Converting analysis into behavior-changing programs if often challenging for marketers. While descriptive analysis investigates what has happened in the past (i.e., what is the demographic profile of individuals who buy shampoo), predictive analytics uses existing data and trends to predict what might happen in the future (i.e., integrating different data to predict the market share a company might achieve as they enter a new geography).
Predictive marketing company Radius conducted a survey with Demand Metric to identify the key challenges facing B2B marketers and the impact of predictive analytics. The following, from Shari Johnston, SVP and Head of Marketing at Radius, provides insight on how marketers can convert analytics into action.
Kimberly Whitler: What are some of the key findings from the study?
• More than 80% of study participants with an “ineffective” demand generation process report that data quality has a moderate to significant impact on marketing campaigns or sales efforts
• 74% of marketers claim effective demand generation processes grew revenue year-over-year
• More study participants claim to understand predictive analytics well (44%) than are actually implementing or using it (11%)
Whitler: It appears that there is a gap between knowledge and usage of predictive analytics. What advice would you give a CMO who wants to become more adept in predictive analytics?
Johnston: Predictive analytics is a tool that enables marketers to improve their go-to-market strategies and marketing programs. It allows them to focus marketing activity on the prospects who are the most likely to become high-value customers and provides insights that they can use to create more relevant and compelling messaging, content and marketing programs targeted at each customer segments’ needs. Predictive analytics can also be used at every stage of the funnel and applied across marketing objectives, from growing share to expanding into new markets to growing customer lifetime value. Predictive is an invaluable tool because it has so many applications, so it’s important for CMOs to first establish the problem that they are trying to solve, or the outcome that they are trying to achieve and then utilize predictive analytics to focus on the right opportunities. Predictive analytics can be applied in the following ways:
• GTM Strategy: Predictive marketing platforms provide CMOs with greater visibility into what sets their best customers apart as well as a clear picture of their full market potential. This allows them to surface growth opportunities and untapped markets so that they focus marketing efforts where it will have the greatest payoff.
• Targeting & Messaging: CMOs can use predictive to determine their ideal customer profile(s) and prioritize resources on the best customer segments for their business. By understanding the DNA of tier A customers they can deliver customer-centric campaigns with messaging personalized to what resonates with each profile.
• Outbound Marketing: With predictive, CMOs can drive customer acquisition and revenue growth by filling the funnel not only with more leads but with leads that are most likely to turn into high value customers. They can pinpoint net-new accounts as well as leads already in their CRM who are the most likely to convert.