Information Driven Digital Marketing
Data-driven Digital Marketing
5 Killer Examples of Data-Driven Marketing
Guest Author
Guest Author
Last updated: July 21, 2020
Marketing Ideas
Data has the potential to be your most valuable marketing resource. With the right information in hand, you can create scalable, repeatable marketing processes. It’s the marketer’s dream: let your campaigns run on autopilot, so you can focus on the creative side—testing and optimization.
The challenge, however, is that few marketers have the expertise to work with data effectively. You may have never taken a statistics course. You may not have access to data visualization tools. And you may not have the quantitative background that you need to figure out when a metric might be tricking you.
But there is good news: almost every marketer is stuck in the same boat. And we’re all learning together.
data-driven marketing
From first-party to third-party data sources, how can you feel like you’re making the right judgment calls in your targeting and optimization strategy? Learn from the experiences of others to cultivate your own best practices. Here are 5 data-driven marketing strategies that you can learn from and incorporate into your own campaigns.
Data-Driven Marketing Strategy 
Fortunately, you can use publicly available datasets to answer some of these questions. Consider the case of GreenPal, a company that describes itself with an analogy: “Uber for Lawn Care.”
data-driven marketing
From first-party to third-party data sources, how can you feel like you’re making the right judgment calls in your targeting and optimization strategy? Learn from the experiences of others to cultivate your own best practices. Here are 5 data-driven marketing strategies that you can learn from and incorporate into your own campaigns.
Data-Driven Marketing Strategy 1
: Use demographic data in your campaign planning
Outcome: More context in your targeting
Let’s say that you’re looking to upsell a new product idea to your biggest customer segment. You have some data that you’ve generated in house with respect to their user behavior, but there are a few missing details. For one, you might not know much about the weather. Or you may not know about that customer’s overall spending habits and household income.
Fortunately, you can use publicly available datasets to answer some of these questions. Consider the case of GreenPal, a company that describes itself with an analogy: “Uber for Lawn Care.”