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AI & Predictive Analytics

AI for Marketing: Myth vs. Reality

AI for Marketing

Behavioral Data Broke Marketing Before digital, marketing was pretty straightforward. Marketers used customer profiles—derived from transaction and demographic data—to segment and run campaigns across a limited number of channels (primarily direct mail and email). But as consumers moved increasingly online and organizations updated their technology to track behaviors across web, email, mobile apps, and more,…

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Four Steps To Keep Data Scientists In Their Happy Place

Data scientists love the analytical work of building and testing new algorithms. Data wrangling—the work of hunting for, validating, connecting, and combining data sets—not so much. In a new article published by Forbes Tech Council, ActionIQ’s co-founder and CIO Nitay Joffe writes about his experience as a software engineer at Facebook, where faced exactly this…

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No Black Boxes

  Last week we published our second chapter in our blog post series on an Enterprise Customer Data Platform. The second chapter was on Freedom & Flexibility. In this chapter we talked about ensuring marketing gets access to the data needed to make decisions and change course on the fly. The first chapter was on…

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Give ‘Em a Break: Let Marketing Analysts Do Their “Real” Job

Despite the fact that the enterprise is looking to grow their analytics ranks, finding and retaining world-class analytical talent is becoming a very hard task. This means more work falls in the laps of companies’ existing analysts, making their life hectic and—sometimes—miserable. This is a potentially deadly problem from organizations trying to compete in a…

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