Customer Data & Analytics Blog

The revolutionary role of AI in B2B marketing

Greg Peverill-Conti | 3 minute read

Over the years, I’ve had the opportunity to work with a number of companies that lie at the intersection of audiences, data, and technology. As time has passed, many of the challenges associated with using data to reach potential customers have been solved. Amassing audience information? Check. Recognizing a prospect across platforms and devices? Check. Integrating information and insights into a range of sales and marketing technologies? Check, again. Many of the fundamental problems of data-driven marketing have been recognized and addressed.

Topics: Customer Tech Thought Leadership

Becoming a highly-successful citizen data scientist: 7 key traits

Chuck Leddy | 3 minute read

Over the course of two prior blog posts, we’ve explored a major trend in data science: the emergence of the citizen data scientist (CDS) and how a CDS can effectively collaborate with professional data scientists to unlock the massive business potential of data. This post describes the 7 key traits of a successful CDS, traits that enable them to drive unique business value through data analytics.

Topics: Data Operations

Successful marketing campaigns begin with customer data and machine learning

Abhi Yadav | 2 minute read

If you’re a data scientist, you’re familiar with the many processes data must go through before it can be used for machine learning models and analytics. If you’re a marketer, you may not be aware of the lengthy journey customer data takes before it reaches you. This post highlights some of the processes customer data goes through before it is made available to marketers for customer analytics and marketing campaigns.

Topics: Customer Analytics

SiriusDecisions Summit takeaways: Get on the Revenue Operations bus & more

Christina Tramontozzi | 3 minute read

This year’s SiriusDecisions Summit, or ‘Summit’ as attendees fondly abbreviate it, highlighted the importance of cross-departmental alignment to drive a customer-obsessed revenue operations strategy.

The event opened with a keynote on togetherness, this year’s show theme, that highlighted the importance of the initiation of work. It’s no longer about having an amazing product but the right processes and systems in place in order to achieve high performance. It’s no longer enough to be good, said one SiriusDecisions analyst, but how organizations set themselves up for success.

Topics: Customer Intelligence

Predictive modeling techniques used in marketing

Janet Wagner | 3 minute read

The concept of predictive modeling has been around for decades, and it involves collecting data, formulating a statistical model, making predictions, and then revising the model as more data becomes available. It is only in recent years that the use of predictive modeling techniques in marketing has taken off- thanks to the abundance of customer data available. There is a wealth of internal and external data that data scientists and marketers can leverage to make predictions about customers such as the propensity to engage, convert, buy, and churn. This post highlights two common predictive modeling techniques used in marketing.

Topics: Customer Analytics