Scott Galloway

Penguin Random House

Author, "The Four," "Algebra of Happiness," "Post Corona," "Adrift: America in 100 Charts"

NYU Stern School of Business

Clinical Professor of Marketing

Section

Founder & Chairman

CNN+ Host

L2 is a research firm focused on helping our member brands shape their digital roadmap and achieve greater ROI on human, creative and financial capital. L2's proprietary Digital IQ Index® is the global standard for determining a brand’s digital competence analyzing more than 850 data points across four dimensions: Site & E-Commerce, Digital Marketing, Social Media, and Mobile & Tablet. 

Founded in 2010, L2 members include the world’s most iconic consumer brands and our research covers the beauty, CPG, drinks, food, luxury, retail, hospitality, and automotive sectors across eleven geographies. We produce over 60 research reports, host over 70 executive education events and deliver over 100 deep dives to our member brands annually, around the world. 

Through industry research and benchmarking, executive education and data analytics, L2 offers member brands actionable insights at a fraction of the cost of traditional consulting. 

Learn more at l2inc.com.

The New York Times

Board of Directors

Firebrand Partners

Founder

Eddie Bauer

Red Envelope

Gateway Computer

For speaking inquiries, please email speaking@profgmedia.com. Not accepting connection invitations — please follow instead. 

Scott is the Founder of L2 and a Clinical Professor at the NYU Stern School of Business where he teaches brand strategy and digital marketing. In 2012, Professor Galloway was named “One of the World’s 50 Best Business School Professors” by Poets & Quants. He is also the founder of Red Envelope and Prophet Brand Strategy. Scott was elected to the World Economic Forum’s Global Leaders of Tomorrow and has served on the boards of directors of Eddie Bauer (Nasdaq: EBHI), The New York Times Company (NYSE: NYT), Gateway Computer, and UC Berkeley’s Haas School of Business. Scott co-hosts the Pivot podcast with Kara Swisher. He received a B.A. from UCLA and an M.B.A. from UC Berkeley.

Sex sells. But social media companies discovered something that sells more.

Professor of Marketing, NYU Stern | Bestselling Author | Founder, Section | Host #ProfGPod, #PivotPodcast

From the latest China Decode. Full episode on the Prof G Pod feed or YouTube channel: https://lnkd.in/df-RWYYE

Barking Mad

Founder & CEO

Method Q

Adviser

President

Vice President of Growth

Linc 

Director, Demand Marketing

PrimeRevenue

- Create and capture demand, with the goal of driving more inbound inquiries and creating higher converting sales qualified opportunities

- Produce and execute customer-centric multichannel digital marketing programs (integrated email, SEO, website, PPC and display) at acceptable CAC for our early payment and on-time payment solutions

- Utilize our ABM platform to separate ICP from TAM and capture the intent levels of ICP accounts

- Segment ICP accounts and personas to deliver targeted content based on firmographics and known intent

- Collaborate with the content and creative teams on earned media, website content, blog posts, ads, landing pages, email, etc... to educate ICP and capture new demand

- Work with the website team on conversion rate optimization (CRO), particularly driving more inbound contact us submissions from sales ready ICP

- Further support sales by maintaining our sales engagement platform, compiling recommended follow-up content in our sales enablement/content platform, sending email outbound to MQAs, and analyzing outreach success metrics (i.e. sales velocity and pipeline stage conversion rates by source)

- Track, measure, analyze and create reports in Salesforce and Excel on success of inbound and outbound funnel optimization, demand creation and ABM plays across ICP targets, Tier 1 account targets, Pipeline and Nurture

Senior Marketing Manager

List Partners LLC

Oversee our US and UK sales prospecting publications that assist our agency, ad sales, sponsorship, martech and nonprofit clients with acquiring new clients. 

Highlights:

- 5 straight years of 25%+ YOY subscriber growth.
- 80% accuracy forecasting agency/martech roster changes within an 18-month window (enough time to get in early) using my agency new business predictive model.
- 140 leads, reports and white papers published weekly in our U.S. and U.K. publications.

Managing Editor & Lead New Business Analyst - WinmoEdge (formerly known as DailyVista)

Reinvented WinmoEdge (formerly known as DailyVista) by taking a data-based forecasting approach to finding and publishing actionable sales leads. 

I led U.S. content strategy, research, editing, data interpretation, staff training, etc... 

Highlights:

- Doubled content production without increasing staff levels. 
- Added financial reporting tactics to make sales leads more actionable. 
- Created a predictive model identifying the decision makers most open to vendor pitches.

