakarta, Seoul, and Bangkok. For more information please visit www.appier.com.

A Beginner’s Guide to Deep Reinforcement Learning

The game of Go has simple rules but complex play. Each turn, a player has something in the vicinity of 2 x 10170 board positions to consider. Experienced players learn what is likely to work by trial and error over years of play in a process known as reinforcement learning. So what do you get when you give artificial intelligence (AI) the data from thousands of games between professional Go players? AI that beats the top-ranked human Go player – AlphaGo. That is deep learning in action. But what if instead you teach AI the rules of Go and let it play millions of games between itself? Deep reinforcement learning enables AI to teach itself by creating its own data (the millions of games) and analyzing the moves to arrive at the best one. Like a learning human, AI adjusts its responses according to failure or success to improve the outcome. It just does it at a scale and speed well beyond human capability. Deep reinforcement learning needs to work inside a structure. This takes into account the context of the environment – whether that is the rules of Go, or the market in the case of your campaign –

Artificial Intelligence in 2020 and Beyond

Author | Min Sun, Chief AI Scientist, Appier 2020 has a great ring to it. In lots of ways, it has for a long time been a signifier of ‘the future’. Many researchers and experts have, over the past decades, projected 2020 as a landmark year when we might expect any multitude of things to happen or come to a head in some way. And now ‘the future’ is here. We don’t yet have flying cars – or even self-driving cars in any widely-adopted way – but we have seen technology advance in leaps and bounds in other ways in recent decades. As computing power continues to grow, we can expect to see this momentum increase. One area that continues to see rapid advancement is artificial intelligence (AI). There have been some critical breakthroughs in AI technology within the last decade that have allowed AI to be applied in truly revolutionary ways in both business and society – take medical diagnostics for example – and I’d like to share some thoughts on how we might expect to see AI continue to transform the way we do things in 2020.   AI Will Be More Strategic and Able to Act on