How to Answer The #1 Question Stakeholders Ask Analysts

Learn how to effectively answer "What does this mean for us?" with actionable insights that connect data to strategy, build stakeholder trust, and elevate your role as an analyst.

By Atticus Li, Head of Conversion Rate Optimization & UX at NRG Energy

The Question That Makes or Breaks Analytics Careers

You've spent days analyzing the data. Your charts are perfect. Your statistical methodology is sound. You present your findings confidently to stakeholders, only to be met with the question that leaves many analysts frozen:

"Okay, but what does this actually mean for our business?"

This seemingly simple question is the most common challenge analysts face in stakeholder meetings. How you answer determines whether your analysis gathers digital dust or drives meaningful business decisions.

After a decade presenting analytics to C-suite executives, marketing directors, and product managers, I've learned that bridging the gap between raw data and business impact is the single most valuable skill an analyst can develop.

Why Most Analysts Fail to Answer Effectively

According to a study by Forrester, 74% of firms say they want to be "data-driven," but only 29% are successful at connecting analytics to action.

The root cause? Most analysts remain trapped in what I call the "Data Reporter" mindset rather than evolving into "Business Advisors."

The Data Reporter:

• Presents raw metrics without context
• Leaves interpretation to stakeholders
• Focuses on "what happened" but not "why it matters"
• Responds to requests but doesn't anticipate needs

The Business Advisor:

• Translates metrics into business implications
• Provides clear recommendations
• Connects findings to strategic objectives
• Anticipates stakeholder questions

The Business Impact Formula: A Framework for Answering "The Question"

Over years of trial and error, I've developed a simple framework that transforms how analysts respond to the "what does this mean" question:

1. Impact Statement

Start with a clear, jargon-free statement of the business impact.

Weak Response: "Our conversion rate increased from 2.3% to 2.8% this month."

Strong Response: "The checkout optimization project increased revenue by approximately $450,000 this quarter by improving conversion rates, putting us 15% ahead of our Q2 target."

2. Strategic Context

Connect your finding to broader business goals or industry trends.

Weak Response: "Mobile traffic increased by 23% year-over-year."

Strong Response: "The 23% growth in mobile traffic represents an opportunity to accelerate our mobile-first strategy, especially as our competitors are averaging only 14% mobile growth according to industry benchmarks."

3. Action Implication

Outline what should happen next based on the data.

Weak Response: "User engagement metrics showed mixed results."

Strong Response: "The data suggests we should double down on our email personalization efforts (which saw a 34% engagement lift) while reconsidering our social media strategy (which saw declining engagement despite increased spending)."

4. Calculation Transparency

Briefly explain your methodology to build trust.

Weak Response: "The ROI calculation shows a 340% return."

Strong Response: "We calculated the 340% ROI by comparing the $50,000 project investment against the $170,000 incremental revenue generated over 90 days, factoring in a 30% profit margin."

Real-World Example: From Data Dump to Strategic Asset

During my time at a major e-commerce brand, our team uncovered that our mobile checkout abandonment rate was 15% higher than desktop. Here's how I presented this finding to executives:

As a Data Reporter:

"Mobile checkout abandonment is 15% higher than desktop, with a 72% abandonment rate compared to 57%. The highest drop-off occurs on the payment information page."

As a Business Advisor:

"We're leaving approximately $2.4 million in quarterly revenue on the table due to our mobile checkout experience. Our mobile abandonment rate of 72% is significantly above industry benchmark of 63%, with 40% of abandoning customers explicitly mentioning payment friction in exit surveys.

A focused 6-week sprint to streamline mobile payments would likely recover $600K-$900K per quarter based on competitive benchmarks and our previous optimization results. This aligns directly with our annual goal of improving mobile conversion by 20%.

We calculated the revenue opportunity by multiplying our average order value ($85) by the number of additional orders we'd capture if we reduced mobile abandonment to just industry average levels (28,235 potential orders)."

The difference? The second approach:

• Quantified the business impact in dollars
• Provided competitive context
• Offered a specific action plan
• Tied directly to strategic goals
• Explained the calculation methodology
• Required no additional work from stakeholders

The Five Levels of Analytical Maturity

In my experience training dozens of analysts, I've identified five levels of stakeholder communication maturity:

Level 1: The Data Courier

Simply delivers requested metrics without additional context.

Level 2: The Trend Spotter

Identifies patterns and anomalies, but doesn't connect them to business outcomes.

Level 3: The Impact Translator

Converts metrics into business terms and quantifies value.

Level 4: The Strategic Connector

Links findings to company objectives and competitive landscape.

Level 5: The Proactive Advisor

Anticipates questions, provides clear recommendations, and builds decision frameworks.

