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But to do this properly, you need a true end-to-end process or solution. The fundamental challenge to performing a true ROI is that you need to be able to isolate and measure the value of the new data that you’ve added.įor example, if you’ve enriched your records with more granular industry and job function data, how do you track the impact? Creating a custom field around job function and level is certainly a data enrichment best practice.
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The science of ROI calculations and formulas is a topic that deserves its own blog post.
CRITICAL OPS ROADMAP HOW TO
While most everyone can agree to the need to upgrade the state of your data records, the problem has been how to assess the tangible value or ROI of better data. Fewer than 10% of marketing and sales leaders at some of the most data-centric companies believe enough in their data to do the type of personal outreach and marketing essential to engaging, nurturing, and making a sale. In a 2021 survey of sales operations professionals by Modern Sales Pros, only 6% of RevOps leaders said they had a high level of confidence in their ability to personalize their sales and marketing efforts. Most companies don’t know enough about their prospects to create a firm ICP.
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And if they do this analysis, it’s usually hampered due to the lack of data fields that are captured. How can this be you ask? Truthfully, few companies perform the proper analysis of their best-fit customers as well as their their customers who are less than ideal. Surprisingly, too many companies, even large and well-financed ones, still struggle with getting this critical metric right. One of the biggest casualties of bad data is often a company’s ideal customer profile (ICP). It’s no exaggeration to say that your company’s GTM effectiveness-everything from account segmentation, lead sourcing and routing, and territory management-depends on how good and actionable your data is. Why you need to optimize your data enrichment strategy In this post, we’ll provide an initial RevOps roadmap for navigating the data provider space, the Do’s and Don’ts in charting your strategy, and some of the data enrichment best practices we’re seeing. However, whatever your stage in the data enrichment cycle-whether you’re a company that currently uses multiple data streams and feeds or a company that still relies on a single provider, there’s room to improve. So many teams to choose from, so many stats to assess, and so little time to do so.īut while it’s okay to do a little guessing when it comes to picking your Sweet Sixteen teams, the stakes are higher when it comes to placing bets on your data GTM stack. How does one compare claims or degrees of human-verified across vendors? How do you judge and rate compliance among the various sources?įor those college basketball fans amongst us, it’s about as daunting as trying to fill out your March Madness bracket selections. The terms used and the promises made are more nuanced than ever before. As the provider landscape has swelled, so have the complexities around picking the best data sources for your data enrichment strategy. And, thanks to advances in harvesting technology for B2B data, more companies provide signals that just several years ago only a few providers could claim. Unlike some of the vendors you’ve worked with in the past, this new crop of providers is hungrier than ever to win your business. The ecosystem of data providers has increased substantially, with many new companies entering the space. The good news is that you couldn’t have picked a better time to take this project on. You’ve decided that 2022 is the year you tackle your data enrichment strategy.