Analytics dashboards are a critical resource for marketing teams that help support performance tracking, strategic planning, and data-driven decision-making. However, many B2B companies are failing to achieve their potential due to improper construction and application of their marketing dashboards.
These interactions, which marketers often call touch-points, can tell you valuable information about what elements of your marketing programs are working, which drives revenue impact through enabling data-driven optimization of your Demand Generation motions.
In the context of B2B marketing, attribution is the process of understanding what actions or engagements with your brand were responsible for driving leads through the sales funnel until closing a deal. Through designing attribution models, marketing and sales can determine what actions are generating business results and make data-driven decisions about where to invest for more effective nurture strategies.
But building an attribution model for today’s buyer journeys is no easy task. Long sales cycles mean it is hard to pinpoint which engagements with your brand are truly impactful. Leads interact with your brand on a variety of channels, and it can be difficult to identify the right dials to tune to drive multiple decision makers down one sales funnel.
B2B companies are learning the hard way that dirty data comes at a cost: A recent study found that 50% of IT budgets are allocated to data “rehabilitation” efforts. So, what do we mean by clean data? We mean it is accurate, updated, and uniform. Clean data is free of duplicate, outdated, incorrect, or misplaced entries. When analyzed for patterns and segmentation, clean data tells a clear, actionable story about your audience. And this can drive benefits like improved employee efficiency, revenue growth, and sales conversion. Here are some rules for how to keep your data clean.