Beyond improving traditional marketing metrics, a crucial new shared KPI for the CMO-CIO partnership is "Time to Value." This measures the efficiency of AI pilot selection, execution, and scaling, ensuring the collaboration delivers on AI's promise of speed without getting bogged down by process or governance hurdles.
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To quantify the real-world impact of its AI tools, Block tracks a simple but powerful metric: "manual hours saved." This KPI combines qualitative and quantitative signals to provide a clear measure of ROI, with a target to save 25% of manual hours across the company.
While time savings from AI are a basic benefit ("table stakes"), the true business impact of an agentic GTM platform is measured by core revenue metrics. Leaders should track pipeline velocity, conversion rates, average contract value (ACV), and win rates to prove ROI, not just efficiency gains.
Marketers over-index on vanity metrics while underappreciating the strategic value of time. The ability to launch campaigns at the "speed of culture" provides a significant competitive arbitrage. Teams should measure and actively work to reduce the time it takes to go from idea to a live campaign.
An "optimization-execution gap" reveals that while 96% of CMOs prioritize AI, only 65% make meaningful investments. This lack of commitment leaves teams stuck in an experimentation phase, preventing the deep workflow integration needed for significant productivity gains.
Leaders can no longer delegate technical understanding. They must grasp how AI fundamentally changes processes—not just automates old ones—to accurately forecast multiplier effects (e.g., 1.2x vs. 10x) and set credible team objectives that move beyond simple 'lift and shift' improvements.
Go beyond simple ROI to measure pilot success. Focus on: 1) Time to Value: delivering measurable outcomes within weeks. 2) Expansion Velocity: enabling the customer to achieve new business growth. 3) Engagement Depth: the customer actively pulling your product into new functions and creating a wishlist of use cases.
While AI tools dramatically increase content production speed, true ROI is not measured in output. Leaders should track incremental engagement, conversion lift, and revenue per message. An often overlooked KPI is brand consistency—how often content passes governance checks on the first try.
The primary catalyst forcing marketing and IT leaders into a strategic alliance is the sheer velocity of AI adoption and accessibility. The old tactical, service-desk model is too slow to manage the risks and opportunities, necessitating a shared, proactive strategy.
Open and click rates are ineffective for measuring AI-driven, two-way conversations. Instead, leaders should adopt new KPIs: outcome metrics (e.g., meetings booked), conversational quality (tracking an agent's 'I don't know' rate to measure trust), and, ultimately, customer lifetime value.
The initial conversation between a CMO and CIO about AI should not be about specific tools or governance. Instead, it must focus on establishing a shared vocabulary and a common understanding of AI's value proposition specifically within the context of marketing and revenue operations.