For decades, marketers have relied on consumer data for targeted advertising. The multi-billion dollar global ad tech industry feeds on tons of first-party and third-party consumer data to serve personalized ad content and earn the big bucks.
Marketers consider first-party data as the most precious marketing asset. First-party customer data is collected and owned by businesses that directly provide services to internet consumers. Consumers entrust this information to the business. For example, banks record applicants' information through credit card applications.
Third-party data is collected by companies that do not provide any direct service to the consumer. They aggregate and segment the data and sell it to multiple businesses, which use it to run personalized ad campaigns.
First-party or third-party data includes basic information like names, email addresses, phone numbers, age, gender, job title, etc. Businesses also collect interaction and behavioral data touch points like page visits, downloads, email inquiries, purchase history, customer support, and product reviews, etc.
How do marketers collect this information through the internet? — The answer is cookies.
A cookie is a small text file that stores tracking information on the web browser when a consumer visits any website. When the consumer visits the website again, the same information is used to identify the user.
Advertisers use cookies to track individual users across many platforms. The idea is to create user profiles and re-target advertisements for increased engagement.
Marketers strive for ad personalization. Cookies allow them to find common attributes among customers and target appropriate audience segments with personalized ads.
With growing privacy concerns, consumers are now actively monitoring their online information. Disabling cookies and using ad blockers are common practices among vigilant internet consumers.
Big tech companies are applying various techniques to curb privacy loopholes and enable consumer empowerment. One such technique is limiting the use of cookie-based advertising — known as cookieless advertising.
What is Cookieless Advertising?
Cookieless advertising aims to make cookies obsolete. In the current state of affairs, cookieless reduces the advertising dependence on third-party data.
This monumental transformation is the direct result of Google’s plan to phase out third-party cookies from its Chrome browser by 2022. Firefox has already blocked third-party tracking cookies and cryptominers.
Apple has adopted a different approach. Apps on iPhone and iPad would have to prompt the user for permission before collecting any tracking information. Users would have to “opt-in” to allow tracking for apps and websites.
Privacy and data policy regulations from GDPR and CCPA have also contributed to the burgeoning challenges of marketers.
What’s the solution? — There are quite a few.
In 2019, Google introduced an alternative for cookie-based advertisement known as Privacy Sandbox, to increase web privacy by developing an open set of privacy standards. This will presumably be a more secure environment that will allow advertisers to track user information while maintaining their anonymity. It is a work in progress since developing web standards is a complex process that involves input from many stakeholders on the web.
Early adopters are turning to AI, which has the potential to transform the advertising industry — without using third-party cookies.
Is It Possible To Advertise Without Third-Party Data And Go Cookieless?
Absolutely.
New York Times — with a subscriber base of 7.5 million, has entirely transitioned to first-party data while ensuring privacy.
Developed over the period of two years, they launched a subscriber-based model for advertisers which only utilize first-party data to show targeted ads.
They collect consent-based information through customer surveys and their digital behavior and feed it into their state-of-the-art Machine Learning models to offer privacy-safe advertisement.
Based on this first-party subscriber data, they have built three AI-based advertisement frameworks: emotion targeting, motivation targeting, and topic targeting.
The ML models predict user’s emotions and motivations in real-time and display relevant ads. A/B testing indicates that these ads have performed equally well as compared to their third-party counterparts in terms of ROI and CTR.
This cookieless approach has been possible because NYT has built a relationship of trust and transparency with the customers. The subscribers are fully aware of how NYT uses their data in a privacy-safe manner.
The machine-led future requires an AI-based technology disruption in the marketing industry. Let’s discuss some AI-powered marketing strategies that ensure a cookieless privacy-protected future.
AI-Powered Cookieless Marketing
AI-powered ad personalization has been around for a while. It offers an alternative strategy to reduce the influence of cookie-based marketing.
High-quality data remains fundamental to AI-powered marketing. Advertising platforms should focus on collecting privacy-first data sources.
They should collaborate with other platforms and companies to share their consent-given first-party consumer data which is difficult to access publicly. They must also expand their data collection process like conducting customer surveys to eliminate the need of going to third-party companies.
With AI, the unique identification of a consumer data point is not important. AI can perform clustering to identify customer segments based on the underlying hidden patterns in the available data sources.
AI enables an omni-channel ad targeting approach. It can easily collect anonymous consumer data from different social and digital platforms and combine them to form unique customer profiles or segments.
AI can perform predictive analysis on ad analytics to understand which ad campaigns are successful. Based on all information, AI can automatically generate personalized ad content.
With cookies gone (in the near future), advertisers can focus more on contextual advertising, conversational marketing, and intent targeting.
Advanced Machine Learning techniques can analyze customer intent in real-time. Based on the user’s click actions on the website, ML can identify whether the user would make a purchase or not and deliver this information to the advertising platform in real-time. The platform can automatically display hyper-relevant ads to improve their chances of success.
AI-enabled chatbots are already making headlines around the world for their speed and accuracy in resolving customer queries. This type of conversational AI is always improving based on real customer interactions. It creates a personal connection with the consumer and delivers personalized recommendations.
Conversational data is a gold mine for consumer-focused advertisers. Natural Language Processing models have become reliable over the years. They can understand speech and text better than humans and respond back with personalized content.
AI can also help in contextual ad targeting. Instead of relying on cookie data, advertisers can observe the trends, tone, and mood of the online content. Based on what kind of content a user is consuming at the moment, AI can decide which ads should be displayed to the user.
It can also integrate real-world data like weather and affairs to increase the relevance of contextual targeting. Like during peak COVID-19 days, people used e-commerce websites for grocery and healthcare supplies. Departmental stores and pharmaceutical companies can easily target users.
Whenever AI and privacy are spoken in the same breath, people start questioning its morality. AI models must be super explainable, ethical, and unbiased to deliver privacy-safe solutions.
Unregulated AI (or anything on the internet) can potentially breach consumer privacy. AI service providers have started to regulate AI using standard industry practices in order to eliminate privacy concerns.
At AdCreative.AI, we believe that consumer privacy is paramount. Our AI-powered advertising platform generates high-converting personalized ad creatives based on privacy-safe data. We do not analyze cookies to understand our customers.
Our intelligent AI finds patterns in historical ad creatives and learns from them. It can precisely predict and position ad assets within an ad banner. Marketers can confidently use our AI engine to design hyper-local automated ad creatives at scale.
Think Long Term And Start Today
According to Salesforce, 95% of interaction between brands and consumers will be via AI — by 2025.
In the wake of changing trends and technological disruption, marketers have to position their organizations for success. They are reevaluating their marketing strategies and preparing for a cookieless world.
Cookies are not going to be eliminated immediately. But the current trends suggest that marketers can not completely rely on a cookie-based marketing approach. In the near future, advertisers might face difficulties in 1:1 ad targeting.
Artificial Intelligence is going to play an important role in building precise prediction models that can improve ad recommendations, customer segmentation, report consumer analytics, all the while protecting consumer privacy and maintaining their trust.
Transitioning to stand-alone first-party data marketing is going to be difficult. Companies have to build secure advertising frameworks, enabling advertisers to focus on cookieless ad personalization and hyper-relevance.
