Melissa asks, “How can companies leverage data — their most valuable asset — as a competitive advantage?” As part of the IBM #WinWithAI Summit, this is a critical question. What are the uses of data? Data as the end product, for analytics and insights Data as the source for training machine learning models Data as…
As part of my work with IBM in the Win With AI Summit, one topic I’ve been asked to address is what technologies will impact AI strategies and rollout. Register for the IBM Win With AI Summit in NYC here. When we look at the data science lifecycle, we see that a healthy portion of…
Updated: Watch this video for more in-depth explanation of 5 different scenarios. One of the axioms of statistics is, “correlation is not causation”, meaning that just because two data variables move together in a relationship does not mean one causes the other. The most common textbook example of this axiom is that consumption of ice…
Melissa asks, as part of the IBM #WinWithAI Summit: “How can enterprises be proactive about data privacy and regulation?” Want to know why we’re having conversations about data privacy and regulation? It’s because marketing has no governance. It’s the Wild West, with CMOs buying every technology available and no one conducting the orchestra. Marketers need…
According to Gartner, 30% of all B2B companies will employ AI to augment at least one of their primary sales processes by 2020. Don’t wait for the future – start implementing now, with today’s technologies. Driver Analysis Prospect and lead qualification Better sales analytics Time-Series Forecasting Sales enablement Sales forecasting Revenue forecasting Text Mining/Natural Language…
In today’s episode, we review the 4 main challenges facing enterprises with data: Volume Veracity Variety Velocity AI is built on data; poor data leads to poor machine models, which leads to poor outcomes. What’s the solution? The Trust Insights 6C Framework for Data is what every company must implement to prepare for AI: Clean…
Sheri asks, “What is AI good at? What kinds of problems is it good at solving?” There are two sets of answers to this question. First, we need to know what AI delivers as an outcome: Acceleration of results Accuracy of results Alleviation of repetitive work Second, we look to understanding what we know and…
Kevin asks, “How do we standardize metrics and measurement, especially when different parts of the company do things differently?” Great and very common question. The answer is, unsurprisingly, a framework: Goal alignment Exploratory data analysis Model creation Model validation Model deployment Adoption, training, and compliance Measurement of compliance Refinement and improvement If this sounds familiar,…
Magdalena asks, “Can you share two or three good practices of using data in tracking our efforts?” Great and important question. Many marketers don’t have, for one reason or another, a solid understanding or past experience in statistics. Let’s look at a few of the most basic rules that apply, especially when we’re digging into…
Magdalena asks, “What are your favorite tools to track data and which one are you using on daily basis?” I’m a huge fan of source data, so whenever a practical API is available, I’ll use it. For social media, I use Brand24 and Crowdtangle almost daily. For owned digital, Google Analytics is my one source…
