2021 was a year full of ups and downs—and not just for the ad tech world. However, the industry saw plenty of exciting improvements and innovations as well as some pretty disappointing mishaps.
As we enter a new year (and hopefully a new beginning) it’s important to reflect on the year that’s passed and get ready for the future. While there are quite a lot of trends we’re seeing come up for programmatic advertising this 2022, there are four that need your attention now.
1. Identity Solutions, Cloud Adoptions, and Spending Will Continue
It goes without saying that the way we work has changed for good. The ongoing pandemic has brought remote and hybrid working models to the forefront, which in turn, has made cybersecurity and identity solutions that much more important.
With so many applications and services now hosted by the cloud, there’s an infinite number of various identities with access. The traditional IT security parameters used to protect sensitive digital information have had to evolve to ensure safe and secure access to all these applications as many of us are now using them on the road, at home, at the office, or a combination of all three.
This evolution of cyber security revolves around the deployment of Identity Governance and IAM initiatives with the emergence of Identity-as-the-new-Perimeter strategies to minimize instances of identity-related risks.
Here’s what we can expect to see from the evolving identity solutions trends:
Intelligent unification, which is the convergence of technologies and identities of various disciplines, is becoming a significant identity management solutions trend in 2022. In today’s world, organizations of all sizes have unlimited application solutions for everything, right at the tips of their fingers, which can easily lead to data breaches and so on.
Intelligent unification aims to maximize the capabilities and information available to provide a deeper insight into identities, their accesses, and the reasons behind their access and usage data. The goal is to give cyber security professionals an idea of how identity access is being used so they can get a better handle on how to reduce identity-related risks.
By breaking down the traditional barriers and sharing pertinent information across the specified technologies, there will be greater assurance that our identities can remain secure and there will be a better method of adapting to new identity-related risks as they crop up.
Continued Cloud Adoption
Cloud services and Software as a Service (SaaS) solutions will also see an increase in their adoption this coming year.
According to a recent survey conducted by the Enterprise Strategy Group (ESG), approximately 52% of business-critical applications are now cloud-based instead of the traditional on-premise hosted—and this number is only increasing.
It’s easier now than ever before for organizations to switch hosting vendors and scale up from their current services. Of course, the increase in cloud-based service adoptions also comes with an increase in identity-related risks and threats.
With this in mind, Identity Governance and IAM solutions will have to provide a more manageable native cloud foundation that will allow organizations to scale their services securely according to their demand while securely managing their identities across all of their applications and services.
Lastly, the autonomy within identity management processes will also see an increase this new year. As of right now, identity management still uses a combination of manual and semi-autonomous activity, which contributes to a significant overhead for both administrators and end-users.
When you combine the overhead with the increasing shortage of IT and security professionals, you get a financially and physically unsustainable ecosystem.
The trending solution here is to implement Identity Lifecycle Management (ILM), which has already seen success with access provisioning and has become accustomed to varying degrees of automation. In terms of Governance involving user access requests, violation management, and even reviews, we’ve been seeing significant improvements in the prescriptive analytics regarding the decision support for end-users for each situation.
This serves as a reminder that there will always be a need for varying degrees of human involvement when it comes down to the decision-making and approvals when it comes to sensitive data for applications. However, as we continue to see an uptick in the amount of necessary data brought in by identities and their automated access of approvals, the remediation for reviews and violation detection will also increase.
Hence the need for more flexible configurations and stronger identity analytics to better serve intelligent unified governance platforms. These platforms are meant to reduce the manual aspects of managing, implementing, and interacting with the identity management processes, and more autonomy within our systems means more streamlined identity management processes.
2. The User Experience Remains a Primary Topic
As publishers continue to adopt and adapt to the standards set forth by Google’s Core Web Vitals, the user experience (UX) and overall web page experience will remain a top priority in 2022.
In a nutshell, the ongoing trends you can expect to see regarding UX design and web page experience include the following:
- Dark mode
- 3D elements
- More abstract data visualization
- Uncommon designs
- Virtual and augmented reality
- More inclusive designs
- More voice search functionality
- More rich animation
- Unique microinteraction
- Possibly new stylistics (as in new fonts and formatting)
- The adaptation of pages to new gadgets, i.e., a “cleaner” screen, navigation optimization, improved visual perception, and so on
As you can see, there’s A LOT to cover when we talk about the ongoing UX trends. It should be noted that while many of these trends, such as dark mode and 3D elements aren’t necessarily new, they have been upgraded.
For example, web developers have already been using oversized and repetitive 3D ad inserts to increase page load times and app launch times. By next year, the emphasis will shift towards smaller frameworks to reduce the time it takes to open either source and therefore improve usability.
Ultimately, the goal is to continuously improve the entire user experience to make it more pleasant and engaging so we can continue to see growth from our monetization strategies. You read about the above UX trends in greater detail here.
3. Contextual Targeting Will Become the Forefront of Ad Delivery
For a long time, behavioral targeting was used to serve relevant ads to users browsing the internet. The primary issue we’re seeing with behavioral targeting is its reliance on third-party cookies gathering user data and ensuring compliance with data privacy laws. Not only is this disruptive to the user experience, but it also ends up serving up ads from the user’s prior search rather than the present.
Contextual ads rely on the current web page’s content to serve up the most relevant ads. For example, if the user is reading about makeup, the ads throughout the webpage will be in relation to makeup such as makeup application tools, other types of makeup, and so on.
The need to bring back contextual advertising came about with the onslaught of popularized social media apps. The average person spends roughly two and a half hours on social media each day, and while behavioral targeting was the initial fallback for advertisers, the digital ads being served gained a bad reputation fast for being “spammy”. This caused more and more users to download ad blockers as well as a panic about how much data and private information these apps were actually collecting.
Hence the reason why legislation to ban behavioral tracking by the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) was passed. These are the very restrictions that caused marketers to shift to contextual targeting as it’s less invasive and is more acceptable among the masses.
4. Machine Learning and AI Will Become More Applicable and Accessible
From price floors to ad copy and even content creation, machine learning and AI are expected to begin taking the lead in 2022.
As the programmatic advertising world has evolved, the methods for audience targeting and speaking to potential leads directly have become feasible with the assistance of machine learning (ML).
Machine learning is a subset of artificial intelligence (AI) that refers to a set of algorithms used to determine conclusions and predict results based on input data. Some of these algorithms are capable of improving their own performance as they “learn” from said data.
In the digital advertising world, ML is utilized to help brands understand their customer base better and to optimize their ad campaigns accordingly. ML can be applied to a wide variety of issues in terms of programmatic advertising, such as performance issues all the way to the development of computer “vision.”
By using ML and its associated tools, advertisers have also been able to automate complicated tasks so they can focus on growth and other aspects of their jobs or web pages.
One prime example of how ML and AI are already being used in detecting ad fraud via DSPs, ML has allowed for quick and easy detection of fraudulent inventory, the prediction of viewable impressions, bid shading, and much more.
As ML and AI become more accessible to everyone, we can look to a future of fully-automated advertising platforms that allow us to focus on increasing our ROAS and more.
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