What 30 Years of Equities Trading Teaches Me About Marketing

I've been interested in trading financial markets for most of my life. For the past 30, it has been considerably more than a casual hobby—and at times, it has been my primary occupation.

I became fascinated with technical analysis: indicators, patterns, probabilities, relationships between markets, and eventually designing my own trading systems. Along the way, I also worked in the financial technology industry as the product manager for eSignal, where part of my job was evaluating trading technologies and understanding how serious traders actually used them.

Finding Signal in the Noise

All of that analytical work has had an unexpected effect on my marketing career. In my own trading, I began developing my own proprietary analytics—not because the world desperately needed another trading indicator, but because nothing quite suited the way I thought or traded. And, more than once, I've had a hypothesis I simply couldn't leave alone until I'd tested it. Spending years looking for meaningful signals buried inside noisy financial data has sharpened the same skills I use to analyze marketing data. It influences how I think about segmentation, predictive analytics, customer behavior and sophisticated account-based marketing approaches such as Target Account Analytics.

Trading Teaches Customer Empathy

But trading teaches me something else about marketing that may be just as important.

It teaches me what it feels like to be the customer.

I'm a demanding consumer of financial technology. I don't simply want to know whether a product has a particular feature. I want to know whether that feature works with my indicators, my workflow, my trading methodology and the decisions I'm trying to make. Sometimes a seemingly insignificant detail matters enormously because I'm the person actually using the product.

Iterating with AI for Real-World Workflows

I was reminded of this recently while working with AI to improve some of those proprietary analytics for trading TQQQ and SQQQ. The challenge wasn't simply writing ThinkScript code. The AI had to understand how I thought about the relationship between the two instruments, how my existing indicators worked, how I interpreted their signals and how the resulting information needed to fit into my workspace. The first solution wasn't the end of the process. We iterated until the analytics became useful to me.

That's a pretty good description of customer empathy.

Marketing data can tell us an extraordinary amount about customers—what they clicked, downloaded, purchased, watched or ignored. Analytics can help us identify patterns and even predict what someone may do next. I've spent much of my career doing exactly that.

But data doesn't necessarily tell us why something matters to the person on the other side of it.

That's where empathy becomes so valuable. The best marketing doesn't simply identify a customer or predict a behavior. It understands the problem that person is trying to solve.

Thirty years of trading made me a better analyst.

Being the customer makes me a better marketer.

Are your marketing analytics missing the human element?

Whether you need to extract clearer signals from your customer data or translate complex technical capabilities into messaging that resonates, BB Marketer can help. Let's Talk