Go-to-market (GTM) operations have traditionally been seen as operating expenses. However, advancements in causal AI reveal quantifiable, time-lagged impacts of GTM investments, indicating a shift in accounting methods. Investments driving long-term benefits can now qualify for capital treatment under GAAP standards. This new perspective allows companies to treat effective GTM activities as depreciable assets. Techniques like time-series modeling and DAGs help isolate effective actions, thus enhancing accountability and reporting for GTM expenditures over time.
Causal AI enables us to quantify the time-lagged, material impact of GTM investments on future business outcomes, signaling a shift in how GTM is accounted for.
An investment that moves pricing power for four years isn't an expense - it's an asset, allowing for a new perspective on GTM expenditures.
Causal AI, when used with time-series modeling, helps isolate which GTM actions influence financial outcomes over time, providing a reliable basis for capital treatment.
For decades, marketing and sales investments failed to demonstrate long-term value due to the inability to prove their impact, but current methodologies enable this.
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