Customer insight fundamentals: Building a framework for access and activation
If you’re going to make an investment in machine learning and seek actionable insights from your customer data, you need to approach the effort strategically.
Predictive marketing
Data-driven solutions to help you stay ahead of the curve, whether you're a marketing team of 1 or 100.
Customer insight fundamentals: Understand your customer data to make better predictions
Most data scientists practice some version of what could be called a data survey; the goal is to surface meaningful patterns, gaps, and anomalies with an eye toward prediction.
Customer insight fundamentals: Data requirements for Customer Insights Reports
The rule of thumb is the more data the better. The more information our models can train off of, or the larger data set to glean insights from will allow for much more meaningful results versus just being based on a random or predetermined set of data.
Customer retention requires data-driven predictions
To scale revenue and drive profitability, companies need to shift their focus to improving retention rates and increasing the average lifetime value of their customers.
Four ways to extend your acquisition spend with data science
As the first step of building out a loyal customer base, customer acquisition is a high priority for marketing teams. This article explores four ways you can leverage data science to extend your acquisition spend farther to build a loyal customer base.
Consider broader changes in your customer data when adjusting your SEO/SEM tactics
As consumers’ spending habits change, companies will see shifts in their customer base... The ability to quickly identify and act on these big-picture changes is just as important as adapting to changes in the more granular aspects of their marketing strategy.