Editor - US

Senior Staff Writer

The Glass Onion

Freelance Writer

The 11th Hour

Managing Editor

Valdosta State University

Editor-in-Chief - The Spectator

Valdosta Daily Times/Lowndes County Review

Reporter

Helping CMOs and Agencies prove impact, drive faster decisions, and end hours of manual reporting.

I’m the founder of Barking Mad, a consultancy crazy about helping fractional CMOs, in-house CMOs, and agency operations leaders stop guessing and gain visibility into the KPIs that actually matter.

Why the name Barking Mad?

● My British friend suggested it and it sounded cool.
● It gave me an excuse to put my corgi, Phil, in the logo.
● Most importantly, because I’m crazy about helping CMOs and agencies cut through the data chaos, reduce manual reporting, empower their teams, and avoid stress and burnout.

After nearly a decade in demand gen, MOps, RevOps, and agency leadership, I realized most marketing and agency leader stress stems from a lack of clarity.

Barking Mad exists to change that.

We help CMOs and agencies stop drowning in data and reporting to make smarter, faster decisions. In 30 days or less, we turn messy, manual reporting into actionable KPI dashboards built on numbers that can be trusted in every conversation.

We take the work seriously—but not ourselves.

That’s why Phil (and his border collie mix bro, Buzz) is part of the brand. They’re working dogs who remind us every day to keep overwhelm in check, enjoy the process, and stay grounded (even if we don't have tiny corgi legs).

When I’m not analyzing data and building dashboards, you’ll find me watching Red Sox baseball, playing Skip-Bo with my wife, Chrissty, playing with Phil and Buzz in the backyard, or with my nose in a book.

Look forward to working with you!

If you're not ready to chat yet or it's too early in the morning for Phil's barking, no worries!

Email or DM me any questions about goal planning (yikes, it's almost Q4 already), KPI chaos, and spreadsheet shenanigans and I’ll point you in the right direction.

Josh Stone

If “leads generated” is still your top ROI metric, your system isn’t telling you the truth.
 
Here’s the thing…
 
CMO Alliance’s Future of Marketing 2025 Report showed something wild:
 
“Leads generated” outranks 𝘳𝘦𝘷𝘦𝘯𝘶𝘦 as the #1 marketing KPI.
 
And at the same time:
 
• 40% can’t track ROI confidently
• 61% say attribution breaks
• 40%+ can’t integrate the tools they’re supposed to rely on
 
That isn’t a reporting problem.  It’s a system problem.
 
Because when your KPIs don’t reflect how buyers actually buy, you can’t steer the business.  You can only react to it.
 
Here are the five KPIs I track with marketing leaders and their teams inside Databox to forecast pipeline 𝘸𝘦𝘦𝘬𝘴 𝘦𝘢𝘳𝘭𝘪𝘦𝘳 than the CRM does:
 
1. 𝗛𝗶𝗴𝗵-𝗜𝗻𝘁𝗲𝗻𝘁 𝗖𝗮𝘁𝗲𝗴𝗼𝗿𝘆 𝗦𝗵𝗮𝗿𝗲 𝗼𝗳 𝗦𝗲𝗮𝗿𝗰𝗵: Shows whether you’re winning solution-aware buyers.
2. 𝗕𝗿𝗮𝗻𝗱𝗲𝗱 𝗦𝗲𝗮𝗿𝗰𝗵 𝗩𝗼𝗹𝘂𝗺𝗲: Validates demand creation and market education.
3. 𝗛𝗶𝗴𝗵-𝗜𝗻𝘁𝗲𝗻𝘁 𝗔𝗰𝘁𝗶𝗼𝗻𝘀: Behavior closest to “I’m ready to talk.”
4. 𝗠𝗲𝗲𝘁𝗶𝗻𝗴 𝗖𝗿𝗲𝗮𝘁𝗶𝗼𝗻 𝗥𝗮𝘁𝗲: Real test for demand conversion.
5. 𝗦𝘁𝗮𝗴𝗲-𝘁𝗼-𝗦𝘁𝗮𝗴𝗲 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗛𝗲𝗮𝗹𝘁𝗵: Reveals friction long before revenue shows it.
   
If you want pipeline predictability, these matter more than attribution ever will.

Leads show activity.  These show momentum.

Which one should we break down next?

