Recent Blogs
Have you started using artificial intelligence (AI) and machine learning (ML) in your analytics initiatives? What kind of results are you seeing?
The analytics chasm fundamentally boils down to one thing: a lack of analytics capacity within your organization.
When you think about decision making in the context of those steps, you realize that the information value of data is perishable, and it decays with time. If you remove the analytics waste from your decision-making process, you can become much more competitive.
Dynamic and uncertain marketing conditions have created new opportunities, but organizations will need to prioritize their analytics investments to seize them.
Given the historical context and a high-level definition of how AI is applied, how can we create a practical definition of AI? In my mind, the definition of AI is quite simple. Artificial Intelligence = Data + Analytics + Automation
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