Most analysts operate at Levels 1-2. The most valuable (and highest-paid) analysts operate at Levels 4-5.

How to Level Up: Practical Techniques

1. Pre-Meeting Preparation

Before presenting findings, ask yourself:

• If I were the decision-maker, what would I need to know?
• How does this connect to our quarterly objectives?
• What actions could reasonably result from this data?
• What financial impact could those actions have?

2. The "So What" Test

For every slide or data point, ask yourself: "So what?" three times to drill down to the business implication.

Example:

• Bounce rate increased 12% month-over-month. So what?
• We're losing more potential customers before they engage with our content. So what?
• We're potentially missing out on $X in revenue and our cost of acquisition is effectively increasing by Y%. Now we're talking!

3. Calculation Templates

Develop standardized calculations for common business impacts:

• Revenue impact = Change in conversion rate × Traffic × Average order value
• Cost efficiency = (Old CPA − New CPA) × Number of acquisitions
• Time savings = Hours saved × Fully loaded hourly cost

4. Stakeholder Mapping

Create a cheat sheet for each key stakeholder with:

• Their primary business objectives
• Metrics they care about most
• Types of decisions they typically make
• Their preferred communication style

At NRG Energy, I maintain a simple stakeholder matrix that helps our analytics team customize presentations to each executive's needs. Our CMO wants big-picture strategic implications, while our Digital Director needs tactical next steps.

Common Pitfalls to Avoid

1. The Technical Rabbit Hole

Diving into statistical methodology or data processing details unless specifically asked.

2. The Metric Avalanche

Overwhelming stakeholders with every possible metric rather than focusing on key drivers.

3. The Recommendation Avoidance

Hiding behind "the data speaks for itself" rather than providing clear guidance.

4. The Jargon Barrier

Using technical terms without translation (e.g., "statistical significance" vs. "we're 95% confident this result isn't due to chance").

5. The Context Vacuum

Presenting findings without historical trends, competitive benchmarks, or business goals as reference points.

Advanced Strategy: The Business Impact Workshop

Want to truly elevate your team's ability to answer the "what does this mean" question? Try implementing a Business Impact Workshop.

At NRG Energy, I run quarterly workshops where analysts pair with business stakeholders to translate recent findings into action plans. The process follows four steps:

1. Metric Translation: Convert technical metrics into business language
2. Impact Quantification: Attach dollar values to key findings
3. Strategic Alignment: Map findings to quarterly objectives
4. Action Planning: Develop specific next steps with owners and timelines

This simple practice has transformed our analytics team from data providers to strategic advisors and significantly increased the implementation rate of our recommendations.

According to research from Gartner, organizations that successfully bridge analytical findings with business actions see 83% higher performance than peers who struggle with this translation.

Your Action Plan: Next Steps

If you're an analyst looking to elevate your impact:

1. Audit Your Last Presentation: Review your most recent analytics report and apply the Business Impact Formula to each key finding.
2. Schedule Stakeholder Interviews: Meet with 2-3 key stakeholders and ask what business questions they're trying to answer with data.
3. Build Your Impact Toolkit: Create templates for calculating common business impacts in your organization.
4. Practice the Translation: For your next analysis, write both the technical finding and the business impact statement side by side.
5. Seek Feedback: After your next presentation, explicitly ask stakeholders if you effectively answered "what this means for the business."

Remember that becoming a strategic analyst doesn't happen overnight. It's a muscle that strengthens with deliberate practice and feedback.

Conclusion: From Analyst to Advisor

Answering "what does this mean for our business?" effectively transforms your role from a technical resource to an indispensable strategic partner. It removes work from your stakeholders' plates, builds trust in your expertise, and ensures your analyses drive real business decisions.

When you consistently connect data to impact, you'll find yourself invited earlier into strategic conversations and given more autonomy to pursue high-value analyses. More importantly, you'll see your work actually implemented rather than merely acknowledged.

What's the most challenging part of translating analytics into business impact in your organization? Share your experiences in the comments below, or reach out directly to discuss how to overcome specific challenges.

About the Author:

Atticus Li has 10+ years of experience in digital marketing, experimentation, and marketing analytics. For resources on marketing analytics careers, visit experimentationcareer.com or connect on LinkedIn.

Content Creation Process:

I use AI tools like ChatGPT and Claude to help generate content ideas, improve structure, and refine grammar. My process involves identifying knowledge gaps from questions I receive from new analysts or challenges I encounter in my work. I research and draft the core material, then collaborate with AI to organize and polish the content. I personally review and edit everything to ensure accuracy before publishing.

Disclaimer:

This article is provided for educational purposes only. The information contained herein should not be construed as professional advice. Always consult with qualified professionals regarding specific analytics implementation. The author and publisher assume no liability for actions taken based on this content.