MQLs should function as internal signals for the marketing team to orchestrate the next step in the buyer's journey, such as triggering a new automation. They are a delivery system within marketing, not a basket of leads to be handed to sales, which prevents sales from chasing low-quality signals.
Instead of abandoning the MQL framework and overhauling systems, marketers should redefine what constitutes an MQL. Focus on high-intent signals (like free trial starts) rather than low-value actions (like email opens). The MQL is a delivery system, and your definition controls its quality.
Marketers mistakenly view conversation intelligence platforms like Gong as sales-only tools. They should be using them to extract customer language for keyword research, identify conversion signals for ad platforms, and find emerging customer needs to create timely offers. It's a direct line to the voice of the customer.
Marketers need complex, multi-point dashboards to make informed decisions. However, presenting this raw data to the C-suite causes confusion. The marketing team's job is to diagnose the complex data internally and then present a simplified, narrative-driven report to leadership that justifies strategy and investment.
Go beyond standard W-shaped or last-touch attribution models. Create "influence reports" that measure the sheer frequency a channel appears in any revenue-generating journey. This provides a different lens, showing which channels are consistently present and influential, even if they don't get direct attribution credit.
The question modern attribution should answer is not "Which channel gets credit for this dollar?" but "What are the commonalities across our most successful buying journeys, and how can we replicate them?" This moves from a simplistic, linear view to a more holistic, pattern-based understanding of customer acquisition.
Don't abandon attribution; evolve it. The old model of single-touch software attribution is outdated. A modern approach triangulates data from software (GA4), self-reported forms ("How did you hear about us?"), and conversational intelligence tools, using AI to identify common buying journey patterns.
High-intent leads often come via phone calls. Every missed call increases your effective Customer Acquisition Cost (CAC) and wastes marketing spend. AI voice assistants or SDRs can provide 24/7 coverage, ensuring these valuable leads are captured, which directly improves marketing ROI and brand consistency.