Data Doesn’t Drive Decisions — Trust in Data Does
How to Get Stakeholders to Believe in the Data
Analyzing 5 million customer journeys per campaign gave me a unique vantage point into stakeholder behavior.
Our mission? Help business leaders decode behavior across email, app, web, and call center touchpoints and turn insights into sharper targeting, better timing, and stronger customer experiences.
But the real challenge wasn’t scale.
It was building trust in the data behind the decisions.
Here are 5 things I did to improve stakeholder trust in data:
🔹 Align on Definitions First
"What does this metric really mean to you?"
It’s a simple question with big implications. “Conversions” might mean clicks to marketing, but closed revenue to finance. Aligning on definitions early saved weeks of confusion and gave everyone a shared understanding of what we were building.
🔹 Rough Drafts Build Real Trust
Rough mockups in Excel or Snowflake sparked more productive conversations than polished dashboards. Early feedback helped stakeholders feel involved so when the final product landed, there was no need to “sell” it. They were already bought in.
🔹 Weekly Syncs > Big Reveals
Instead of saving everything for a big “ta-da” moment, I kept stakeholders in the loop with short check-ins even a quick Slack update. It reduced surprises, reinforced shared goals, and kept momentum high during multi-week builds.
🔹 Data Quality Is Invisible — Until It’s Not
You don’t notice broken joins or null inflation until dashboards start misbehaving. In true analyst fashion, we built dashboards to monitor dashboards catching issues before they eroded trust. It’s far better to flag problems proactively than respond to escalation emails.
🔹 More Refreshes ≠ More Trust
Real-time data sounds exciting, but daily refreshes met 90% of our analytical needs and were far easier to maintain. If your source system updates once at 8 a.m., your dashboard should reflect that reality. Extra refreshes can create a false sense of accuracy and mislead decision-makers into thinking the data is fresher or more precise than it actually is. When expectations and reality drift apart, trust in the numbers erodes
Whether you're in marketing, product, or data - trust in your numbers is what makes them actionable.