Episode 050: The Operating & Data Models Used in Go-to-Market are Flawed! with Chris Walker
Jan 18, 2024
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In episode 50, we had an insightful discussion with go-to-market expert Chris Walker about aligning sales and marketing to drive revenue growth. With over 15 years of advising B2B companies, Chris provides a data-driven approach to strategically improving ROI.
Chris explains that misalignment between sales and marketing teams still plagues organisations today like it did a decade ago. The cause is flawed operating and data models, not personalities.
Firstly, the traditional model functions in silos - marketing generates leads, sales pursues meetings, and these handoffs optimise metrics, not revenue. Secondly, marketing impacts the entire customer lifecycle, yet companies only scrutinise top-of-funnel investments.
To solve this, Chris has developed a unified data model combining marketing, sales, and SDR data to analyse full go-to-market performance. This provides the complete analytics executives need to optimise budget allocation and strategy.
Many companies lack the right data structure to make smart decisions, often spending lavishly without measurement. Chris stresses it’s inexpensive to implement this analytics framework relative to go-to-market budgets.
We discuss his “Hero” model - standardising the definition of qualified pipeline based on historical conversion rates by source. This reveals a bad pipeline inflated with low-quality leads.
Chris explains that different lead sources have dramatically different conversion velocities, win rates, deal sizes, and sales productivity. Blending all pipelines masks this variance and opportunities to optimise.
Timing is key - it’s ideal to implement structured data tracking with just 5 sales reps. Otherwise, problems compound and require ripping out engrained workflows later to fix. But any growth-stage company can benefit now.
Listen to the podcast now and discover how go-to-market expert Chris Walker transforms businesses by aligning sales and marketing with a powerful data-driven approach.
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