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Data-driven culture: how to take marketing and product to the next level
From intuition to experiment: the turning point of a data-driven culture.
Behind the squads that grow above average lies a silent pattern: a data-driven culture where marketing and product share the same framework of metrics, the same questions, and the same appetite for experimentation. This culture begins with a simple agreement: no major decision without data. From there, the path unfolds through three coordinated fronts. First, clarity of objectives: OKRs that connect acquisition, retention, and revenue and define a few master KPIs, such as CAC, LTV, churn, NPS, and North Star Metric. Second, rituals that make data part of daily life: weekly performance reviews, bi-weekly product reviews, and monthly experiment reviews, always opening with a single dashboard. Third, empowerment: training ‘data champions’ in each squad, teaching funnel reading, cohorts, A/B testing, and creating a common glossary of metrics to reduce noise and semantic debate. When data becomes common language, friction between areas decreases, and prioritization becomes less political and more impact-oriented.
Rituals, tools, and indicators that support analytical maturity.
In practice, a data-driven culture takes shape through well-designed rituals. In marketing, the classic cycle involves daily operations with media and CRM dashboards, weekly growth sessions to review creatives, audiences, CAC, and ROAS, and monthly planning guided by projections and backlog testing. In product development, the basic trio is: a discovery ceremony with quantitative and qualitative analyses, a prioritization ritual using frameworks like RICE or ICE powered by data, and a post-launch session focused on adoption, North Star impact, and user feedback. Tools connect all of this: a stack that combines product analytics, CRM/marketing automation, experimentation platform, and BI for visualization creates that 360° view. Analytical maturity can be measured in levels. At the initial level, decisions are still reactive, and few reports are recurring. At the intermediate level, squads look at complete funnels, conduct A/B tests, and justify hypotheses with data. At the advanced level, the company operates with predictive models, advanced segmentation, personalization at scale, and a backlog guided by estimated incremental impact. Indicators such as the percentage of data-driven decisions, the number of experiments per quarter, response time to analytical questions, and the adoption of dashboards by area help measure this progress.
Trends: Where is data-driven culture in marketing and product headed?
A data-driven culture is ceasing to be a differentiator and becoming a minimum competitive requirement. The convergence between martech and product analytics accelerates the creation of hybrid growth teams that use data to orchestrate everything from the sales channel to in-app purchases within a single funnel. Generative AI acts as a co-pilot: automating descriptive analyses, suggesting segmentations, generating experimental hypotheses, and freeing up team time for strategic decisions. In parallel, privacy concerns and the end of third-party cookies are forcing a shift towards first-party data, clear consent, and robust governance. The most advanced companies invest in data contracts between teams, event standardization, semantic layers, and data catalogs, reducing dependence on spreadsheet heroes. The next stage combines all of this with a product mindset applied to data: measuring the value of each insight, treating models and dashboards as living assets, and continuously reviewing whether the metrics still explain the business. In these organizations, marketing and product teams stop competing for narratives and begin to share accountability for growth, guided by a data-driven culture that is less of a project and more of an operating system for the company.
References
- PM3 – What is data-driven culture and how to implement it in business?
- HubSpot Brazil – Data-driven culture: what it is, its importance, and how to implement it.
- Salesforce Brazil – Data-driven marketing: a data-driven strategy
