There’s plenty of buzz these days around all things data. Big data. Data science. First-party. Third-party. Second-party. Data Management Platforms. Customer Data Platforms. Data strategy. Data privacy.
It’s enough to make a marketer’s head spin.
Which is why we asked our data scientists here at Lytics to break it down for us. What is data science exactly? Why does it matter to marketers? What do we need to know about it?
We answered all these questions in depth in our latest white paper—Data Science for Marketers. If you’re interested in the topic, we suggest downloading your free copy.
But if you’re just looking for a quick run-down on what data science is? Here are some basics.
Defining data science for the marketer
At its core, data science is the act of using data to gather actionable insights.
A data scientist typically does this by identifying a goal
(for example: we want to understand where our highest lifetime value customers are located), creating a model to sort the data based on that goal using mathematical algorithms and technical systems, and then interpreting the data that model surfaces to tell a story (for example: clients in Omaha have a 60% chance of becoming high-lifetime-value customers—or newsletter subscribers are more likely to become high-lifetime-value customers than those who don’t subscribe).
If you know that Texans are better customers, you can funnel more marketing spend to Texas or plan more events there.
If you learn that customers who subscribe to your kitten adoption newsletter are highly likely to buy your line of tiny cat tutus, you can spend your time, energy, and marketing budget pointing them toward said tutus.
If the data serves up a list of customers who love a particular line of products, you can target recommendations to them with new arrivals in that product line.
Data science helps marketers…
So, how specifically can data science help marketers? Here are six use cases we see often:
Data science insights can help you…
1. Create and send content that customers actually want to see
2. Find more prospects that look like your best customers—and fast!
3. Identify customers likely to churn (and send them campaigns, coupons, or content most likely to keep them from churning)
4. Engage customers in the channels they prefer
5. Avoid annoying (or worse, losing) customers with impersonal, too-frequent, or emotionally charged marketing
and nurture your best customer relationships
And companies harness the power of those use cases? They’re winning—big. Data science has helped industry leaders like Airbnb increase conversions by 10% in China, Japan, South Korea, and Singapore. It’s what powers Amazon’s personalization engine, which is responsible for 35% of their sales. And it’s the foundation for Lytics success stories like The Economist, who grew digital subscriptions by 3x and decreased acquisition costs by 80%.