As we go from digital advertising's historical roots to the present, we explore how it is set to transcend traditional boundaries, entering an era of profound connection and relevance.
This is all due to the transformative power of shopping and purchase data, where The Third Wave (Retail Media) represents a pivotal shift towards enhanced targeting accuracy and profound profiling precision.
1990s: The Dawn of Digital Advertising
1994: The first banner ad on HotWired.com by AT&T marks the beginning of digital advertising.
First Wave: Search Media
2000: Google AdWords (now Google Ads) launches, introducing keyword targeting. This allows advertisers to show ads based on user search queries, to deliver highly relevant advertisements.
Second Wave: Social Media
2005-2007: The rise of platforms like Facebook introduces social targeting, using data from user profiles, interactions, and network connections for ad personalization.
The First Decade of Data & Machine Learning
Mid to Late 2000s: Behavioral Targeting starts collecting browsing history and other online behaviors, especially from uprising Social Media networks, to profile and classify the purchase intent of users.
2010s: Big Data technologies start processing vast amounts of user data and specialized data platforms are appearing. In 2010, Real-Time Bidding (RTB) and programmatic advertising appear, optimizing ad buying and placement in real-time based on detailed user data.
Mid 2010s: Machine Learning start being used to significantly enhance ad targeting and relevance. This is the beginning when advertising platforms are using this new capability to fill in missing data of users by enriching their profiles with data from other users or from other behaviors.
Third Wave: Retail Media
Late 2010s: Amazon revolutionizes digital advertising with sponsored recommended products. Amazon's specific profiling capabilities leverage comprehensive purchase history, search patterns, and consumer preferences within its ecosystem, setting a new benchmark for Retail Media. This approach not only boosts visibility for sellers but also enhances relevance for consumers by integrating ads seamlessly into the shopping experience.
2020s: New Data Paradigms & AI
2021 onwards: As GDPR and other developments of privacy-preserving regulations appear, targeting technologies are looking at a new era of behavioral-based segmentation and the revival of contextual targeting. This is where user's personal data proves to be less valuable for advertising results than their anonymous behavioral data.
What's In-Store For Digital Advertising? Predict & Influence Purchase Decisions.
Advertisers are looking to improve their Return on Investment from Digital Advertising while being able to influence omnichannel purchase behaviors of their customers.
The purchase and behavioral data of retailers became a goldmine in this new paradigm.
With Footprints AI, behavioral & purchase data from both physical and digital retail channels (beyond the limited volume of registered users only) can transform into audience profiling.
This audience data is currently revolutionizing the success rate and profitability of retail media networks, their go to market success and data-asset valuation.
Using proprietary AI technologies, Footprints AI can enable targeting based on:
- Psychographic Analysis: Understanding customers' values, attitudes, life stages and lifestyles based on physical retail behavior and omnichannel shopping habits.
- Socio-Demographic Profiling: Using AI & behavioral data to predict gender and age of anonymous customers based on their shopping habits and the context when these patterns happen.
- Predictive Behavior Modeling: Anticipating future needs, visits, and purchases to optimize customer knowledge and improve relevance across the complete omnichannel path to purchase.
Join Footprints AI in pioneering this new paradigm in digital advertising.
