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, blockchain, quantum computing and cryptography. I was invited by IBM as a guest to share some insights from […]
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. Predictive analytics and artificial intelligence capabilities provide a way to extract insights from that data to help you improve the customer experience and optimize customer loyalty. Artificial Intelligence and Predictive Analytics […]
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 experiencing around three challenges in the previous year. A principal component analysis of the 20 challenges studied showed that challenges […]
Over 16,000 data professionals were asked to indicate their favorite data science blogs, podcasts and newsletters. The top two favorite blogs were KDNuggets and R Bloggers. The top two podcasts were Becoming a Data Scientist and The Data Skeptic. The top two newsletters were O’Reilly Data and Data Elixir. Data professionals use a variety of […]
I like sharing my knowledge about the power of data and analytics. This knowledge 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 lives, respectively. Toward that end, I am creating a video series called, Data Days, to explore the world […]
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 Stack Overflow Q&A. On average, data pros used around three (3) different platforms/resources to learn data science skills. There are many ways […]
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 skills. About half of data professionals said they were competent in supervised machine learning (49%) and logistic regression […]
Data science methods and related tools (i.g., predictive analytics, machine learning) can help companies improve their customer success programs by answering 5 important questions about customer churn, including what is the current churn/retention rate (e.g., descriptive analytics), who is at risk for churning (predictive analytics), what actions can prevent churn (i.e., prescriptive analytics) and more. […]
Learn how to build your business around the customer using customer-centric measurement and analytics. Available in Kindle and paperback. Learn more about TCE: Total Customer Experience.
Beyond the Ultimate Question: Book includes comprehensive review of Net Promoter® Score (NPS) and presents better measures of customer loyalty and best practices of customer feedback programs.
Measuring Customer Satisfaction and Loyalty (3rd Ed.): Book includes discussion of how to measure the customer experience, including customer satisfaction and customer loyalty.