Solving scattered KPI data for CMOs, Fractional CMOs & Agency Leaders | Dashboards showing what happened, why, and what to do now | Marketing, Sales, CS & Finance data centralized | End manually pulling metrics madness

5 Signals Marketing Leaders Should Track Instead of Leads

I never planned to build a business around data clarity.  But one moment changed everything.
 
I had strong instincts for what my bosses, teammates, and clients needed:  Context. Visibility. Early signals. Confidence in what to do next.
 
But I couldn’t deliver it consistently — not early or clearly enough to drive real change.
 
Everything felt too reactive.  I was chasing insights instead of leading with them.
 
I got trapped by the activity monster: hours stitching data, updating reports, pulling last-minute numbers. Doing everything 𝘣𝘶𝘵 the strategic work that actually moved the needle.
 
Not because I wanted it that way. I 𝘩𝘢𝘵𝘦𝘥 it.  But the system rewarded speed and volume over clarity and impact.
 
Looking back, I was always busy but rarely ahead.  And I knew I wasn’t alone.
 
As I moved from marketing ops to demand gen to operations leadership, I kept hitting the same wall.
 
I was responsible for profitability, forecasting, pacing, and performance.  But I didn’t have the visibility to steer outcomes with confidence.
 
No matter the team or the tools, the problem was the same:  Performance data lived in disconnected platforms. Definitions didn’t align. Reporting took hours.  And even when I pulled everything together, the story still wasn’t clear or forward looking enough to drive confident action.
 
It wasn’t the people. I worked with smart, driven teams.  The problem was systemic and painfully consistent.
 
I’d seen it for years across roles, teams, and clients.  Our industry is stuck in reactive mode: buried in dashboards, starving for signal.  Everyone’s working harder just to stay afloat, but real clarity — early, actionable clarity — rarely arrives.
 
That’s when I knew: I couldn’t keep solving the same problem inside the same system.
 
I had to build something different and fix the problem at its core.
 
Today, I help CMOs, fractional CMOs, and Agency Leaders consolidate all of their performance and go-to-market data — plus client data for agencies — into a single Databox source of truth.
 
It’s not just cleaner reporting. It’s a system that shows:  

✅ What’s happening  
✅ Why it’s happening  
✅ Whether you’re ahead or behind pace  
✅ What to do about it
 
No more spreadsheet-stitching.  No more heroic work just to get to square one.  No more flying blind.
 
Because leaders don’t need more dashboards.  They need clarity early enough to act without burning themselves out to get it.
 
Ever feel like you’re leading with dashboards, but missing the signals that matter? Drop a comment or DM me if this hit home.  No pitch. Just a friendly ear and some advice (if you want it) to help you get where you want to be.

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If your most valuable marketer is your “reporting person,” you’re already behind.

I keep meeting teams where the sharpest operators spend every Monday and more trapped in a spreadsheet cell literally and figuratively. I’ve been that person, stuck pulling the same data and rebuilding the same decks over and over.

→ Pulling GA4, LinkedIn Ads, Google Ads, HubSpot and on and on.
→ Cleaning columns.
→ Reconciling totals.
→ Pivot tables.
→ Screenshotting charts into slides.
→ Rinse and repeat every week, month, and quarter.

By the time they escape spreadsheet jail, half the insights are already stale.

And the worst part?

Everyone says, “Thanks for the report, nobody reads it, recommendations go unfollowed, and the team goes right back to guessing.

It’s not because people are jerks. It’s because everyone is already overloaded. If reporting doesn’t lead to better, faster decisions, it’s not useful.

I learned this the hard way.

Hours of effort can feel productive, but only outcomes matter. Feeding the activity monster feels helpful in the moment, but it starves long-term impact. Escaping it requires a system that aligns goals, definitions, and leading indicators.

When we install and operationalize a Growth OS, the goal isn’t just “fewer hours on manual reporting.” It’s making reporting the least valuable time your team spends.

→ Dashboards update themselves.
→ KPI scorecards roll straight to owners.
→ Leadership reviews the early signals instead of reading a 30-slide history book once a month.

Gaining 10 hours a week from automating manual reporting is nice. Freeing your best operator from low-value work so they can drive traction and early signals is better. Replacing backward-looking reports with real-time, confident decisions is best.

Manual reporting doesn’t just waste time. It delays the moment you can actually fix the problem.

Where does reporting steal the most energy from your team right now?

Happy Thanksgiving! Thankful for beautiful days, great stories, and amazing family and friends like Betty.

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Nothing rattles a room faster than four leaders giving four different answers to the same question.
 
