Alright, team. I've hit this wall a few times—you build this beautiful, complex report in Braintrust with all the right cohorts, funnels, and custom events. You're proud of it. Then you send it to the VP of Marketing or the CEO, and you get that blank stare in the next meeting. 😅
We, as analysts and growth folks, live in the weeds. We love a good p-value and a detailed trend line. But for the execs who are steering the ship, they need a completely different view. They need the "so what?" served on a silver platter. Over the last few projects, I've landed on a bit of a formula that seems to work. It's less about the raw tool skills and more about the framing.
Here's my current playbook for building exec-friendly reports in Braintrust:
**1. Start with the Single Metric That Matters (SMTM) for that audience.**
Every report should answer one key business question at the top. Is this about user activation efficiency? Feature adoption? Retention? Put the answer—the single most important number, compared to last period—in a huge font at the top. Everything else supports that.
**2. Use Visuals as Simple Signals, Not Detailed Charts.**
Braintrust has great charting, but complexity is the enemy. I've swapped out multi-line charts for big, bold summary numbers and directional arrows (📈 📉). If you must show a trend, make it a single, thick line with maybe two data points: "Then" (last quarter) and "Now." Execs process "up 15%" faster than they process a 90-day jagged line.
**3. Segment by Business Initiative, Not by Technical Cohort.**
Instead of a cohort labeled "Users who performed event X after Y seconds," label it "Power Users of Feature Z" or "Trialers who saw the core value." Frame the segments in the language the business uses. I often create these as "Saved Cohorts" first, then build the report around them.
**4. Narrative Over Numbers.**
Add a text block at the top of each report section. Use plain English: "Our activation rate improved by 10% this month, driven primarily by the new onboarding flow we launched in April. This suggests that simplifying steps 2 and 3 is working." Turn the data into a story they can retell.
**5. Bury the "How" in the Back.**
I often have a final, collapsed section at the bottom titled "Methodology & Definitions" or "Deep Dive Data." That's where I'll put the more complex charts, SQL snippets (if I used any for custom metrics), and detailed cohort definitions. It's there if they ask, but it doesn't clutter the main message.
The biggest shift for me was moving from "Here's all the data" to "Here's what you need to know and what we should do next." Braintrust is fantastic for this because you can build this layered approach all in one report.
What about you all? What tricks have you found to make your Braintrust insights stick with a non-technical audience? Any specific chart types or widget arrangements that have gotten a good reaction?
—ec
Test, measure, repeat
This is super helpful, especially the "single metric that matters" idea. I've definitely been guilty of opening a dashboard with like five key metrics fighting for attention.
One question about simplifying visuals - when you say to use them as signals, do you mean something like replacing a detailed line chart with just a big trend arrow (up/down) and the percentage change? I'm trying to figure out how far to strip back the charts in Braintrust. Like, is a clean summary number always better than even a simple bar chart?
That single metric approach makes so much sense from a compliance perspective too. We had to report on payment reconciliation and started with a giant table of discrepancies by region. Total blank stares. The metric that finally clicked was simply "funds at risk" as a dollar figure and trend. It framed everything.
But I wonder how you decide which metric to choose when different execs care about different things. The CFO wants CAC, the CMO wants leads. Do you build separate one-page reports for each, or is there a way to find the one metric that truly bridges them all?
That single metric trick works great, but you're forgetting the cost dimension. I've seen teams proudly report a huge spike in user activation or leads, while the AWS bill tripled. The execs eventually notice, trust me.
Your big number at the top needs its sidekick: "Cost per X". User activated? Show cost per activated user. Lead generated? Show cost per qualified lead. If that number isn't trending down or at least holding steady, your beautiful growth metric is just burning cash.
Find the metric that marries their goal to the infrastructure spend. Otherwise you're just handing them a victory lap that ends at the finance department's door.
Show me the bill
Oh, the "silver platter." That's a nice way of putting it. I've always called it "predigested data" because that's what they're asking for - something that requires no mental digestion on their part. The problem with your single-metric-at-the-top approach is that it often becomes a single-point-of-failure for understanding. You pick one number, make it huge, and everyone nods. But what if that number is beautiful because you're running five extra EC2 instances and a pricey managed service to juice it? The next slide should always be a simple infra cost allocation tied directly to generating that metric. If you can't point to that, you're just doing performance art with data.
Your k8s cluster is 40% idle.
Agree with the playbook. It's basically forcing you to do narrative analysis instead of data dump.
But your point about "so what" is key. I'd take it further: the single metric needs a target. "Activation rate is 15%" is meh. "Activation rate is 15%, 5 points below target" is the so-what. That framing forces the rest of the page to explain the delta.
Your post implies the execs need simplification. Sometimes they need the opposite: a single, ruthless prioritization call. That big number at the top should tell them what to stop doing, not just what's happening.
slow pipelines make me cranky
You're right about needing a target. That context is everything. A standalone number is just trivia.
But I've seen targets backfire when they're arbitrary. If your execs aren't bought into that target, the whole "five points below" narrative just leads to a debate about goal-setting, not action. The target itself has to be credible, or you're adding noise.
The "ruthless prioritization" angle is the real gem. A single metric with a clear target should answer one question: are we doubling down or changing course? If it can't do that, it's just decoration.
Review first, buy later.
Yeah, the arbitrary target thing is a real trap. Been there.
It feels like you need a "source of truth" for that target number, something more than last quarter +5%. Maybe it's a benchmark from a similar project, or a model's output given current spend. Something that gives it legs.
Otherwise, like you said, it's just a decoration that starts arguments. How do you even pick that source? Is it a tech decision or a business one?
Containers are magic, but I want to know how the magic works.
Great point about the "source of truth." It's a business decision, but tech provides the guardrails. You need a range, not just a single number.
I start with a forecast model from our last initiative that's similar. Then I run a sensitivity analysis - basically, what's the best and worst reasonable outcome given current team velocity and infra costs? That gives you a target *range*. Presenting it as "we're targeting 12-15% based on model X" frames the conversation around whether the *model's assumptions* are right, not whether the target is arbitrary. The debate becomes productive. If you're hitting 16%, you talk about efficiency. If you're at 10%, you talk about blockers.
If you can't point to the model, you're just picking a number to make someone happy or sad.
ship early, test often