There’s no shortage of discussion about the possibilities of big data and advanced analytics for today’s B2B marketers.

Sales and marketing analytics covers a spectrum of data and techniques, from historical to exploratory to predictive analysis. Historical analysis, which examines past activities or results across a range of categories, is used to report on marketing and sales performance, monitor process compliance and improve future effectiveness.

Exploratory analysis conducts what-if analysis to identify scenarios that may result in improved outcomes. Predictive analysis uses the outputs of historical and exploratory analysis to anticipate outcomes and find the best ways to improve effectiveness. Big data plays a role in all three forms of analysis, although more so in exploratory and predictive analysis.

Despite low adoption rates, many B2B marketing and sales organizations are keenly interested in big data and advanced analytics. They recognize that analytics can yield better insights into markets, potential buyers and customers by providing the following:

  • Improved understanding of customer interests, perceptions and likely purchase actions
  • The ability to predict and manage customer churn
  • Improved capabilities to estimate customer lifetime value and make better decisions about customer retention and growth
  • Improved content strategy resulting from insights into customer and prospect communications preferences
  • Territory optimization and customer prioritization
  • Better insight into what customers are likely to buy now and what they might buy next

    • How can an organization take the next step and gain access to the benefits of advanced analytics? In my next post, I’ll describe the five required elements of an analytics foundation.