Last January, a study by Forrester Consulting released some remarkable statistics regarding the role of predictive analytics in B2B Marketing: While 89% reportedly plan to incorporate predictive analytics as a central component of their strategic planning, nearly 93% of marketers say they lack the necessary skills. Success in 2017 will require progress in the adoption of critical predictive analytics strategies.
Defining Predictive Analytics:
What is predictive analytics? At its core, predictive analytics involves analyzing established data patterns to predict future behavior and events.
Predictive Analytics in Marketing:
For marketers, these predictions mean analyzing marketing data for patterns of buyer engagement and behavior. Predictive analytics are used to determine customer responses or purchases, as well as promote cross-sell opportunities. Predictive models help businesses attract, retain and grow their most profitable customers. Using developments in machine learning and predictive analysis, it is now easier than ever to identify hidden opportunity in your customer data – and the best bit is that the opportunities are huge.
5 Key Benefits of Predictive Analytics in B2B Marketing:
- Expanded Social Media Presence: Social media utilizes predictive data to see what people want to see and read more about. In other words, predictive analytics can be used to optimize a company’s use of social media. It means that companies can see trends or phrases from their predictive analytics marketing and use it on their desired social media platforms.
- Generate and Nurture Leads with More Personalized Messages.
- Accuracy: With B2B sales, which tend to have more established marketing patterns, the predictive calculations of machine learning tools are incredibly accurate. Similar businesses have similar needs and therefore the machine draws on existing data that, in turn, leads leads to more accurate predictions.
- Scope of Unknown Opportunity: B2B organizations operating in a broad range of industries many are more likely to find gaps in their marketing strategy. Predictive analytics identifies can broad gaps in a company’s presumed customer profile. In one case, ana;ytics reveal that a client was missing huge opportunities in the education market—our numbers had revealed a whole new industry for our client’s products.
- More Sales: Predictive Marketers are 2.9x more likely to report revenue growth at rates higher than the industry average.
Skill Set: The Challenge of Predictive Analytic
According to B2B Marketing’s Data Skills Benchmarking Report, predictive analytics is the weakest data skill among B2B marketers, their team and their organization:
- Only 7% of marketers surveyed rated their own predictive analysis as “good” or “excellent”
- 41% of marketers surveyed rate their own level of expertise as either “quite poor” or “”
- 52% of marketers surveyed rate their company’s predictive analysis as “poor.”
- 62% of marketers surveyed rate their team’s skills in predictive analysis as either “poor” or “very poor.”
Joel Harrison, editor-in-chief at B2B Marketing, reports that “predictive analysis is consistently the weakest data skill across the board. It’s clear that marketers need to stop merely discussing the merits of using data to make accurate predictions and begin to actively do something about it.”
In 2014 60% of professionals reported rising pressure from upper management to be more data-driven, with marketers feeling a majority of the heat. The Mike Whitelegge, head of big data solutions at Marks & Spencer, links the lack of skills to the lack of necessary training: “If we look forward five years, the types of jobs we’ll be needing to fill have not even been thought of yet,” he says. “I feel the universities could do more than they are now.”
While predictive analytics represent an invaluable and essential tool for developing an effective marketing strategy, finding those with the skills and training necessary to execute this kind of data analysis reprsents a considerable challenge. To help make the work of predictive analytics more accessible, MarketScale has developed a custom suite of analytics tools in an easy-access dashboard. MarketScale’s dashboard provides a user-friendly-interface designed to consolidate an otherwise confused clutter of disparate data sources in a single display. MarketScale’s analytics tools also employ machine learning to organize and produce automated narrativesreports of essential, actionable data. http://www.marketscale.com/