We’ve already gone over a brief history of ad tech in part 1 of this blog. In addition, we also discussed the modern structure of ad tech that detailed the entire process by which online advertising takes place. Now, we will go a step further and discuss the integration of marketing technology (MarTech) and ad tech.
In relation to this, Part II of this blog will explore the evolution of ad tech from Robotic Process Automation (RPA) to Intelligent Process Automation (IPA). This evolution is key to understanding the role artificial intelligence plays in the modern ad tech industry. So let’s dive in and get started by exploring the MarTech – Adtech connection.
Here’s what you missed in Part I of the blog.
The Connection Between MarTech and Ad Tech
Today, ad tech is considered a natural extension of marketing technology or MarTech. In fact, in the modern age, the distinction between the two is increasingly blurred thanks to their inherent connection. Marketers have focused on personalizing customer experiences through the integration of artificial intelligence. This personalization manifests itself simultaneously across Martech and ad tech thanks to the predictive capabilities provided by artificial intelligence.
As users expect customized content, Martech platforms utilize artificial intelligence to automate nurturing sequences that are catered according to specific user interests. Additionally, AI technologies analyze user preferences and interests to generate personalized content for each user, case in point: personalized social media feeds on Facebook, Instagram or Twitter.
Ad tech uses AI to generate personalized ads based on the content users are interested in. As such, the utilization of AI in ad tech goes hand in hand with the personalization of content and automation in Martech. Whether it’s real time bidding in programmatic advertising, customer-centric personalization of ad content or AI-driven content curation and integrated marketing campaigns, AI has sewn Martech and ad tech together for all ages.
RPA & IPA: From Automation to Insights
Despite the seeming complexity of the ad tech process, it is extensively automated thanks to the integration of artificial intelligence. In fact, artificial intelligence has been around for longer than most people realize. This is particularly true for marketing automation platforms that accomplish simple and repetitive tasks according to the instructions set manually by marketers. This basic automation technology is known as Robotic Process Automation, or RPA.
A Closer Look at RPA
RPA has had an increasingly significant impact on the ad tech industry thanks to trigger placement and customized user interface, all with virtually no coding required within the platforms. This has automated the ad tech process for advertisers and publishers alike, while increasing the speed and relevancy with which users are served ads. Behind this miracle of automation is a basic level of AI that offers error free machine automation capabilities.
Yet the integration of advanced artificial intelligence and machine learning with RPA has yielded an even more sophisticated ad tech system than before. The combination of AI and machine learning models with RPA has given rise to Intelligent Process Automation (IPA) that offers the automation capabilities of RPA along with analytical insights for improved future performance.
AI + RPA = IPA
The Need for IPA
The advent of IPA technology is hugely beneficial for digital marketers in general, and for ad tech experts in particular. While the automation capabilities from RPA are retained, IPA allows advertisers to enhance performance analysis of ads and ad campaigns. For instance, systems equipped with IPA technology can learn from past trends to predict favorable future outcomes.
For advertisers, this opens up endless possibilities of automating machines to find the best combination of ad features that works for a particular target audience. Based on continuous learning, IPA updates user preferences based on real time activity and recommends appropriate strategies for optimal performance. In addition, AI used within these technologies can adjust budget allocation in ad campaigns based on best and least performing ads.
All this automation and predictive adjustment means consumers are now used to getting personalized content and ads. Salesforce estimates that 62% users expect businesses to anticipate their needs before hands, while 53% users are now used to getting customized content. That’s why hundreds of thousands of businesses are now employing IPA technology in their ad tech process.
On an even larger scale, the integration of IPA in ad tech means that artificial intelligence will play an increasingly essential role in the industry for years to come. From automation to insights, advertisers now lean on AI more than ever during the ad tech process to not only execute repeated processes with increasing efficiency and speed, but also to anticipate user needs and adjust ad strategies accordingly. On the other hand, publishers rely on IPA and advanced artificial intelligence to make SSPs more efficient in monetizing ad spaces.
So there is little doubt that AI will continue to reshape ad tech like never before. It is likely that the programmatic advertising landscape will experience drastic changes in the coming years and decades. But how drastic? That remains to be seen.
Speaking of ad tech – here’s a handy guide to integrate DV 360 and Campaign Manager 360 for higher ROI.
Ad Tech in 2021: Publishers & Advertisers Perspective
For now, there is one thing that the ad tech industry can agree on; 2021 is going to be shaped by exciting new trends that will allow advertisers and publishers to improve user experience even further. Some of these trends are discussed below.
1. Contextual Targeting
Data privacy will be a governing issue in ad tech in 2021. Along with consumer data protection laws such as GDPR and CCPA, governments are now taking a closer look at what publishers and advertisers do with the consumer data that they collect. As such, publishers and advertisers will be scrutinized for collecting consumer data that has no way of being utilized in a digital environment, especially for providing a personalized consumer experience.
As a result, the ad tech industry is turning to contextual targeting where technology such as GPT3 will be used to understand the context of an article in relation to its emotions and sentiments. Publishers aim to ascertain the tone of the content put up on their websites, and will utilize IPA to analyze the sentiments of consumers landing on the content. They can then add a new dimension to the customer profile presented to advertisers prior to the RTB process. Advertisers can then collect contextual data about consumers rather than gathering troves of data that may be seen as irrelevant by authorities.
2. CTV on the Rise
Connected TV (CTV) advertising is definitely a rising trend in 2021. This is partly because of the lockdown restrictions implemented by governments due to the coronavirus pandemic. As a result, advertisers are reallocating budgets to expand their reach through CTV advertising. Even more importantly, almost 60% of CTV inventory will reportedly be purchased programmatically in 2021. This digitization of a traditionally offline inventory buying process will result in a surge in CTV verification technologies and partnerships.
3. Accurate Measurement
Finally, accurate measurement of ad performance will be the order of the day in 2021. Historically, advertisers and publishers have always disputed impression figures and other performance KPIs for ads online. 2021 is likely to bring ad verifications and enhanced ad measurement technologies into the mix. The focus will be firmly fixed on monitoring ad spend wastage, consumer engagement and end-result of business campaigns for advertisers. The aforementioned IPA technologies will play an important role for publishers to enhance performance measurement capabilities of ad servers.
Contending with the ad attribution problems in ad tech remains one of the biggest challenges for advertisers and publishers alike. Lucrative.ai solves this problem by presenting clean and meaningful data, thanks to data engineering capabilities for machine learning. As such, advertisers are able to integrate long term programmatic strategy with core KPIs to bridge the gap between expected and actual results.
Dive Into the World of Ad Tech with Lucrative.ai
The world of ad tech is ever-evolving especially with the integration of AI. That’s why businesses need to have a sound ad optimization strategy that is supported by valuable data-driven insights. With Lucrative.ai, that’s exactly what you get. Contact us below and sign up for a 2-day free trial on Lucrative.ai where you can explore all its features in details.