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Technology companies like Uber and Jawbone collect massive and intricate datasets about consumer behavior, and in the process, they’re tackling critical issues with data science. These kinds of innovative organizations are revolutionizing the way businesses interact with each other by automating the complex techniques data scientists use to extract value from big data. And as a result, we’re seeing a lot more interest in the impact data science can have on the enterprise organization.
Becoming a data-driven marketing & sales organization
B2B marketing and sales executives are no strangers to data. In every area of the marketing and sales funnel, data drives decisions. On the marketing end of the funnel, data drives decisions about which market seg
ments to pursue, how to identify the best new prospects, which opportunities to re-engage with, how to increase conversions, and how to measure success. Today’s smartest marketing leaders use predictive marketing algorithms built on data to make better business decisions.
However, to run a truly data-driven organization, marketers need rich proprietary data sets, real-time integrations, sophisticated record matching, machine-learning — and they need it delivered through intuitive software. Despite the rise of the marketing technologist, most marketers just aren’t wired to grapple with billions of unstructured data points while developing strategic messaging roadmaps.
Matching your own CRM data to a massive database of businesses
Every time you record a customer interaction in your CRM, you store data about customer behavior. Most companies hold incredibly valuable insights in their CRM and marketing automation systems, but they don’t have the time or the technology to identify those insights. Companies like Radius help marketers find insights by matching CRM account data to a proprietary database that tracks tons of signals about every business in the US. By matching our customers’ CRM data to our data, we can determine which signals impact pipeline activity — even if our customers have never evaluated those signals before.
On the sales end of the funnel, data drives decisions about which prospects to contact, when and how often to contact them, on which channels to conduct prospect outreach, building pipeline, forecasting revenue, and measuring sales rep success.
InsideSales.com uses data science to solve some of the challenges salespeople face in the qualification and conversion processes. InsideSales.com tracks call and email data for customers, and applies machine learning to predict which channels perform at which times, as well as which leads are most likely to convert, qualify, and close.
Adopting predictive intelligence
Rather than developing these complex systems in house, most B2B marketers look to technology partners that can help them achieve better results using data. Today, the best-funded companies in the marketing and sales space use data science to build predictive tools.
At its core, predictive analytics refers to the practice of analyzing current and historical facts to make predictions about the future. The science of predictive analytics requires statistics, modeling, data mining, and machine learning.
“It’s math, not magic,” says Mick Hollison, CMO of InsideSales.com, the sales acceleration company that’s developed a patented technology which uses data science to predict lead conversion, called Neuralytics.
A 2014 Bizo report on data-driven marketers found that less than 20% of B2B marketers feel that their organizations use data well. A number of chief marketing and sales officers face pressure from CEOs to hire data scientists, but skilled data scientists are some of today’s most sought after professionals; building data science teams often isn’t a feasible goal for modern marketers and sales professionals. And marketers that try to mine insights from their data without the help of data scientists struggle to stay ahead.
Building an Intelligent Marketing & Sales Funnel
We refer to the Intelligent Marketing & Sales Funnel as the revenue process that uses data science to find, convert, and close customers. The Intelligent Marketing Funnel isn’t your average conical funnel that moves leads from the top to the bottom in a linear fashion. The Intelligent Funnel uses insights from won customers and lost deals to build audience segments for targeted campaigns, identifies which new leads within those segments are most likely to convert, and predicts when and at which price point opportunities will become customers.
The intelligent funnel automatically suggests how you should market based on a data-driven understanding of your customer, and recommends the most efficient and effective sales actions to help you close your most valuable prospects.
Data science has been slowly revolutionizing the way businesses interact with each other for decades, and the movement has finally begun within the sales and marketing organization. We’re currently seeing a swift rise of importance in the sales and marketing leadership roles as tech giants at Oracle and Salesforce turn their attention to the CMO, and the marketers and sales leaders that align with data science have an unprecedented opportunity to solve major problems from their helm at the sales and marketing table.
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