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February 22, 2022
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Let Predictive Analytics Run Your Go-To-Market Strategy to Success
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The need to meet customer expectations, optimize processes, and increase security are all contributing factors to the global projection from MarketsandMarketsTM that the predictive analytics market size will grow from USD 10.5 billion in 2021 to USD 28.1 billion by 2026. This is a clear indicator of the value of predictive analytics as a means of predicting the impact of future events, proving it’s a smart investment for businesses.
What’s more, digital transformation is accelerating faster than ever. A recent survey by McKinsey & Company found that COVID-19 alone has sped up the technology transformation by six to 10 years on a global scale, and it has also accelerated the digitization of customer interactions by several years.
Once you understand how to harness the combination of data with predictive models, you’re primed for a Smarter GTMTM. And we have an eBook (and a playbook) for that.
Without predictive models, target accounts are primarily defined and selected by sales and marketing teams. In general, this list of target accounts won’t be wildly off-base, after all, reps know their markets. But this method is limiting.
Predictive analytics has the power to provide insights into a myriad of go-to-market challenges, especially within the B2B realm. Whether in customer operations, demand gen, sales enablement, etc., predictive models enable users to anticipate, plan, and select better accounts.
Over the past few years, the importance of predictive models within the context of smart B2B GTM has evolved. In a recent survey, Forrester Consulting found that the top tactic B2B practitioners planned to utilize to execute their customer engagement goals was the increased leverage of their data and analytics tools.
“As we expand the role of marketing technology throughout the customer journey, predictive analytics becomes even more important. When companies pivot from account-based marketing (ABM) to account-based experience (ABX), predictive analytics goes with the territory,” affirms Chris Penn, co-founder of Trust Insights and PodCamp. Chris provided further insights by asserting that “instead of simply doing lead scoring, we use the same scoring algorithms and models to predict customer churn, upsell opportunities, or candidate customers for customer advocacy and evangelism.”
The F.I.R.E. acronym — Fit, Intent, Relationship, Fit Engagement — is the perfect visualization of how predictive analytics plays into the go-to-market strategy.
F.I.R.E. helps companies focus on the right accounts at the right time:
There is a lot of information on this framework starting on page 81 of The Clear & Complete Guide to Smarter GTMTM that shows how by combining each of these tasty ingredients together into a predictive model, you get a killer recipe for finding the best accounts that are in-market and ready to engage with you.
Businesses that can pivot their operations on a dime –– especially in unprecedented times –– and have tools like predictive analytics at their disposal will be the ones who thrive in the uncertain new normal. Our Predictive Analytics For Smarter Go-To-MarketTM eBook will show you how.
Once you see the impact a properly set-up and well-trained predictive model can have on your GTM, you will wonder how you ever went to market without one.
Content Marketer, Demandbase
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