At SAP we use analytics to deliver unprecedented insights into customer behavior. In turn, these insights are driving better decision making, better yields from marketing activities, improved customer experiences — and ultimately, delivering more sales. And it’s working. In fact, SAP recently won the 2015 Genius Award for Excellence in Analytics-Driven Strategy.
Instrumental in delivering these breakthroughs is Nancy Fessatidis, who was recently appointed head of Big Data analytics in the Enterprise Analytics organization. In her previous position Nancy led the Insight-Driven Marketing program, which developed and deployed an end-to-end “insight activation” process of marketing analytics tools and processes.
Predicting customer actions
Propensity-to-buy models are the foundation of this capability. These data-driven, statistically-derived regression models produce scores that identify the “likelihood” of an account purchasing a particular product.
Used in marketing since 2007, propensity model scores are embedded into SAP’s marketing processes and have influenced €200M+ in annual sales. Global in scope, there are currently 108 solution propensity models helping marketing to optimize and target campaigns more effectively. In fact, they have been so successful that they are utilized in sales, cloud, and retention programs worldwide.
Increasing opportunity conversion
Similar in style to propensity models are opportunity scoring models. Rather than evaluating the likelihood to purchase, these data-driven statistical models assess the probability of opportunities progressing down the pipeline and becoming a won deal.
Sales managers and executives can not only see the opportunities that are most likely to close, they can also identify those that are at the greatest risk of being lost. As a result, conversion rates have increased, with the top 30% of targeted opportunities delivering 54% of converted opportunities. The incremental impact has been €9.6M in sales.
Improving campaign effectiveness
To help with account-based marketing, Nancy’s team developed a recommendation engine. It determines the next best set of solutions for each account based on the likely interest in a given solution and its value. This methodology also provides the analytic basis for an account ranking engine that compares, segments, and predicts the future value of accounts.
The recommendation and account ranking engines have proved that the top 10% of the marketable universe are responsible for more than 30% of account value. By combining account targeting with audience persona messaging, marketing has been able to improve campaign effectiveness by over 120% compared to typical marketing campaigns. In addition, this tactic reduces the cost of lead generation by 48% compared to a typical campaign.
Learn more about how analytics solutions are driving greater sales and marketing success, and how other SAP executives are leveraging analytics solutions to accelerate insight, anticipate tomorrow, and shape the future.