Bob Hayes

Data Science and the Quest for Truth

I was interviewed by IBM to share my thoughts on a topic related to data science about which I’m passionate: How do we know what we know and, once we know it, how do we know it’s the truth? IBM turned that interview into a comic strip (see below) ...

Customer Success Executives Need to Answer These Three 3 Critical Questions

In today’s subscription-based economy, customers are no longer trapped in long-term contracts; instead, they are able to jump to competitors easily when they become dissatisfied with their current vendor. Consequently, many subscription-based and SaaS ...

4 Reasons Why Customer Retention Matters to Your Customer Acquisition Efforts

Business growth depends on acquiring new customers and keeping them around for a long time. Yet businesses are over 2x more likely to focus on acquisition efforts than they are retention efforts. In today’s post, I want to discuss why busines...

Salaries of Data Scientists and Machine Learning Engineers From Around the World

Annual salaries for data scientists and machine learning engineers vary significantly across the world. Based on a 2017 Kaggle survey of data professionals, countries with the highest paid data scientists and machine learning engineers (in USD) were: U...

Top 5 Paying Data Science and Machine Learning Jobs in the US

A recent survey by Kaggle revealed that the annual median compensation (salary + bonus) of data professionals in the US was $118K. US data professionals who self-identified as machine learning engineers, software developers and data scientists had the ...

My Highlights from IBM Think 2018: Data Science, SPSS, Augmented Reality and the Customer...

I attended IBM’s inaugural Think event in Las Vegas last week. This event, IBM’s largest (estimated 30,000+ attendees!), focused on making your business smarter and included keynotes and sessions on such topics as artificial intelligence, data science...

Top 10 Challenges to Practicing Data Science at Work

A recent survey of over 16,000 data professionals showed that the most common challenges to data science included dirty data (36%), lack of data science talent (30%) and lack of management support (27%). Also, data professionals reported expe...

Data Days Video Series: What is Data Science?

I like sharing my knowledge about the power of data and analytics. This knowledge can can help business leaders and citizens understand how the world works, improving how they manage their business and make better decisions to improve their personal li...

Top 10 Platforms and Resources to Learn Data Science Skills

A recent survey of over 16,000 data professionals showed that the most used platforms/resources included Kaggle, Online courses and Stack Overflow Q&A. Additionally, the most useful platforms/resources included Personal Projects, Online courses and...

A Majority of Data Scientists Lack Competency in Advanced Machine Learning Areas and Techniques

Data science requires the effective application of skills in a variety of machine learning areas and techniques. A recent survey by Kaggle, however, revealed that a limited number of data professionals possess competency in advanced machine learning sk...

Machine Learning Engineers and Data Scientists Report Highest Job Satisfaction Among Data Professionals

Results from the Kaggle State of Data Science and Machine Learning survey of data professionals revealed that job satisfaction varies widely across job titles. Data professionals who reported the highest level of job satisfaction were: 1) Machine Learn...

Top Machine Learning and Data Science Methods Used at Work

The practice of data science requires the use algorithms and data science methods to help data professionals extract insights and value from data. A recent survey by Kaggle revealed that data professionals used data visualization, logistic regression, ...

Which Data Science Tools are Used Together?

Analysis of usage of 48 data science tools by over 10,000 data professionals showed that data science tools could be grouped into a smaller set (specifically, 14 tool groupings). That is, some data science tools tend to be used together apart from othe...

Most Used Data Science Tools and Technologies in 2017 and What to Expect for...

The practice of data science requires the use of analytics tools, technologies and languages to help data professionals extract insights and value from data. A recent survey by Kaggle revealed that data professionals relied on Python, R and SQL more th...

Use Machine-Assisted Predictive Analytics to Capture Your Customer’s Heart, Mind, and Pocketbook!

As users/customers engage with a company (their products, services, surveys), they generate a lot of data about their behaviors and interactions with the brand....

Brands In One Word – Equifax

We recently collected feedback about Equifax using our #BrandsInOneWord approach to measuring attitudes. This method requires each respondent to provide one word that best...

To be Successful at Data Science, Think Batman, Not Superman

Data professionals talking data science. Click the image to watch our discussion on theCube. I recently made a Batman analogy when discussing the topic of...

Why You Need to Adopt Data Science and Machine Learning in your Customer Experience/Success...

A study of 80+ companies showed that analytical leading companies (those who use analytics to gain a competitive advantage), more so than analytical lagging...

Data Science Helps Answer 5 Important Questions About Customer Churn

Business professionals are relying heavily on the practice of data science to answer important questions to improve how they manage customer relationships. Data scientists,...

Demystifying Data Science For All

I’m all for helping educate the world about the power of data and analytics. I believe that the power of data science can help...

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