This week’s roundup discusses what to consider when strategizing advanced analytics initiatives, tips for using data science and statistical tools to optimize digital marketing programs, how to avoid data bias in machine learning, and a recap of last week’s webinar Marketers vs. Machines: Can Your Experience Beat Our Models?.
by Troy Hiltbrand, Chief Digital Officer at Kyäni, featured on TDWI
As you take steps to become a top performer in your industry, you will likely evaluate multiple advanced analytics initiatives. As you do, apply the ABCs (Alignment, Building Blocks, Cost / Value) and you can more effectively assess whether your proposed advanced analytics initiative is a good fit for your organization.
by Kimberly Parish, Journalist, featured on thebusinesstactics.com
Since businesses are increasingly relying on data to promote data-driven decisions, they are also incorporating data science to streamline their digital marketing strategies. Unlike the “hunches” of Mad Men, today’s marketers have the power to leverage data and statistical tools to produce results that add tremendous value to businesses.
by Kalia Barkai, Data Scientist and Designer, featured on Design Indaba
When we start to blindly give machines decision-making power based on their precision and objectiveness, we may, unintentionally, be perpetuating prejudices ingrained in the data. This is because the predictions made by algorithms are entirely based on the data provided by people. If the data is biased, the model will be too. This is an ever-more problematic situation as business processes become further automated.
presented by Lityx and Concord Direct
Last week, Lityx and Concord Direct partnered up to present an interactive webinar, using real data to demonstrate how predictive analytics can dramatically impact fundraising campaign ROI for nonprofits.
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