We’ve all been there hiding in the saloon as they step into main street at high noon:
 
😨 CEO: “So… are we on track?”  
😨 Finance: “Yes.”  
😨 Sales: “If we close X.”  
😨 Marketing: “If these campaigns land.”
 
RevOps: dives under a wagon and opens 12 tabs in quiet panic.
 
Here’s what’s really happening underneath that moment:
 
• Nobody agrees on which KPIs define “on track”  
• Each team is staring at a different source of truth  
• The story lives in people’s heads, not in the system
 
It’s rarely a people problem.  It’s a data problem that makes alignment impossible.
 
When we install a Databox-powered Growth Operating System, the goal isn’t prettier dashboards.  It’s making sure that when someone asks, “How are we doing?” everyone gives the same answer.
 
That only happens when:
 
✅ The revenue team agrees on the handful of KPIs that define winning
✅ Each KPI has a clear owner and definition
✅ There’s one view that ties it all together (instead of six decks and 12 tabs)
 
Once that exists, exec meetings shift from proving whose numbers are right to deciding what to change next to hit lag measures and business objectives.
 
You can’t have alignment if your data tells four different stories.
 
What’s the question that still gets four different answers in your leadership meetings?

Most dashboards don’t fail because the data is wrong. They fail because nobody knows what to do with them.

I learned this the hard way. Sitting in exec meetings explaining charts instead of making recommendations and driving decisions.

You know the meeting.

➜ Someone walks through the chart.
➜ The data gets disputed.
➜ Another tab opens to check filters.
➜ Turns out three teams filter it three different ways.
➜ 45 minutes later, we’re still debating what we’re even looking at.
➜ Decisions aren’t being made.
➜ Your butter coffee gets cold and kind of gross.
➜ The meeting runs over.

And when you finally escape, the only thing left at the breakfast buffet is burnt bacon and cottage cheese.

Early in my career, I thought the fix was better dashboards and widgets. 

• More metrics.
• More views.
• More tabs.

What I didn’t realize at the time: I was optimizing for display, not movement.

The shift happened when I stopped asking: “What should we track?” and started asking: “What question does this answer and what decision should it trigger?”

One small change made an outsized difference: We renamed every chart to the exact business question it answers.

• No Little Orphan Annie decoder ring.
• No interpretation.
• No Zack Morris timeout of “wait… what am I looking at?”

If it takes more than a glance to understand the point, the system is too heavy.

Rule of Thumb: If a leader has to ask what a chart is showing, the dashboard already failed.

Dashboards create insight. Operating systems create movement.

What’s a business question your dashboards answer really well today?

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CMO Alliance's latest Future of Marketing report shows something familiar and concerning: 

“Leads generated” is still the top metric marketers use to measure ROI in 2025, placing even ahead of revenue (which was 3rd).

That isn’t a measurement issue. It’s a system issue. Because simultaneously:

• 40% can’t track ROI confidently
• 61% say attribution breaks because systems don’t talk
• 40%+ can’t integrate their tools

I see this with the teams I work with. Execution isn’t the issue — the KPIs are. They don’t reflect how buyers actually buy. And digital attribution reinforces it by measuring only a sliver of the journey, yet still shaping what teams optimize around.

Here's the 5 main ones I track with teams in Databox to forecast pipeline and what you can do to improve them:

1. Branded Search Volume
• Why?: Validates that market education and word-of-mouth efforts are working.
• You Control: Message clarity, POV consistency, publishing useful content, customer experience.
• Dec/Jan: Rewrite 1 core page using buyer language, publish one “problem clarity” insight, and pull one customer quote into your messaging.

2. High-Intent Category Share of Search
• Why it Matters: Shows if you’re capturing solution-aware buyers before they become brand aware.
• You Control: Positioning clarity, showing up in conversations buyers trust, and publishing content that helps buyers see why you're the best option.
• Dec/Jan: Create solution-evaluation content that matches how buyers search (“best tools,” “how to choose”), clarify your category language on key pages, and use paid search to show up for high-intent solution queries you don’t rank for yet.

3. High-Intent Actions (e.g. pricing page visits, demo page visits, case study depth).
•  Why?: Behaviors closest to buying intent.
•  You Control: Page clarity, visible pricing, proof you've solved their problem for others, eliminating hurdles from "I'm interested" to "I want to talk."
• Dec/Jan: Simplify one friction-heavy page, move a case study above the fold, and add a “What to expect in a demo” section.

