Chief marketing officers (CMOs) are under tremendous pressure to more effectively use the customer data that’s available for targeting, personalization, and campaign execution across different channels. With the wealth of data that’s available for businesses to draw on (40 zettabytes by 2020), and as CEOs and organizational leaders become increasingly aware of the power of Big Data and analytics, most CMOs recognize that they have to take advantage of the available cutting-edge tools and information to deliver the goods.
Unfortunately, too many marketers are behind the curve when it comes to using customer data and predictive analytics. Just 24% of marketers use data for actionable marketing insight; meanwhile, 45% of the marketers surveyed say they lack the capacity to analyze Big Data.
The right analytics tools make a huge difference for CMOs, including giving them access to real-time data streams and data visualization capabilities that strengthen decision making by enabling marketing leaders to quickly grasp emerging customer or marketing performance trends.
Three Big Questions That Data Visualization Can Answer for CMOs:
1. Which customers and prospects are most likely to respond to offers? It’s not enough for CMOs to simply view data reports to gauge how email, print, billboard, mobile, multimedia, and other types of marketing campaigns are faring.
Data visualization techniques enable CMOs to plan marketing campaigns more effectively by empowering them to determine which customer segments are most likely to respond to a specific offer. For instance, a marketing team for a sporting goods retailer uses data visualization and predictive analytics against recent transactional and behavioral information to identify the types of golf products a certain customer segment (e.g. high-income males, ages 35 to 49) is most interested in purchasing.
Data visualization techniques bring these insights forward to empower marketing leaders to make decisions around individual or bundled product offers. These insights can be used to help marketers craft relevant messaging for that target segment. Narrowing the target segment to the most likely buyers can also help reduce campaign costs while driving higher response rates.
2. Why did customers and prospects respond to offers? Predictive analytics and data visualization techniques also enable CMOs to identify not only whether customers and prospects respond to offers, but why they respond to offers as well as the types of messaging that certain customers identify with in specific channels.
For example, a wireless carrier can use data visualization techniques to plot a heat map of the types of messaging and channels leveraged that lead to the highest conversion rates. The heat map could signal to the CMO that millennials who were targeted responded at a much higher rate to offers that were sent as SMS alerts versus newspaper, television, or other channels.
From there, the CMO uses data visualization to more closely examine the wording of different messaging that were used, and the type of messaging that led to the highest conversion rates with specific customer segments.
3. What are the characteristics of high-value prospects that we want to target? CMOs are also under pressure to attract not just new customers, but the most profitable new customers.
Data visualization methods can be used to create relational maps and trees that demonstrate the key characteristics of a company’s most profitable customers—including demographics, behavioral, education, family or lifecycle status—to identify the traits most sought after among prospects.
These types of insights enable CMOs to refine their marketing efforts with prospects, reduce campaign costs, and drive higher performance.
Explore how data visualization can help your organization. Try Spotfire today.
