A key warning sign that your KPIs are failing is when leadership meetings devolve into questioning the data's source and meaning. Productive meetings, built on trusted data, bypass this debate and focus immediately on action and strategy: "What are we going to do?"
Don't wage a direct war on familiar but flawed metrics. The politically savvy approach is to introduce new, more insightful KPIs alongside them. As the new metrics prove their superior value in driving decisions, the legacy ones will naturally become obsolete and be outgrown.
Even with visible engagement metrics, founders often feel isolated because much positive feedback happens privately in "dark social" (e.g., internal shares). This silent resonance, which metrics can't capture, leads to self-doubt about their impact.
Parting ways with clients who don't share your vision feels like a failure but is a strategic move. It frees up resources and mental energy to attract and serve ideal clients who already understand your value, eliminating the need for constant convincing.
While constant questioning signals distrust in your metrics, complete silence from leadership is an equally dangerous red flag. It indicates a lack of shared understanding or engagement. Your peers don't understand the data well enough to even ask clarifying questions, rendering it useless.
Executives are indifferent to the philosophical nuances of new measurement models. To convince them to abandon legacy metrics like MQLs, frame the change around what they care about: cost of growth, CAC payback, EBITDA, and overall business risk, not just better marketing data.
A CMO or VP can't single-handedly overhaul a company's data infrastructure. Successful change agents find a partner, typically in RevOps, who has the technical ownership to navigate the CRM and data systems. Approaching this person with curiosity, not directives, is key to gaining their buy-in.
Attribution models, even multi-touch, are fundamentally designed to answer "Who gets credit?" and often become weaponized internally. Causality analysis asks a more strategic question: "What sequence of events causes a deal to progress faster?" It focuses on optimizing the process, not distributing credit for the outcome.
Sales leadership has established weekly, monthly, and quarterly cadences for pipeline reviews and forecasting. Marketing often lacks this structured, repeatable process for tracking its own leading and lagging indicators. Adopting a similar operational rhythm would significantly boost marketing's credibility with the C-suite and board.
The trust gap between sales and marketing data is systemic, not personal. CRMs are designed to track the closed-won deal, an event tied directly to a salesperson's compensation. Marketing's influence is more diffuse and lacks a single, compensable event to anchor its data, making it inherently seem less concrete.
When legacy first/last-touch metrics reappear, don't debate them. Instead, present a broader analysis of the entire journey. This reveals how a "successful" last touch (e.g., a product trial) might belong to a cohort with a tiny win rate, high acquisition cost, and small deal size, proving its inefficiency.