As organizations continue to navigate the evolving and increasingly tech-enabled sales landscape, commercial leaders must continually find ways to drive efficiency and growth, improve margins, and retain customers against increasing competition.
Recent Alexander Group research highlights how many organizations are investing in machine learning (ML) to elevate their sales motions and accelerate their daily processes for improved sales results, increasing their year over year (YoY) revenue growth by 4.3 percentage points compared to peers.
Our research shows that leaders who invest in 3 or more ML use cases are seeing 4.3 percentage points more YoY revenue growth compared to peers, demonstrating the value-add that machine learning offers commercial organizations.
84% of data science leaders use machine learning to optimize seller productivity, 82% to drive pipeline and 62% to boost customer lifetime value, emphasizing the cross-functional applicability of these models and investments throughout the customer journey.
Data science delivers measurable impact. From a telecom provider retaining $350M in revenue through predictive churn models to a fintech company unlocking $10M in cross-sell revenue, leaders are capturing tangible ROI through their investments.
Average YoY Revenue Growth for Data Science leaders compared to peers
of Leaders invest in ML to Drive Awareness and Engagement
of Leaders invest in ML to Optimize Seller Productivity and Focus
of Leaders invest in ML to Improve Customer Experience and CLTV
Reduce time spent on lower quality leads and boost your pipeline with higher-quality prospects using ML-backed targeting and lead scoring efforts.
Focus your reps on the best opportunities with predictive forecasting and opportunity modeling. See shorter sales cycles, bigger deals and higher quota attainment.
Scale your CX strategy to retain and expand your most valuable accounts with next best offer and churn prediction models.
See real strategies from real businesses grounded in research from 175+ executives and 45+ in-depth interviews with B2B commercial leaders.
Understand the detailed and technical processes behind six key ML model use cases across the customer journey.
Learn how top companies have operationalized data science for demonstrable ROI.
In the full report, you’ll find in-depth technical modeling use cases and detailed case studies tied back to the top priorities and initiatives that commercial organizations are driving toward today.
Complete the form to request a briefing to access the models and playbooks that are driving results for your peers.