Imagine that I’ve done extensive research on a new car. Safety, quality, reliability. I’ve read customer and professional reviews, researched warranties. After weeks of research, I make a decision, I go to a local dealer, and I buy a new car.

A week later, I receive a targeted ad from Lexus, pulling me into their funnel thanks to their insights into my activity. It isn’t the invasion of privacy that bothers me most, it’s the ignorance of how the targeted ads result in reality.

This theme is common in how companies are applying new technologies to the core business. Every time I see a press release on a large company’s investment in AI and machine learning, I think of the colloquialism, “missing the forest for the trees.”

The perceived opportunity to apply these technologies has been in sales and customer service. I am maniacal about detail, so any advantage in customer-facing interactions is, in my view, worth the investment. According to Forbes, $75 billion was lost last year due to poor customer service. This compares to lost revenue of $62 billion just two years prior.

A failed customer interaction is very costly to any business. This is becoming even more true. A separate study polled consumers about switching services due to poor customer service. Baby Boomers have the least propensity to switch, with only a quarter of all Boomers indicating that they would switch as a result of poor service. Millennials, on the other hand, are nearly 2.5x more likely to switch services due to a poor customer service experience.

With more and more data available on customers, and with more and more technology becoming available every day, how is it that the cost of failed customer interactions continues to grow?

Strategically, companies should be two steps ahead of the opportunities to use technology to make the company better. Operationally, companies should worry less about what might be different in five years, and worry more about those things that are just as true now as they have always been. In using technology to drive the business, it is sometimes easy to get caught up in everything that has changed, but it is smarter to focus on what hasn’t.

First was the rise of analytics. A computer company could make inferences like, “based on last year’s data, 10% of our revenue comes from laptops.”

The next logical step is data science. “Based on representative secondary data from last year as well as external data, next year 14% of our revenue will come from laptops.”

From data science, machine learning is possible. “Because of the activity of this user on our website today, there is a 50% chance that she buys a laptop.”

And finally, even artificial intelligence. “Because of the activity of this user on our website from two different devices today, I am going to ask her if her partner is also shopping, and, if so, there is a 50% chance that she buys two laptops.”

And yet, too many organizations attempt to jump from analytics into artificial intelligence, without ever having asked the question, “why are people buying our laptops?” or “why aren’t they buying our desktops?”

It is an honest mistake. These companies are only seeking to take advantage of what is available. They are fearful of being left behind, of missing out on the ROI of machine learning. They look to tech companies like Uber and Netflix for thought leadership.

Ironically, the simplest and cleanest products win the hearts of the buyer. Netflix started by solving the customer problem of paying late fees, going to a physical location, wading through advertisements. They happened to take advantage of technology along the way.

Uber solved the problem of calling a car in advance. Uber solved the problem for those who needed an on-demand taxi, but did not live on a main avenue. It turns out they had to use technology to solve those problems.

For that theoretical computer company, the best ROI would not be on 2018 technology like machine learning to help them sell laptops. It would be on 2006 technology like making it easier for a customer to sign in and search for products.

Don’t miss the forest for the mechanical trees.