Brian Kardon is a respected marketing thought leader, a “Top 10 Global CMO,” and a seasoned executive with a 20-year track record of success. He previously held top marketing roles at Eloqua, Forrester Research, and Reed Business Information before taking the reins as CMO at Lattice Engines, a pioneer in predictive applications for marketing and sales. I caught up with Brian recently to pick his brain about the sudden wave of interest in All Things Predictive.
(HS) Brian, I was at Dreamforce in San Francisco earlier this month and it seemed like every other exhibitor was trumpeting “analytics”. Even Salesforce announced their own Analytics cloud. Why do you think analytics is suddenly such a hot topic?
(BK) Several factors have come together to bring analytics to life. First, the era of big data is here with the volume and velocity growing exponentially. Social media has contributed greatly, certainly, but so has the overall increase in web traffic, digital transactions, video and apps. The sheer volume of these data presents an unprecedented opportunity for marketers. The second is about the technology. Advances in technology now allow us to cost-effectively capture, store, share, analyze and visualize these data – things like faster CPUs, cheaper memory, and massive parallel processing. Exploring big data with analytics is within the reach of more organizations than ever before.
The use of analytics in B2B marketing and sales is actually lagging other industries. We see it all around us. It is used in healthcare to determine which patients are at risk of developing certain conditions. It is used in fraud detection to predict which transactions are most likely to be fraudulent. Online retailers like Amazon and Netflix use it to make movie and book recommendations that are predicted to result in a purchase.
(HS) Lattice offers “advanced predictive analytics” for marketing and sales. To a layman, how would you describe the power of predictive analytics solutions?
Sales and marketing teams have to answer some pretty important questions every day. For example: Which of my prospects should I call first? Who is most likely to buy? Why? What else can I sell to my current customers? Which of my customers are likely to churn? For the most part, companies rely on instinct and, perhaps, lead scoring via marketing automation. Predictive analytics is different. It relies on data science to answer these questions by analyzing past “success events” and providing predictions based on a model. It is science, not guessing. And it is being used by organizations today. It is not some future thing. It is now. Read More