Top BOB Blog Posts for 2017: Data Science, Machine Learning and Customer Analytics Best Practices

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The importance of analytics continues to grow in business and beyond. I did my part this year to spread interest in analytics to more people. All of my top blog posts of 2017 (most reads) are all related to analytics, with posts that address data science, artificial intelligence and machine learning. Below are my top 10 blog posts of 2017:

1. Demystifying Data Science for All – In this blog post, I cover what data science is, the people who practice it and the tools they use to generate insights. You’ll find links to two important events in which I participated this year, IBM’s Data Science for All, and Metis’ Demystifying Data Science.
2.  What Data Science Skills Do you Need in a Big Data World? – Data science skills fall into three broad skill areas. These skill areas are: 1) subject matter expertise, 2) technology/programming and 3) statistics/math. Data science is essentially a way to extract insight from data using these three skills.
3. 25 Data Science Terms Every Customer Professional Needs to Know – I believe that a good first step for customer-centric professionals to leverage customer data is to understand the terms data professionals use when extracting insights from their data. I put together a glossary of terms that you will commonly hear when data professionals discuss data science.
4. Artificial Intelligence: The Customer Experience Imperative – An understanding of customer metrics now, more than ever, requires the proper application of math and statistics that underlie such fields as artificial intelligence and machine learning. The companies that are better able to leverage the data science tools and methods of AI and machine/deep learning will be able to outperform their analytics-challenged competitors.
5. To Be Successful at Data Science, Think Batman, Not Superman – I recently made a Batman analogy when discussing the topic of data science with some colleagues. In this post, I will explore this analogy further.
6. Customer Analytics Best Practices: Free White Paper – Competing on analytics today means integrating data silos, applying machine learning capabilities and leveraging data experts/scientists in your formal customer programs. Download the complete 22-page white paper.
7. What Must You Ask? Comparing Two Customer Survey Approaches – A new customer survey approach that requires only two open-ended questions provides customer insights that are comparable to a longer, more traditional customer survey. This post presents the new survey approach and outlines its benefits to your enterprise.
8. Why You Need to Adopt Data Science and Machine Learning in Your Customer Experience/Success Program – A study of 80+ companies showed that analytical leading companies (those who use analytics to gain a competitive advantage), more so than analytical lagging companies, leverage their data differently.
9. State of Analytics in Customer Programs: Customer Loyalty Focus, Machine Learning Adoption and the Data Science Skill Gap – The use of multiple survey methods is the most common practice across companies (80% of companies). The use of machine learning was one of the least adopted practice in customer programs (38% of companies). Customer professionals lack proficiency in, or access to, three important  data science skills: programming, mathematics, #statistics. Customer professionals said their biggest roadblock was the inability of translating customer insights into business operations.
10. Data Science Reveals the Unintended Effectiveness of Male Genital Accoutrement – The people of American Optdicks created a gag gift to raise money for prostate cancer research. Their product, eyeglass frames for male genitalia, while humorous, could theoretically improve heterosexual women’s ratings of male genitalia. This group of humanitarians reached out to me to employ the practice of data science to conduct a seminal study to help test this proposition.

Thanks for reading my writing. Also, thanks to my social media followers for sharing my work with your followers. In the upcoming year, I plan on writing more on the topic of data science, machine learning and customer experience. I’m also working on a video series to help data professionals, both practicing and aspiring, better use their skills to generate insights.