7 Programmatic Trends You Might Have Already Heard Of, But Not This Way [Quiz]
Yes, we know: programmatic trends & predictions are among the TOP-5 hackneyed topics in the industry. This is quite mind-numbing to see all these statements roaming from one blog to another. We are not going to tell anything globally new here (we can't change the trends, not yet), but offer a refreshing perspective on how to apply them.
After combing through tons of upcoming programmatic predictions for 2021 and interviewing a dozen of the greatest ad tech innovators, we know what the major trends are today for sure. Yet, the thing we're not sure about is whether your company needs to chase them altogether.
Thus, we decided to make our predictions more client-oriented and designed a quiz that will help you decide what to implement first based on your yearly goals. Also, the article features direct commentaries from ad tech leaders on the media buying trends 2021 and actionable insights for brands, publishers, and ad networks. Does it sound alluring enough to check out? Let's start then.
(Or, you can always watch a video first and then come back to the article if you need extra info):
Programmatic Trend #1: Consent-Driven 1st-party Data Models
Consent-driven 1st-party data models will emerge and become more tangible in 2021. This is not just a logical step forward, but more of a necessity driven by the IDFA, 3rd-party cookies, and CCPA. The final farewell with such cookies is set for 2022, so this year will be our time for the preparation and dry run of new solutions.
Which exact models are expected to arrive? Data management platforms will likely re-architect their algorithms to collect consented, personally identifiable data, and transfer it to programmatic platforms without the need to define anonymous segments.
One of the ways to collect personally identifiable information data proposed by Google is Federated Learning of Cohorts. Cohort solutions are all about local data processing: they use machine learning algorithms that run on the device and form audience segments based on behavior such as browser history.
The idea is to improve privacy by letting advertisers target groups of users based on common interests, rather than using a pseudonymous identifier for each individual user.
Tip: to learn more about this method, check out the Google Privacy Sandbox initiative.
“Solutions developing themselves in a privacy-first environment and companies adapting their strategies to still be able to effectively approach and acquire customers are going to come out stronger than before — building a strong relationship with their consumers while also retaining the main benefits of performance marketing.”
Another workaround here is shared user ID solutions. Here, publishers collect 1st-party cookies on their website and forward them to the ID provider through a Prebid API. An ID provider creates an anonymous ID based on the user's consent. This ID will later be shared with ID consortium's partners like brands and ad tech companies and sent back to the publisher to store the ID in their 1st-party cookie.
The identifier assigned to the user can be declared or inferred. Declared ones are consistent identifiers like emails or phone numbers. Users are not very prone to leaving such info, so the use of inferred identifiers seems to be more viable. Those are passive identification signals like IP addresses or the device's user agent.
Tip: What shared ID solutions are already on the market? Check out DigiTrust from IAB, ID5, Britepool, LiveRamp, and Unified ID solution.
From the legal side, consent management platforms will be a new must for publishers. With a CMP, it will be easier to automate the process of obtaining consent from consumers and therefore comply with GDPR and CCPA in a much simpler way.
“It's overall good to see that the ad tech industry stopped arguing about GDPR (or CCPA) but built with TCF 2.0 framework that integrates these legal requirements into the programmatic process chain. The technical centerpiece to handle all these privacy requirements is obviously the Consent Management Platform (CMP).”
Programmatic Trend #2: The Rise of Connected TV, OTT and Mobile Ad Formats
Connected TV, OTT, and mobile-friendly ad formats will continue to rise. 1 in 3 Americans cut the cord and banish the cable to a dump. 55% of them pay for at least one OTT service. And lastly, 3 out of 4 people use their CTV devices daily. This all means we're breaking into the new era of TV commercials — now programmatic.
“CTV component will be a fundamental element of the media planning of many advertisers in 2021, with an approach that we call “total video” advertising. Between September and October 2020 we conducted a study with CoLab, a survey of marketing professionals from the European countries, where 68% of German marketers forecast to increase their investments in Connected TV devices in 2021.”
Other facts revolve around such ads' effectiveness. OTT ads have an average completion rate of 98%. It's much harder to skip the ad on a Smart TV device, and in some cases, viewers have no choice but to watch if they want to proceed with the video.
During the Covid-19 pandemic, CTV and OTT programmatic ad spend increased by 40%. And we're far from the return to normal life. Due to quarantine restrictions, people stay at home and use their CTV devices more frequently than ever, which will likely be the trend of 2021 as well.
The big screen is an absolute favorite arena for advertising, but let's not forget about small yet mobile ones. Mobile has a 68% share of digital ad spending, as there is no more accessible device to browse the web, play games, and watch videos anytime. New reality also affected app usage: in the 1st part of 2020, app downloads grew by 131% while monthly consumer spends on apps and games increased by 25%.
Programmatic Trend #3: AI and Machine Learning Development
Both COVID-19 and the data revolution have dramatically accelerated the use of artificial intelligence (AI) and machine learning in programmatic advertising and this trend will likely persist in 2021. First, it will be fully applied in targeting to process loads of data faster and generate better audience segments. Machine learning is a must in such targeting methods as contextual and behavioral targeting.
Machine learning will also be used to improve bidding optimization to make programmatic advertising more cost-effective. For example, Epom DSP offers a system of bidding rules and multipliers to automatically adjust the bid price based on the given conditions.
“Utilising machine learning in advertising has been a trend present over the past years and it's adoption is only about to accelerate. Many ad tech providers and ad networks are introducing more products relying on machine learning to best optimise their client's campaigns and take off the load for granular optimisations.”
