Catch Me Up:
- Part 1: From Billboards to Bots: Marketing’s Wild Evolution
- Part 2: The Dawn of Computing—the 1950s
- Part 3: The 1960’s (and 70’s): Women flex their marketing muscles
- Part 4: 1980–Y2K: Marketing’s Big Bang
- Part 5: 2000-2010 – the Year the DOT-COM Bubble Burst
- Part 6: 2010–2015: Marketing Goes Mobile
I started building a PRTools database because I was overwhelmed by choice. I thought I was cataloging software. What I discovered was how our profession itself was changing.
When I re-launched as PRToolFinder in 2016, PR pros were still debating whether social media belonged in the communications mix. Today, we’re debating whether AI can write our pitches and social posts. The tools have changed dramatically. The underlying principles haven’t.
Let’s Review
If the first half of the 2010s was about getting marketing onto our phones, the second half was about letting algorithms decide what we saw when we got there.
Social networks were no longer simply chronological streams of everything our friends had posted. Algorithms increasingly determined what appeared in our feeds—and, just as importantly, what didn’t.
That changed marketing. (And a lot of other things, like elections.)
A lot.
When the Algorithm Became the Gatekeeper
Facebook became an enormous advertising platform. Instagram became a visual marketing powerhouse. YouTube transformed video creators into businesses. LinkedIn became increasingly important for B2B marketers. And in 2018, TikTok emerged globally after the combination of TikTok and musical.ly, helping make short-form video one of the defining formats of the next era.
The audience was still there and growing.
But marketers no longer controlled the distribution.
Algorithms did.
And algorithms were/are learning.
When AI Started Showing Up in Marketing
Machine learning and artificial intelligence had been developing for years, of course. I’ve written many a case study on the use of these by my enterprise software/application development clients over the years. But marketers were increasingly encountering AI in practical ways: predictive analytics, recommendation engines (if you liked X, then you might want to also see Y), automated advertising, chatbots, personalization and tools that could identify patterns in enormous quantities of data much faster than humans could.
One example is TikTok’s “For You” Feed Algorithm (2016–2018). TikTok built its entire product around its real-time recommendation engine. Rather than utilizing a social graph, it analyzed microscopic data points (such as frame-by-frame retention rates, swipe speeds, and device audio tags) via deep neural networks to instantly personalize feeds
Another is Netflix’s Artwork Personalization (2017). Netflix expanded Machine Learning beyond video recommendations to customize the actual thumbnail art shown to users. Using a type of reinforcement learning called Contextual Multi-Armed Bandits, their engine calculated whether a user was more likely to click a movie if the thumbnail emphasized a specific actor or a romantic theme.
At this same time, influencer marketing matured.
From Celebrity Endorsements to Influencers
The basic idea wasn’t particularly new. Celebrities had been selling everything from cigarettes to breakfast cereal for generations. But social media created a new kind of celebrity: someone who might have started with nothing more than a smartphone, an audience and a willingness to post regularly.
And unlike traditional celebrities, creators could talk directly to their followers. That made influence feel more personal—and potentially more persuasive.
It also created a new regulatory challenge. By 2023, the Federal Trade Commission had updated its Endorsement Guides to address social media, influencers, reviews, virtual influencers and other modern marketing practices. The basic lesson was reassuringly familiar: new technology doesn’t repeal old-fashioned truth-in-advertising rules.
The Privacy Reckoning
Meanwhile, consumers were becoming increasingly aware that their personal data had become an extremely valuable commodity.
The European Union’s General Data Protection Regulation, or GDPR, began applying in May 2018, establishing significant new expectations around personal data and consent. California followed with the California Consumer Privacy Act, which took effect January 1, 2020.
Marketing was discovering that “personalized” and “private” were going to have to coexist.
Then Came 2020
COVID-19 didn’t invent digital marketing, e-commerce, virtual events or remote communication. It simply took the accelerator and pushed it through the floor.
Businesses that had planned to “go digital someday” suddenly had to figure out how to sell, communicate, collaborate and serve customers online, and without delay!
According to McKinsey research conducted during the pandemic, companies accelerated their adoption of digital technologies by several years in just a few months.
When Digital Transformation Became Tuesday
Restaurants m
oved online and outdoors.
Retailers moved online AND also invented curbside pickup.
Conferences moved online.
Sales meetings moved online.
Zoom became a daily event.
And marketers discovered that the digital transformation they’d been talking about for years was no longer a strategy for the future.
It was Tuesday.
The Remote-Work Experiment
By the end of 2020, marketing had become more digital, more measurable, more personalized and more automated than anyone could have imagined when this series began.
I’ve been working remotely since 2001 when Milani Marketing & PR was launched; I was running my own business, setting my own schedule and I remember thinking back then that, for me, the pandemic didn’t really change that much for me – I was already working from home. (If my client in Australia had a briefing with an analyst in the UK, I was still the one facilitating in the middle of the night.)
Now the entire world got to have that experience—and it turned out, a lot of people really liked remote work. (Except maybe those with kids.)
More businesses realized that a remote-first approach to work was truly a viable methodology that worked – and worked well.
Still, companies eventually implemented their RTO (return to office) mandates, and some offered—and continue to offer—hybrid work environments.
But the biggest disruption was still ahead.
Join us next week for our final installment, Part 8: 2021–August 2026: From Algorithms to AI
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