Survey: Market Rewards B2B Predictive Marketers

Business-to-business marketers who use predictive analytics are rewarded with better revenue and market position, according to a recent Forrester Consulting survey. The study tapped 150 respondents from market-leading B2B firms in a range of industries, dividing them into predictive marketers, those using modeled data for forecasting and scoring, and "retrospective marketers" without predictive analytics. The survey, commissioned by predictive marketing firm EverString, found that B2B predictive marketers are 2.9 times more likely to have revenue growth above the industry average, 2.1 times more likely to occupy a commanding leadership position in their product/service market, and 1.8 times more likely to exceed company goals when compared with retrospective marketers. No wonder 89% of the B2B marketers interviewed included predictive analytics in their 2016 plans, either initiating or expanding implementation! Some 49% already used predictive marketing, 44% said they planned to expand or upgrade existing predictive implementation, and 40% planned to initiate predictive efforts within 12 months. Equally interesting, most of the marketers (78%) saw a shift in their role from demand generation to deal acceleration, requiring involvement in the sales cycle beyond pouring leads into the top of the funnel. And here is where predictive marketers led retrospective counterparts again. Predictive marketers showed effectiveness across the customer life cycle, with 49% listing two or more customer discovery tasks (building brand equity, audience targeting, identifying best account types, etc.) among their top three best practices, balanced by 51% including two or more tasks from later in the sales cycle (such as qualifying leads and managing the end-to-end customer experience). Retrospective marketers focused mainly on customer discovery in naming their top three best practices (70%). Marketing success with any stage in the sales cycle is still all about the data, however. Predictive and retrospective marketers agreed that their two biggest marketing challenges were ensuring quality data from a variety of sources (47%) and managing data from a variety of sources (47%). For a Forbes magazine summary with a link to the full report: http://www.forbes.com/sites/louiscolumbus/2016/01/24/89-of-b2b-marketers-have-predictive-analytics-on-their-roadmaps-for-2016/#147e0488d291

Turn Aging Behavioral Data From Problem to Opportunity

Database marketers focused on quick response to customer behavior tend to discount aging or expired behavioral data, creating an ongoing "data atrophy" problem. And that's a mistake in our experience. We agree with veteran database marketer Stephen Yu's recent Target Marketing magazine post, which argues that marketers need to see their aging and expired behavioral data as an opportunity rather than a problem. Issues arise because while targeting is improved when demographic or "firm-ographic" data is combined with behavioral data (transactions and clicks, for example), behavioral data is both harder to collect than geo-demographic data, which can be appended to fill gaps, and has a shorter shelf-life. The value of a hotline list evaporates quickly, and delayed response to real-time mobile or online actions can misfire, even backfire. But aging behavioral data still has value, and formerly hot data can be warmed up--especially if handled appropriately as Yu suggests. One way is to go from simple time stamps to measurements of intervals between events. How many weeks have elapsed since the last purchase? What are the average number of days between transactions? What is the average number of weeks between new product release and actual purchase? Marketers should also measure by channel to catch when an in-store or catalog buyer becomes an online buyer, and for which items. Yu points out that by collecting, maintaining and transforming historical behavioral data, marketers can use it for more effective targeting and personalization. Scored behavioral data become predictors in models identifying “cutting-edge buyers,” “bargain seekers,” “online buyers of repeat items,” “infrequent high-value customers,” “frequent small-item buyers,” for example. Yu concludes: "Today’s data become historical data in a blink, but we still have a lot to mine there. And such mining is possible, only if we arrange the data properly and let it age gracefully using statistical techniques. That is the way to personalize messages constantly for everyone, instead of reacting to real-time data only sporadically for a fraction of your audience." For the whole post, see http://www.targetmarketingmag.com/post/data-atrophy/

Want to Rev 2016? Commit to Data-Driven Marketing

Whether it's the latest digital marketing trend or traditional direct mail, bottom line success depends on smart use of targeted customer and prospect data. So for all those seeking growth and profit in 2016, we wanted to pass along five great data-driven marketing goals proposed by database marketing veteran Mike Ferranti, founder and CEO of Endai Worldwide, in a recent Target Marketing magazine post. Ferranti starts by urging investment in a scalable prospect database program, which requires mating transactional data about your best customers with other data about them (demographic, psychographic, behavioral) to find the most predictive factors for targeting prospects who will respond and convert into more good customers. His No. 2 suggestion is identifying the gold customers in your database for new loyalty programs to "retain and delight"--and that means going beyond personalized e-mail and a nominal discount now and then. A true investment in VIP customers pays big dividends. A third idea for data-driven growth is to use your analytics-optimized database to identify customer purchase patterns for targeting by next likely customer purchase (before competitors snatch a sale). Similarly, the database can be modeled for targeting by next likely product or segment purchase, timing to close gaps otherwise filled by competitors or lower-priced buys. Ferranti's fifth suggestion is aligned with all of the above: improved segmentation that structures for queries and segmented targeting to optimize sales from both existing customers and acquisition of new customers. Are these easy goals? Heck, no, but they pay off in terms of profit and sales growth--and we are ready to help any clients who want to get started. For more discussion, see the full post at
http://www.targetmarketingmag.com/post/5-data-driven-marketing-catalysts-2016-growth/