AI-Driven GTM Strategies: 10 Costly Mistakes to Avoid
Explore 10 common machine learning pitfalls in Go-To-Market (GTM) strategies and how to avoid them. Understand how AI is used for customer segmentation, lead scoring, and market analysis.
Show Me The Data is a curated collection of articles that explore ideas from adjacent disciplines to help you make better business decisions.
Explore 10 common machine learning pitfalls in Go-To-Market (GTM) strategies and how to avoid them. Understand how AI is used for customer segmentation, lead scoring, and market analysis.
Is Net Promoter Score the definitive measure of customer satisfaction? Unveil the limitations of NPS and the richer insights from multiple metrics.
Unlock actionable insights with essential tools for precision in measurement, tailored for small datasets.
How does one measure intangible things like “public image,” “innovation,” or “IT security”? Despite what you might think, these things are not “unmeasurable.”
The single most effective thing organizations can start doing to be more data-driven is understand how to get the most from their metrics and measurements.
Introducing a better approach for measuring the cost of bad data to your business. No hand-waving required.
The Chasm Trap and the Fan Trap are two common SQL JOIN mistakes that cause unwanted duplicates in the result of queries. The Unified Star Schema is a powerful new solution to these old problems.
Measuring the value of data is often ignored because it is seen as an intangible asset. However, data assets can drive significant value for your business, and this value can be quantified.
40% of all business initiatives fail to achieve their targeted benefits as a result of poor data quality, yet few are investing in measuring their data quality.
The evidence for the business benefits of diversity is now overwhelming, but WHY does diversity lead to better outcomes? In this post, we’ll explore the mechanisms that turn diversity into a competitive advantage.