What's more, AI can deliver predictive insights by taking into account customer's browsing history, installed apps, past purchases, past interactions with ads, and a customer's resemblance to previously identified high-value customers. These insights also help advertisers to improve their targeting and bidding and to increase their ROI.
Programmatic Trend #4: Audio and Podcast Ads Scale-up
Mysterious programmatic audio will likely scale, as the popularity of online music streaming and podcasts grows. By 2022, Americans will spend nearly 90 minutes a day listening to streaming radio, music playlists, or podcasts. Brands will spend over $2.5 billion this year on digital audio advertising, with podcast ad revenue alone is expected to surpass $1 billion by 2021.
Only the minority of demand-side platforms support podcasts and other audio ads now, yet this will likely change in 2021. Time to look at the ways to execute programmatic advertising within this promising channel.
Linear audio ad formats work like video ads: you listen to pre-roll, mid-roll, or post-roll third-party insertions placed inside the main program respectively.
A more interesting way is host-read ads. It's kind of a native ad in an audio format. With programmatic, host-read ads will be also placed dynamically, being pre-recorded to use during any episode of a podcast.
“The sale of smart devices has exploded in recent years, which is a lucrative avenue for advertisers to grab. For instance, the concept of smart audio ads that would perform action-based responses is also in trials.”
Programmatic Trend #5: Shift from Hyper-Personalization to Hyper-Relevance
The focus in targeting will shift from hyper-personalization to hyper-relevance. What does it mean? Personalized ads create experiences based on the user's overall interests. Relevant ads create timely experiences based on the user's current interests, which means more room for making decisions here and now.
The example of hyper-relevant advertising combined with a smart choice of device targeting is geofencing on mobile. It focuses on highly localized areas to provide relevant ads — making it useful even when you lack additional user persona information. Geofencing places higher value and precision on location — and it works well, often becoming a crucial factor in purchase decision making.
This is only one of the factors that can be taken into account — right location combined with the person's potential needs. When it comes to advertising relevance, we ask ourselves a number of questions whether the user NEEDS the product or not rather than identifying their INTEREST in that product.
That's a much more complex task to implement than just personalizing the message. Thus, hyper relevant ads will be powered by abovementioned AI and machine learning algorithms due to the ever changing, dynamic nature of relevance.
Programmatic Trend #6: Recovery of DOOH Advertising
In 2021, digital out-of-home advertising will likely start its slow yet steady recovery. Seems like people got tired of lockdown policies and are less prone to stay at home due to health concerns. DOOH is forecast to see an increase of 40% in 2021, and screen fatigue and tiresome sunlight deprivation consumers experienced in 2020 are the main reasons for that.
“I'm quietly optimistic that many areas that were hit hard by the COVID19 pandemic will see a resurgence, such as DOOH.”
Out-of-home advertising is basically one of the oldest forms of promotion, yet it's popularity seemed to be fading away once online ads were introduced. And, especially the mass obsession with mobile phones did the trick. But as you know, fads come and go, and now when everybody becomes nauseous about online, OOH will see its great renaissance, now in the new wrapper.
Not that many supply-side platforms now integrate with DOOH. The segment remains more tied to direct forms of media buying rather than traditional online advertising, which experiences a great shift toward programmatic. Yet, DOOH is gaining momentum among SSPs, so the company that owns a DSP and has access to custom supply partners can greatly benefit from early adoption of programmatic DOOH.
Programmatic Trend #7: White-label Software Will Loom Larger
“Owning a DSP? Millions and years to spend. Nah, better use the existing one.” — advertisers, especially smaller ones, may show their protest. That is the #1 reason why we predict the growth of the white-label software segment, which allows brands to reap all the benefits of platform ownership but spend zero time and energy on in-house software development.
Transparency, modularity, and data richness — these words are seen across the loudest headlines in advertising-related media as trends of 2021. White-labeling your advertising platform, you kill three birds with one stone. Let's see how.
- White-label tech makes your media buying process 100% transparent. You become a root user of a system, see all the insights of the platform, and even can get access to the back-end. As a platform owner, only you decide which supply or demand partners to integrate with and pay no bid markups to middlemen.
- White-label tech is modular and highly customizable. The root user can give out accounts, set up roles and permissions for their own clients. It's possible to adjust interface, optimizations, and even request custom feature development from your provider (which is obviously cheaper than development from scratch).
- White-label tech allows for data collection from the supply side. The platform owner controls all data streams and can use this data for their specific needs. For example, you can request audience data from the SSP and enrich your targeting options with custom parameters based on data values of any kind.
Being so well aligned with the overall programmatic trends, white-label demand-side and supply-side platforms might get a new round of recognition this year.
“White-label software is a godsend for the companies with $20,000+ ad spend who have money but would prefer to invest it in anything else rather than development. Paying a flat fee to the white-label provider usually turns out to be less spendy than building the platform themselves.”
Summing up, the ad tech industry will still be driven by the way how the world pandemics will unfold. Other significant factors to affect programmatic are new data regulations, phase-out of traditional targeting algorithms, and some castling in device use. So, seven trends to expect in 2021 are:
[Quiz] Your Personal Programmatic Prediction for 2021
And now, we're going to predict your personal #1 trend for 2021. This is not like tarot card reading or magic ball based on the pseudo-random number generator, but a data-based projection on what's may be the most relevant for your company.
Press “start” and let's find out: should you focus on 4K visuals for TV, create a literal buzz with programmatic audio or reach your personal zen with a white-label programmatic platform.
Your Personal Programmatic Prediction for 2021
Based on your advertising goals and values, and not on a random number generatorGet now