Measuring What Matters vs. What's Measurable: A Love Story

August 1, 2025Thoughts

Measuring What Matters vs. What's Measurable: A Love Story

Finding the balance between data-driven decisions and trusting human intuition about community needs

Once upon a time, there was a marketing team that fell in love with analytics. It was a beautiful romance at first—spreadsheets full of data, dashboards that updated in real-time, metrics that made everything feel scientific and professional and definitely more sophisticated than their competitors who were still making decisions based on "gut feeling."

They could tell you exactly how many people opened their emails (down to the second decimal place), precisely which social media posts got the most engagement, and the exact conversion rate of their landing pages segmented by traffic source, device type, and time of day.

The problem? Despite having more data than ever before, they couldn't tell you whether their marketing was actually helping people, building genuine relationships, or creating the kind of community impact they'd started the organization to achieve.

Welcome to the modern marketing romance gone wrong: the love affair with measurable metrics that accidentally obscures the meaningful outcomes we're actually trying to create.

The Seduction of the Quantifiable

There's something intoxicating about numbers. They feel objective, professional, and reassuring. When someone asks "how's your marketing going?" you can point to charts and graphs instead of fumbling around with subjective impressions or anecdotal evidence.

The metrics that seduce us:

Email open rates (Are people paying attention?)
Website traffic (Are we getting noticed?)
Social media engagement (Do people like us?)
Conversion rates (Are we persuasive?)
Cost per acquisition (Are we efficient?)
Return on ad spend (Are we profitable?)

These metrics answer important questions, but they're not necessarily the questions that determine whether your organization is successful at its actual mission.

The blind spot: We optimize for what we can measure, which slowly shifts our focus away from what we're trying to achieve and toward what's easy to quantify.

The Love Story Gone Wrong

Here's how the romance with metrics typically unfolds:

The Honeymoon Phase: "Look at all this data! We can optimize everything! We're so much more professional than organizations that just guess!"

The Obsession Phase: "Let's track everything! If we can measure it, we should measure it! More data means better decisions!"

The Optimization Phase: "Our open rates are up 3%! Our click-through rates improved! Our conversion funnel is working!"

The Realization Phase: "Wait... are we actually achieving our goals, or are we just getting better at hitting metrics that don't necessarily correlate with our mission?"

The Crisis Phase: "We have amazing analytics, but I'm not sure our marketing is actually helping anyone or building the relationships we care about."

The Measurable vs. Meaningful Gap

What's easily measurable:

How many people clicked your link
How long they stayed on your website
How many forms they filled out
How much you spent to acquire them
How quickly they moved through your sales funnel

What actually matters (but is harder to measure):

Whether people trust your organization
If your messaging resonates with their real needs
Whether you're attracting the right people for the right reasons
How your work impacts their lives or businesses
The quality of relationships you're building over time

The challenge: The measurable things are concrete and immediate. The meaningful things are abstract and long-term.

The Vanity Metrics Trap

Some metrics feel impressive but don't actually indicate success at your real objectives.

Vanity metrics that seduce:

Social media followers: Looks impressive, but followers who don't engage or convert aren't helping your mission.

Website traffic: Great for ego, but traffic that bounces immediately or comes from irrelevant sources doesn't advance your goals.

Email list size: A big list feels successful, but subscribers who never read or act on your emails aren't building relationships with you.

Content views: High view counts look good, but views without engagement or action don't necessarily mean your content is effective.

Brand awareness surveys: People recognizing your name sounds good, but if they can't articulate what you do or why it matters, awareness isn't translating to value.

The vanity trap: These metrics can grow while your actual impact decreases, creating the illusion of success while you drift away from meaningful outcomes.

The Community Building Measurement Challenge

Community building—the kind we focus on at Kern & Turn—is especially vulnerable to the measurable vs. meaningful gap.

What community-building metrics typically measure:

Event attendance numbers
Social media engagement rates
Email newsletter open rates
Website traffic and time on page
Survey responses and satisfaction scores

What community building actually creates:

Trust between community members
Mutual support and collaboration
Shared learning and skill development
Connection that leads to meaningful opportunities
Sense of belonging and shared purpose

The measurement challenge: The most important community outcomes—trust, belonging, mutual support—are inherently qualitative and relational, not quantitative and transactional.

