Avoid the trap of trying to achieve everything with one launch. Instead, define a single primary KPI—such as press mentions, sales rep message adoption, or a specific user action—and build the entire campaign strategy around optimizing for that one goal.

Vanity metrics like total revenue can be misleading. A startup might acquire many low-priced, low-usage customers without solving a core problem. Deep, consistent user engagement statistics are a much stronger indicator of genuine, 'found' demand than top-line numbers alone.

Instead of tracking abstract metrics like CPU usage, AppDynamics created a new unit of monitoring called 'business transactions' (e.g., logins, checkouts). This aligned with the KPIs of their buyer—Ops leaders—who cared about business uptime and performance, not code-level details they didn't understand.

Instead of focusing solely on conversion rates, measure 'engagement quality'—metrics that signal user confidence, like dwell time, scroll depth, and journey progression. The philosophy is that if you successfully help users understand the content and feel confident, conversions will naturally follow as a positive side effect.

When shifting budget to upper-funnel activities, sales impact takes time. Use leading indicators like increases in branded search volume, website sessions, or social follower growth to show early positive signals and maintain buy-in from leadership while tests are still running.

While pipeline is important, the real signal of a successful AI-driven business is the depth of customer engagement. Are customers expanding beyond their initial use case? Are developers integrating your tool into core workflows? Are communities actively discussing you? These leading indicators show a stronger foundation than top-of-funnel metrics alone.

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.

Focus on what customers value (e.g., delivery speed, order accuracy) rather than internal business metrics like ARR or user growth. This approach naturally leads to a better product roadmap and a more defensible business by solving real user problems.

Product performance isn't one metric; it's the sum of all touchpoints, from support tickets to app reviews. These disparate inputs all roll up into the ultimate North Star metric: user engagement.