Relying solely on data leads to ineffective marketing. Lasting impact comes from integrating three pillars: behavioral science (the 'why'), creativity (the 'how' to cut through noise), and data (the 'who' to target). Neglecting any one pillar cripples the entire strategy.

To succeed, marketers must stop passively accepting the data they're given. Instead, they must proactively partner with IT and privacy teams to advocate for the specific data collection and governance required to power their growth and personalization initiatives.

It's tempting to postpone foundational work like data integration until the slower post-holiday period. However, the holiday sales surge provides the richest dataset for testing, learning, and setting up automations. Building this foundation during Q4 allows insights to compound, driving more sustainable growth throughout the following year.

Marketers should use AI-driven insights at the beginning of the creative process to inform campaign strategy, rather than solely at the end for performance analysis. This approach combines human creativity with data to create more resonant campaigns and avoid generic AI-generated content.

Don't just show creatives a summary report from the marketing team. Giving designers, copywriters, and video editors raw access to performance data allows them to spot non-obvious patterns and make intuitive leaps that analytical minds might miss, leading to better creative.

Georgia Pacific built trust for marketing investments by bringing analytics and market mix modeling (MMM) in-house. This allowed them to not only highlight wins but also to act with credibility by quickly identifying and stopping underperforming tactics, demonstrating fiscal responsibility to leadership.

Shift the mindset from a brand vs. performance dichotomy. All marketing should be measured for performance. For brand initiatives, use metrics like branded search volume per dollar spent to quantify impact and tie "fluffy" activities to tangible growth outcomes.

Brands miss opportunities by testing product, packaging, and advertising in silos. Connecting these data sources creates a powerful feedback loop. For example, a consumer insight about desirable packaging can be directly incorporated into an ad campaign, but only if the data is unified.

To maximize AI's impact, don't just find isolated use cases for content or demand gen teams. Instead, map a core process like a campaign workflow and apply AI to augment each stage, from strategy and creation to localization and measurement. AI is workflow-native, not function-native.