Read customer stories
In our recently launched white paper—Data Science for Marketers—we asked our data scientists to explain why marketers need data science and what exactly it is.
The short answer to that first question, which you may already know, is that data-driven marketing is proven to produce business results. In fact, data-driven businesses are six times more likely to be profitable than their competition.
That’s right, six times more likely.
Why? Another short answer: Data science helps us understand things we otherwise wouldn’t understand. It’s more efficient and cost-effective than the typical marketing spray-and-pray approach. And it’s what makes finding the right customers and speaking to them with the right messages at the right time—at scale—possible.
(For the long answer, download our free white paper.)
But here’s the thing: Even though data science has been proven to drive real business results, most companies still aren’t taking advantage of it. In fact, 87% of marketers still say data is their company’s most underutilized asset.
At least part of the answer is simply this: data science sounds great…and it also sounds hard. It sounds like it comes with a learning curve (and it does). It sounds like it’ll take too long.
After all, marketers have campaigns moving ahead at full speed. They’ve got deadlines to hit. They’ve got goals that they can’t push the pause button on. And so taking the time to harness the full potential of data gets pushed to the side.
Which is a really bad strategy.
Because the truth is that every change takes time (and often money). But keeping our heads down and doing things the same way we’ve always done them is a good strategy for destroying a business.
How do we know? Because we watched what happened to Blockbuster.
Did you know that Blockbuster was the first video company to offer streaming services? They did it before Netflix, before Amazon, before Hulu, and long before the cable networks caught on.
The service was called Total Access and it was available to subscribers for a short time.
They were industry leaders. They had something that could have made them into what Netflix is today.
But they killed the project.
Why? Because they didn’t want to lose their multi-million-dollar late fee revenues—and streaming services don’t support late fees.
The problem here is that Blockbuster didn’t take into account that they had competitors. They thought they could operate in a bubble. They thought they could keep new technology away from their customers and thus keep their late fees.
We all know what happened instead: Blockbuster went the way of the dinosaurs. All because they thought the cost of change was too high—but their competitors didn’t.
So, here’s the point: Yes, incorporating data science into your marketing practices will take time and money. Yes, there’s a cost to change. Yes, there’s a learning curve.
But learning curves aren’t a good enough reason to put off changes that the market demands. They aren’t a good enough reason to ignore the stunning results companies like Amazonand Airbnbare seeing from their data science practices.
Industry leadership and growth mean taking a different approach than Blockbuster—embracing the change that customers demand instead of ignoring it.
Here’s the good news: Incorporating data science into your marketing probably won’t take as long as you think.
Here at Lytics, data science insights, machine learning predictions, and NLP tagging are all built in. Most clients start seeing value within 60 days.
If that sounds intriguing, check out our new guide: Data Science for Marketers. Or chat with one of our experts about how Lytics’ data science insights can support your business goals.