A more accurate measurement system can be intimidating because it reveals uncomfortable truths. It may show that seemingly successful activities, like generating high MQL volume, had a negligible impact on actual pipeline. Leaders must prepare to face this exposure to truly improve performance.

Metrics like "Marketing Qualified Lead" are meaningless to the customer. Instead, define key performance indicators around the value a customer receives. A good KPI answers the question: "Have we delivered enough value to convince them to keep going to the next stage?"

To get buy-in for developer experience initiatives, don't use generic metrics. First, identify leadership's primary concerns—be it market share, profit margin, or velocity. Then, frame your measurements and impact using that specific language to ensure your work resonates.

Relying on activity metrics like the number of meetings is a flawed way to gauge an MSL's effectiveness, as activity is just "noise." Real impact is measured by tangible changes in the healthcare system, such as improved diagnosis rates or better guideline adherence, requiring a shift away from activity-based KPIs.

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 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?"

Escape the trap of chasing top-line revenue. Instead, make contribution margin (revenue minus COGS, ad spend, and discounts) your primary success metric. This provides a truer picture of business health and aligns the entire organization around profitable, sustainable growth rather than vanity metrics.

Don't jump directly to optimizing for high-level business outcomes like retention. Instead, sequence your North Star metric. First, focus the team on driving foundational user engagement. Only after establishing that behavior should you shift the primary metric to a direct business impact like revenue or retention.

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.