To My Fellow Marketers: AI Has Been Our Secret Weapon Long Before ChatGPT

It was a lovely morning in Little India, Singapore. And between mouthfuls of dosa, chutney, and chai, I had a rousing discussion with my old friend, Gosia, a veteran documentary producer, about how marketers have been early adopters of AI quietly for decades.

If you’re a marketer who is wondering if you’re falling behind in this “new” world of AI, this article is for you.

Remember lingos like “machine learning”, “predictive analytics”, and “programmatic marketing”? We’ve been using subsets of AI to connect with our audiences, make better ad spend decisions, and boost ROI for years.

Now, opportunities have multiplied with GenAI, such as the ability to synthesize data and generate insights faster, build audience personas, and shorten customer service response times, among other benefits.

But marketers have been experimenting with subsets of AI all along, and we'll continue to do so:

1. Segment audiences using algorithms that predict behavior

Many of us have been using tools like Google Analytics’ predictive audiences or Facebook’s Lookalike Audiences, powered by machine learning, to analyze past user behavior and find prospects most likely to convert.

This has helped me stretch my marketing dollar and target audiences most likely to convert; double-digit conversions were already doable. I anticipate more consistent results with the use of GenAI.

2. Personalize content at scale

We know Netflix, Amazon, and Sephora are the trailblazers. Netflix with their content recommendations, Amazon's use of predictive analytics to anticipate customer needs, and Sephora create a personalized beauty shopping experience with AI-powered AR.

The good news is we can create more immersive experiences for our audiences with GenAI. That said, the fundamentals of marketing don’t change. We still have to define our audience personas, map the customer journey, collect the data, and integrate the AI platform into our marketing operations. Some time ago, I encountered a product manager who innocently made a bubblegum remark that digital marketing is simply clicking a few buttons. Perhaps one day, but for now, we can’t escape the groundwork.

3. Automate repetitive tasks

Applying automation with tools like Hootsuite was already common eons ago. I remember being so thrilled to introduce simple auto-replies on social media and websites to ease the load on the digital and customer service teams.

Fast forward to today, chatbots driven by Natural Language Processing (NLP) can answer queries faster than we can say, “Wait, haven’t I answered this question like a hundred times today?”

If you are like me, compiling FAQs for internal and external use was a time-consuming task, but now, it is so much faster with GenAI.

4. Tailor value propositions for different market segments

Did you know it was the application of a machine-learning algorithm that led Unilever to uncover the cultural phenomenon, ‘breakfast for dessert’? They went on to introduce sweet breakfast offerings in the market.

In 2017, Nutella deployed an algorithm to design 7 million one-of-a-kind Nutella jars, and they were sold out within a month in Italy.

When I was a digital product owner in the 2010s, UI/UX developers and I were cracking our heads to figure out how best to customize our landing pages dynamically for different audiences. The good news is that this has gotten easier with AI-driven analytics/tools.

The list goes on.

Let’s continue to do our best work responsibly with GenAI. Stay curious.