Category: Data
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You Ask, I Answer: Qualitative vs. Quantitative Marketing Data
Magdalena asks, “Which is more important for marketers, qualitative or quantitative data?” This common question is a false choice. Both are equally important and inform each other. Watch the full video for an explanation with details, and ways to gather both. Can’t see anything? Watch it on YouTube here. Listen to the audio here: Download…
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You Ask, I Answer: Starting from Scratch with Marketing Data
Seth asks, “I just took over a marketing volunteer role for a small non-profit and they have no data repository. Like, nothing but disparate spreadsheets; some with donors, some with event attendees, some prior volunteers, etc. What should I be thinking about while building from the ground up to make sure I’m setting them up…
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You Ask, I Answer: Augmented Analytics Viability?
Michael asks, “Have you heard of augmented analytics (defined by Gartner)? It seems to me it means your job will get easier in the short run and you’ll be out of business in the long run – if you believe it. I’d be interested in your comments on it.” Augmented analytics is what the rest…
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You Ask, I Answer: Tools for Storing Valuable Information?
Alessandra asks, “How do you keep/store/index all the information you read, and I am sure you read A LOT, that might be useful for future presentations/consulting/business development activities?” Terrific question – it depends on what the information is. Photos: Google Photos. The AI is unbeatable. Notes: Evernote. Short ideas: Apple Reminders. Mind maps: Mindnode maps…
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You Ask, I Answer: Spotting Trends in Analytics?
Julie asks, “What trends should I be looking for in my analytics?” The answer to this question is going to require some math, so pour a coffee and let’s tuck in. In this video we’ll review simple and exponential moving averages, the moving average convergence divergence indicator, and the application of the stock alerting technique…
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IBM THINK 2019 Day 3 Recap: Reducing Bias with IBM
In today’s IBM THINK 2019 Day 3 Recap, we look at the problem of bias in AI and machine learning, the three locations in the development process where bias can creep in, and how IBM helps us mitigate bias with two key products, Fairness 360 and IBM Watson OpenScale. Learn more: – Fairness 360 (open…
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IBM THINK 2019 Day 2 Recap: The Next Frontier
In this video, learn 5 key takeaways from day 2 of IBM THINK 2019 on the topics of finding more AI/ML talent, the use of personas in an AI work, digital transformation and its relationship to AI, finding new opportunities for innovation, and perhaps the meaning of life itself with quantum computing. Can’t see anything?…
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You Ask, I Answer: Qualitative Data Analysis
Dave asks, “How do you interpret the “why”, i.e. if you see data that says actions were taken (or not) how do you determine WHY those actions were taken so you can replicate or avoid those specific marketing tactics moving forward?” No analytics tool focused on gathering “what” data – meaning, what happened – is…