The Data-Driven Decision Delusion

"We make data-driven decisions" has become a badge of honor in modern marketing. But data doesn't make decisions—people do. And the data we have access to is always incomplete.

What data can tell you:

What happened (past behavior and results)
What's happening now (current metrics and trends)
Correlations between different variables
Performance relative to previous periods or benchmarks

What data can't tell you:

Why people behaved the way they did
What they were thinking or feeling
What would have happened if you'd done something different
Whether your approach is building long-term value
How your work fits into the larger context of people's lives

The decision-making reality: Good decisions require both quantitative data and qualitative insights, both analytical thinking and intuitive understanding.

The Human Intuition Renaissance

While we've been falling in love with analytics, we've accidentally devalued human intuition and qualitative understanding. But the most successful organizations combine both.

What human intuition provides:

Context for understanding what the numbers mean
Insight into motivations and emotions behind behaviors
Recognition of patterns that don't show up in data
Understanding of quality differences that metrics miss
Wisdom about long-term implications of short-term trends

Examples of valuable intuition:

"This email had great open rates, but the responses feel less enthusiastic than usual"
"Our website traffic is up, but the people calling seem less qualified"
"The survey scores look good, but people's energy at events feels different"
"We're hitting all our metrics, but I'm not sure we're solving the right problems"

The integration opportunity: Use data to inform intuition and intuition to interpret data.

The Qualitative Measurement Toolkit

Just because something is harder to measure doesn't mean it's impossible to measure. It just requires different tools and approaches.

Qualitative measurement methods:

Story collection: Regularly gather detailed stories about how your work impacts people's lives or businesses.

Relationship mapping: Track the depth and quality of relationships, not just the quantity of connections.

Sentiment analysis: Pay attention to the tone and emotion in communications, feedback, and interactions.

Long-term follow-up: Check in with people months or years after initial contact to understand lasting impact.

Observational data: Notice what people do, not just what they say in surveys.

Conversation quality: Evaluate the depth and value of discussions you're generating.

Referral patterns: Track not just quantity of referrals, but the quality of relationships that generate them.

The Leading vs. Lagging Indicator Balance

Lagging indicators tell you what happened after it's too late to change it. Leading indicators give you signals about what's likely to happen so you can influence it.

Marketing lagging indicators:

Revenue generated from campaigns
Conversion rates for completed projects
Customer satisfaction scores after service delivery
Retention rates after the first year

Marketing leading indicators:

Quality of conversations with prospects
Depth of engagement with content
Referral rates from existing relationships
Repeat interaction patterns with your organization

The insight: Leading indicators are often more qualitative and harder to measure, but they're more useful for making real-time improvements.

The Context vs. Numbers Tension

Numbers without context can be misleading. Context without numbers can be purely subjective. The magic happens when you combine both.

Example: Email open rates

Numbers only: "Open rates increased 15% this month." Context only: "People seem more engaged with our emails lately." Numbers + Context: "Open rates increased 15% this month, and we're getting more thoughtful replies and questions, suggesting people are not just opening but actually reading and connecting with the content."

The combination principle: Use numbers to identify trends and patterns, use context to understand what they mean and what to do about them.

The Long-Term vs. Short-Term Measurement Challenge

Most analytics focus on short-term, immediate results. But the most important outcomes—especially in community building—often take months or years to develop.

Short-term metrics: Email opens, website visits, social media likes, form submissions Long-term outcomes: Trust, reputation, sustained relationships, community growth, referral networks

The patience principle: Build measurement systems that track both immediate activity and long-term relationship development.

Long-term measurement strategies:

Annual surveys that track relationship depth over time
Longitudinal studies of client or community member outcomes
Regular check-ins with key relationships to assess quality and value
Tracking career or business development of people you've worked with
Measuring community health indicators beyond just size

The Proxy Metric Problem

Sometimes we measure things that correlate with what we care about rather than measuring what we actually care about.