4. Meeting Creation Rate & Time-to-First-Touch
•  Why?: Strong predictor of opportunity creation.
•  You Control: Routing, responsiveness, follow-up discipline.
• Dec/Jan: Add outcome-focused CTAs to site, document routing issues slowing down inbound ICP follow-up time, fix 2 of the delays.

5. Stage-to-Stage Conversion Health
• Why?: Reveals blockers early before pipeline and revenue show it.
• You Control: Discovery consistency, deal hygiene, qualification
• Dec/Jan: Hold a 30 min GTM friction review, ensure every opp has a next step documented in the CRM, and review 5 lost deals and bring 1 insight to the GTM sync.

These predict pipeline far better than lead counts or attribution ever will because they’re the backbone of a system built on clarity, demand signals, and consistent rhythm.

I’ll break each one down next. Which should I cover first?

You’re not drowning in data.  You’re drowning in unclear decisions.
 
Most marketing and agency teams think their dashboards are broken.  But dashboards aren’t the problem.
 
The 𝘴𝘺𝘴𝘵𝘦𝘮 underneath them is.
 
No shared definitions.
No weekly rhythm.
No agreed-upon list of the metrics that actually matter.  
Multiple “sources of truth” arguing for attention.
 
Sound familiar?
 
Here’s the pattern I keep seeing:
 
Teams aren’t missing numbers.  They’re missing agreement on what the numbers mean.
 
So when we rebuild a dashboard, we ignore the charts at first.  We start with three questions:
 
1. What decision needs to happen faster?  
2. Which KPIs tell that story?  
3. Who owns the number when it moves the wrong way?
 
Once those answers exist, everything changes. 

The dashboard finally becomes what it was supposed to be: The cockpit for a real operating system.  Not a prettier place to be confused.
 
𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 𝗱𝗼𝗻’𝘁 𝗳𝗶𝘅 𝗺𝗶𝘀𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁.  𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗿𝗵𝘆𝘁𝗵𝗺 𝗱𝗼.

A dashboard without a system?  

That’s like having a pretty fire alarm that doesn’t go off until the fire has already done the damage.

What’s the one KPI your team debates every single week?

A simple Friday test to see if your growth system is healthy:
 
If you had to walk into a board meeting in 5 minutes…  could you answer these five questions?
 
1. Are we pacing to revenue? (Lag)
2. Is pipeline creation on track this week? (Directional)
3. Are our leading indicators improving or declining? (e.g. brand search, high-intent page views/scroll depth, meetings scheduled, 
4. Where is conversion slowing? (Stage bottlenecks)
5. Do we trust the data we’re looking at? (Governance)
 
Most teams can’t answer all five and not because they’re not performing…  But because their system isn’t giving them a clear story.
 
That’s the gap a Databox-powered, single source of truth CMO Command Center closes:  one view → one narrative → confident decisions.
 
What’s the one KPI you always check before the weekend?

The number of KPIs you track matters far less than the number of KPIs you actually use. 

I get asked all the time, "How many KPIs should we track?" And I used to ask the same question, leaning towards more = better and believing: 

• If we just had more data…
• If we just had better ways to correlate everything
• If we just knew the idea amount of touches
• .... we'd finally know what's working and could forecast properly. 

But I eventually realized after way too much reporting pain: 

Collecting more signals only matters if it helps you identify the 10-20 KPIs that actually drive impact — and the combinations that create more of it, faster.
 
So now when someone asks, “How many KPIs should we track?”  I flip it to:
 
“Which KPIs actually change what we do next week?”
 
That’s the difference between a dashboard and an operating system.
 
Inside a functioning Growth OS, every KPI earns its place:

💪 Lead indicators you can influence weekly  
💪 Lag indicators that prove the impact of those leads 
💪 Guardrails that protect efficiency, margin, and keep you from feeding the activity monster 
💪 Visibility into how today’s work shapes tomorrow’s outcomes, so morale stays high and nobody ends up in the nuthouse
 
Once those KPIs are defined, documented, and agreed upon across the entire revenue team:
 
Dashboards stop being pretty charts and start answering:  What happened? Why? And what’s the next step

Alignment across Sales, Marketing, and Customer Success gets easier. Relationships get stronger. Teams finally feel like they’re winning together. Decisions get faster. And the data stops drowning everyone.
 
You don’t need more KPIs. You need the fewest KPIs that move the business forward.

If you had to cut your KPI list to 5, which ones would stay?

If you finish Friday thinking, “No idea if this week moved the needle,” that’s a system problem — not a you problem.
 
