With over $100 million in venture capital invested in predictive marketing companies, predictive analytics, Big Data, and all that attends are of key consideration to marketers. A Forbes Insights’ study, co-authored by Lattice Engines – The Predictive Journey: 2015 Survey on Predictive Marketing Strategies, based on a survey of 308 North American executives representing companies worth $20 million and above in annual revenues, observes that predictive marketing is becoming the best method for using data analytics in decision making and predicts organisations will soon be investing in it. As predictive selling enters the mainstream, early adopters will lead their markets.
Forbes Insights’ study found that although a massive 86% of executives experiences positive return on investments in predictive analytics technologies, only 13% of companies using these technologies deem themselves highly advanced users. With the growing understanding that data-driven decision making can advance business operations around cross-selling and upselling, identification of new customers, and customer habits, 80% of marketing leaders plan to increase spending on marketing technologies in the year to come.
Furthermore, the report notes:
- 68% of organizations require additional predictive or analytics skills.
- 71% of organizations offer onsite training and education in predictive marketing for employees.
- Six out of ten organisations believe a chief obstacle to be the accurate measuring of a marketing campaign or initiative results.
- 41% of organizations consider the improvement of customer retention to be vital when measuring the success of predictive marketing efforts.
Says Bruce Rogers, chief insights officer and head of Forbes Media’s CMO Practice, “Predictive marketing is rapidly becoming essential to data-driven organizations. Businesses need to close the gaps among sales, marketing, operations and other departments that are made worse by siloed data and systems.”
What it Means for Marketing
Lattice Engines provides predictive applications for marketing and sales, and recently released a new maturity model outlining steps to help CMOs convert their traditional marketing structures into predictive marketing ventures. Lattice’s Maturity Model encourages the leveraging of big data as well as streamlined marketing processes for better predictions of customer behaviour that can be used for efficiency restructuring while driving revenue growth.
In discussions with CloudTweaks, Nipul Chokshi, Lattice Engine’s Head of Product Marketing, stated, “Marketing organizations believe in the benefits of predictive marketing, and as the Forbes study shows, companies are hungry to learn the best way to dive in. That’s why we created the Predictive Maturity Model, to give marketers a blueprint for getting started with predictive marketing and driving outsized revenue gains for their organization.”
Lattice Engines concludes that predictive analysis is vastly enriched when combined with data, process, and technology within a marketing organisation, and believes that marketers should not focus on one model, data scientist, or type of technology, but instead take a systematic approach to marketing. Their new maturity model, A Blueprint for Building a Predictive Marketing Organization, helps marketers understand predictive marketing organizations and measure the current stage of their own organisation. Additionally, the process of maturing and developing one’s own predictive marketing organization is considered. It’s evident that predictive marketing isn’t just about the measurements; it’s about how you put them to work.
By Jennifer Klostermann
Jennifer Klostermann is an experienced writer with a Bachelor of Arts degree majoring in writing and performance arts. She has studied further in both the design and mechanical engineering fields, and worked in a variety of areas including market research, business and IT management, and engineering. An avid technophile, Jen is intrigued by all the latest innovations and trending advances, and is happiest immersed in technology.