High close rates, larger deals, and faster velocity are influenced by psychological states rather than just product-market fit or pricing strategies. ACT modeling offers insights into time-lagged causal effects that drive deal velocity, conversion, and expansion. Awareness and trust impact future results, with significant effects on renewals and churn. Causal go-to-market strategies focus on increasing ACT and understanding the timeline of revenue translation. In an era dominated by AI interaction, confidence and trust are vital for visibility in buyer evaluations.
Awareness today may drive results six months from now. Trust lost in Q1 may kill renewals in Q4. Confidence built slowly over the years becomes a firewall against churn.
ACT doesn't just tell you what matters - it tells you when. The evidence was ACT modeling helps you understand the weight of these factors and their time-lagged effects - giving you predictive visibility and operational leverage.
Once you begin thinking this way, you stop managing activity and start managing impact. Traditional pipeline logic operates on correlation, while causal GTM reframes the question of what increased ACT and how long before that translated to revenue.
AI is now your front door. Whether it’s OpenAI, Perplexity or Copilot, buyers are turning to AI agents to surface, compare and evaluate vendors.
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