Mobile advertising has evolved over the years and the fact that 2019 will be celebrated as a “year of mobile advertising” is not a secret to any marketer. The advertising world had bravely explored the mobile landscape a decade ago, when users had started shifting from desktops to mobiles. The mobile environment continues to grow and attract new audiences.
The mobile advertising ecosystem supports high return on investment (RoI)-driven interactive ad formats that engage and retain users on the app. The fastest growth is noticed in the in-app mobile segment, which is explained by the popularity of mobile games among audience segments of all ages.
The mobile advertising market is expected to exceed $200 billion globally in 2019, according to eMarketer. Apps will represent lion’s share of the ad spend. At the same time, video advertising will grow to be worth $37 billion, with mobile exceedingly becoming the platform of choice. Ad agency Zenith believes mobile ad spending will account for 30.5 per cent of all global advertising expenditure, and not just digital, by 2020. At such an exciting time, there are certain trends that are dominating the industry.
Augmented reality/Virtual reality
William Arthur Ward once said, “If you can imagine it, you can achieve it.” It is not just a quote any more, augmented reality/virtual reality (AR/VR) has given us enough power to bring our imagination to life. People only remember those ads that were interactive enough to hold their attention.
Current media puts a constraint on the amount of interaction one can have with an ad. But AR/VR has surpassed all those limits and has provided users with interactive ads that go way beyond the traditional ads with the growth of machine learning (ML) and artificial intelligence (AI).
The AI market is growing fast and is expected to exceed $100 billion in 2025. According to Gartner, the top 200 companies in the world will fully rely on apps based on AI and ML technologies. Together with ML, AI helps with getting real-time stats and valuable insights about any and all data.
Personalisation vs GDPR
An Interactive Advertising Bureau research has shown that consumers create their own points of “prime time” engagement through the day. The advertiser needs to capture the user’s attention at the point of maximum engagement while giving them the opportunity to choose the appropriate level of personalisation.
A Salesforce study shows that 65 per cent of users believe personalisation enhances their brand loyalty. At the same time, users value data privacy. This caused a controversy in the online ecosystem – companies like Google or Facebook asked for private information to provide a better and more personalised user experience. On the other hand, the general data protection regulation implementation forced Europeans and the rest of the world to clarify which information is gathered and what will be done with it.
Voice tech’s growing role in the household
If 2018 was about testing smart speakers’ usability in the household, 2019 will be the year of brands proving their voice tech’s value. Ownership of smart speakers like Amazon Echo or Google Home has grown rapidly. Smart speaker adoption is driving consumers’ voice tech usage and pushing marketers to explore how to tap into this burgeoning channel– something that will evolve further in 2019 as people grow more comfortable conversing with devices and the technology becomes increasingly predictive.
OTT/Video spends are increasing
Besides rewarded video, advertisers are getting serious about reaching users in over-the-top (OTT) environments. In 2018, OTT ad revenue reached an estimated $2 billion, up 40 per cent over 2017. Marketers who are still trying to wrap their heads around the shift to OTT need to look at these buys more like in-app advertising than the next wave of TV. After all, content on connected TV and OTT platforms is analogous to apps – just on a larger screen.
AI and ML
The problem that every marketer faces is that there exists a mountain of data but comparatively less time to analyse it and narrow it down to user demographics, and their preferred time to watch and engage with the ads. This is where AI/ML comes into the picture. It does all the work of keeping track of users’ interaction with ads, the keywords they use, and accordingly predict what is the best time to display ads that will get the maximum user interaction.
Using data predictions from AI/ML, marketers can direct the ads that are most relevant to the users’ newsfeeds. For instance, when we are trying to book a hotel, we get suggestions of similar hotels based on our search history.