Common proxy mistakes:

Measuring: Time spent on website Assuming it means: People are engaged with our content Reality: They might be confused and trying to figure out what you do

Measuring: Email list growth Assuming it means: Growing audience for our message Reality: Many subscribers never read emails or take action

Measuring: Social media engagement Assuming it means: Building meaningful relationships Reality: Engagement might be superficial and not lead to deeper connection

The direct measurement challenge: Whenever possible, measure the actual outcome you care about rather than assuming proxies are accurate.

The Reporting vs. Insight Distinction

Many organizations confuse reporting data with generating insights from data.

Reporting: "Website traffic was up 20% this month" Insight: "Website traffic was up 20% this month, primarily from organic search, suggesting our content strategy is helping people find solutions to problems they're actively searching for"

Reporting: "Email open rates decreased by 5%" Insight: "Email open rates decreased by 5%, but click-through rates stayed the same, suggesting we're reaching fewer people but maintaining engagement with those who do open"

The analysis gap: Raw data needs human interpretation to become useful for decision-making.

The Community-Centered Measurement Framework

For organizations focused on community building, create measurement systems that reflect community values.

Traditional marketing metrics: Focus on acquisition, conversion, and revenue Community-centered metrics: Focus on connection, mutual value, and sustainable relationships

Examples of community-centered measurement:

Connection quality: How often do community members connect with each other, not just with you? Mutual support: Are people helping each other solve problems and achieve goals? Skill development: Are community members learning and growing through participation? Opportunity creation: Are people finding jobs, partnerships, or other opportunities through the community? Belonging indicators: Do people feel like they're part of something meaningful?

The Measurement Maturity Model

Level 1: Activity measurement

Track what you're doing (emails sent, posts published, events held)
Focus on output rather than outcome

Level 2: Engagement measurement

Track how people respond (opens, clicks, attendance, responses)
Focus on immediate reactions to your activities

Level 3: Relationship measurement

Track the quality and depth of connections over time
Focus on sustained interaction and mutual value

Level 4: Impact measurement

Track how your work influences people's outcomes and experiences
Focus on meaningful change in people's lives or businesses

Level 5: Community measurement

Track the health and sustainability of the community ecosystem
Focus on collective flourishing and mutual support

The Balanced Scorecard Approach

Create measurement systems that balance quantitative and qualitative indicators.

Quantitative measures (what's happening):

Participation rates and frequency
Growth patterns and trends
Resource allocation and efficiency
Comparative performance over time

Qualitative measures (why it's happening and what it means):

Satisfaction and sentiment feedback
Story collection and case studies
Relationship quality assessment
Mission alignment evaluation

The integration goal: Use quantitative data to identify what's working and qualitative insights to understand why and how to improve.

Your Measurement Audit and Redesign

Current state assessment:

What do you currently measure in your marketing and community building?
How much time do you spend analyzing metrics vs. understanding their meaning?
Which metrics drive your decision-making, and do they align with your actual goals?
What important outcomes are you not measuring because they're difficult to quantify?

Values alignment check:

What does success actually look like for your organization's mission?
Which metrics reflect progress toward that success?
What qualitative indicators would show you're building the relationships you want?
How can you balance immediate feedback with long-term outcome tracking?

System redesign:

Choose 3-5 metrics that directly correlate with your mission success
Add qualitative measurement practices to provide context for quantitative data
Create feedback loops that help you understand the story behind the numbers
Build long-term tracking systems for relationship and community health

The Love Story Resolution

The best measurement approaches don't choose between data and intuition—they create a loving relationship between both.

Data provides the facts: What's happening, when, and how much Intuition provides the meaning: Why it's happening, what it feels like, and what it suggests about future possibilities Together they create wisdom: Understanding that leads to decisions that serve both immediate needs and long-term mission success

The mature relationship: You use data to validate and challenge your intuitions, and you use intuition to interpret and contextualize your data.

The happy ending: Measurement systems that help you understand not just whether you're hitting your targets, but whether you're aiming at the right targets in the first place.

Because at the end of the day, the goal isn't to measure everything—it's to understand what's working, why it's working, and how to create more of the outcomes that actually matter.

The numbers tell you what happened. The stories tell you what it means. And both together help you figure out what to do next.

The moral of the story: The best measurement systems are love letters to your mission, not just spreadsheets full of data.

Thanks for reading! If you enjoyed this article, check out our other blog posts for more insights.