Here’s a tiny reset I’ve started using that’s been helpful:
 
Before you log off, finish these three lines:
 
1. This week, the data surprised me most when…
2. One thing I’d repeat next week is…
3. One thing I’d stop or change based on the numbers is…
 
That’s it.  

No giant slide deck. No offsite. No 3-hour post-mortem.

We're teaching our brains (and our systems) to:
 
• Notice early signals
• Reward what worked
• Retire what didn’t
 
Over time, this is what turns dashboards from boring history books into actionable feedback loops.

You don’t need a big new framework to get better. You need one small ritual you’ll actually do and act on.

Which of those three questions would help you most if you answered it 𝘦𝘷𝘦𝘳𝘺 Friday?

The Boss: Those guys are really on the ball!

The Guys (playing with a football) 

See, corporate jargon can be fun.

Kicking off Q1 with no leading indicators

If you're skipping the AMA Atlanta Holiday Party tonight because you're worried The Grinch might steal your tree while you're out, Buzz and Phil may be free to stand guard. Let me know. Excited to hang with everyone tonight! https://lnkd.in/enDss3wC?

Open article: AMA Atlanta Holiday Party: ATL in Neon Lights by eventbrite.com

AMA Atlanta Holiday Party: ATL in Neon Lights

Inconvenient truth: LLMs and AI won’t replace dashboards. They will expose their weaknesses.
 
Give a messy data stack to LLMs and AI and you don’t get magic. You get faster nonsense.
 
Asking “How’s pipeline pacing?” in Slack only works if:
 
• Your KPIs are clearly defined
• There’s one source of truth for each metric
• Your dashboards already reflect the actual business story
 
Otherwise, you’ve just given the chaos a louder megaphone.
 
The teams that win pair:
 
🏆Chat for triage and quick “what-if” questions
🏆A Growth OS dashboard layer for verification and decisions
 
LLMs and AI are accelerators.  They compound the quality of the system it sits on.
 
If your data house is messy, AI just helps you trip over furniture faster.
 
What’s one guardrail you’d need in place before trusting LLMs and AI for GTM decisions?

A simple dashboard win that almost no one does (and it changes everything): Rename every widget to the business question it’s answering.

Even insightful, actionable dashboards can still fail because they show metrics, not meaning. 

Instead of widget titles like:

• MQLs
• Conversion Rate
• Pipeline by Source
 
Try framing every widget as a question:

❓ Are we creating enough demand to hit pipeline next quarter?
❓ Where is conversion breaking down right now and why? 
❓ Which channel deserves more (or less) investment next week?
 
Good dashboards should do three things fast:
 
1. Answer what’s happening
2. Explain why it’s happening
3. Make the next step obvious
 
If someone has to ask, “What am I supposed to do with this?”, the dashboard already failed.
 
This one simple change creates a shared, memorable narrative everyone in the room can follow. This leads to:

✅ Better exec conversations 
✅ Less metric defending 
✅ Faster, better decisions

So here's the test:

Which questions does leadership keep asking?  Do your dashboards answer them already? 

If you think they do, try this:  Rename your widget titles as the actual questions being asked. Then watch what changes.
 
Pay attention to:  

• How they engage with the dashboards
• The tone of meetings where you're sharing these dashboards.
• The quality of follow-up questions in meetings, Slack, and 1-on-1s. 
• Whether your written recommendations get read and acted on. 
 
When dashboards answer real questions, conversations shift from explaining numbers to deciding what to do next.

For butter subscription services is churn considered good or bad 🤔

When the College Football Playoff committee says “trust the process”… but the process is a Google Sheet with no KPI standards and every member is following their own rulebook.

Tulane and James Madison taking up two spots in the top 12? More like Too Lame.

That’s exactly how revenue teams miss targets. 

Bad definitions + misaligned rules = chaos. Every. Single. Time.

What’s the wildest “trust the process” moment you’ve seen in reporting? 

(And no, 2022 TCU getting ranked #3 and then losing 65-7 to UGA doesn’t count 🤣)

The only thing scarier than proximity mines in GoldenEye’s multiplayer Stack is another year with an unaudited, bloated tech stack.

Monday shouldn’t feel like guesswork.

If you’re starting the week asking:

❓ “Are we behind?”
❓ “Which channel is wobbling?”
❓ “What actually matters right now?”

That’s not Monday anxiety. That’s a system gap.

Clear weeks don’t happen by accident.

They happen when signals are already waiting. 

What’s the first metric you check every Monday and why?

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