Blog: Translating Media Performance Data Into Something the C-Suite Can Actually Use

Jordan Crawford has sat in this room before. 

The marketing team walks in with a report that looks like good news. Cost per lead is flat or improving. ROAS is climbing. Across the table, the board asks why revenue is flat (or even declining) when the plan called for 15% year-over-year growth.

Nobody’s lying. That’s what makes it so disorienting. 

“Basically, everything looks like it’s getting better, but the business is going in the opposite direction,” Jordan says. The marketing report and the business report are describing two different realities, and there’s rarely a translation layer between them. There’s no shared way to connect marketing attribution to actual marketing ROI. “It often feels like there’s the business reports, and then there’s the marketing reports, and they’re really not speaking to each other at all.”

Jordan has spent the last two years mapping exactly where that gap opens up and how to close it.

Why Marketing Goals Get Set to the Wrong Number

The first crack forms before any campaign ever launches, when goals get set.

Jordan describes a familiar pattern: a team looks at how their CPM has trended and decides that’s a good number to hold steady. Add more spend, keep the CPM where it is, growth follows.

Except that number was never connected to the business. It’s an artifact of the platform, not a measure of profit. Manage toward it, and every report will look successful by its own, built-in logic.

The fix starts by working backward from the business itself. Take a higher-ed client, though the same logic applies across industries. 

How to Set a Media Goal That’s Tied to the Business

1. Start with the real unit economics. What does it cost to deliver your product or service? What margin does the business need to sustain itself? These numbers live in the P&L, not the media platform.
2. Calculate what the business can actually afford to pay to acquire a customer. For this higher-ed client, that number was roughly $6,000 per enrolled student. This is the ceiling. Every media decision has to fit inside it.
3. Map the full funnel and timeline. How long does it take from first contact to conversion? What does the drop-off look like at each stage? You can’t set a lead goal without understanding how leads move through the funnel.
4. Translate the business goal into a media-actionable target. The $6,000 CAC ceiling becomes a per-lead value only when you know your conversion rates. In this case, that worked out to roughly $160 for a lead showing real signs of enrolling. That’s the number the media team can actually optimize toward.

This work has to happen before any platform metric means anything. Skip it, and a team optimizes toward a number that was never tied to the business in the first place.

Why Click-Based Attribution Misses the Channels That Actually Build Demand

The other half of the gap comes from how attribution works. It’s structural, not a simple matter of picking the “right” model.

“At the end of the day, all of the different attribution models are biased toward channels that require a click,” Jordan says, “because that’s the only way that attribution model would know that someone engaged with it.” 

Someone watches an entire YouTube video, absorbs the message, acts on it days later. “No one’s ever going to know.”

This is playing out in marketing departments across verticals. Budget moving out of TV, traditional radio, and events, concentrating into digital, and then concentrating further into branded search and Performance Max. 

On paper, this looks like optimization. Efficiency metrics improve. 

But Jordan is blunt about what’s happening: these channels “look really good from an efficiency standpoint, but they’re not helpful for reaching net new audiences.”

The channels capturing more budget are often the channels best at claiming credit for demand that already existed, not the channels creating new demand. And because the attribution model can only see the click, it can’t tell the difference.

Building the Translation Layer: How to Structure a Marketing Report the C-Suite Actually Trusts

To build a report that closes this gap, start by replacing the metrics.

“CPL, cost per conversion, and platform ROAS — if you deliver that to a CFO or CEO, they’re like, what does that mean?” Instead, Jordan points to CAC (customer acquisition cost) as the unit that translates. Specifically: CAC by audience segment or product segment versus your target CAC, and how both have moved when compared period over period.

That last part matters. Showing a CAC number is useful. Showing how CAC changed—and being able to explain why—is what earns trust. Did CAC go up because you expanded into harder-to-reach audiences? Did it go down because you cut spend that was duplicating organic traffic? The C-suite doesn’t need a data dump; they need the story behind the number.

“Marketers don’t just have those numbers at their fingertips,” Jordan says, “so that’s why there’s a lot of measurement setup needed to be able to do that.” 

Building the ability to translate marketing performance into C-suite reporting requires CRM data, defined economics, and often new tracking. But the payoff is a report that speaks the same language as the rest of the business.

From there, Jordan’s structure for an executive-ready report is simple: Start with the bottom line (growth, revenue) and how the team is pacing against it, regardless of whether that team’s channel can claim full credit. 

“Even if I only manage your paid media and I can’t fully impact your full business revenue, starting with that helps earn the respect of the C-suite,” Jordan says. “We establish that we care about the same metrics. We’re driving towards the same thing.”

Then narrow: CAC by target, broken out by business line if relevant. What changed period over period. And, most importantly, what that change points to next. 

Jordan’s framing is direct: “Trying to do that concisely in three slides is a lot more impactful than a 50-page report. Most executives just want to know what they should do next and what data supports that.”

How to Report on Channels That Can’t Be Directly Tied to Revenue

Not every activity has a clean connection to the business’s bottom line. Jordan’s approach doesn’t pretend that connection exists when it doesn’t.

For channels like SEO or content, where you can’t simply say, “We shifted budget here and revenue moved accordingly,” Jordan looks for a leading indicator: something measurable today that has historically correlated with revenue down the line.

One example: a client selling a small number of very high-value items each month. Too few sales for any meaningful close-rate analysis by channel. 

Instead of forcing attribution onto a process that can’t support it, Jordan’s team checked a range of metrics against revenue and close rate over time: branded search impressions, total leads, subscribers, marketing-qualified leads. The goal was to find something that moves before revenue does.

Branded search volume turned out to be the signal, but it wasn’t immediately visible. Facebook spend against branded search, week to week, showed nothing. Build in a two-week lag, and the two lined up clearly. 

Makes sense once you see it: someone browsing Facebook is often earlier in their journey. They engage with content, and only later do they search for the brand by name.

“If you just throw up branded impressions, they’d probably be like, I don’t care about this. This is a fluffy metric,” Jordan says. “But if you can prove out, hey, no, this really correlates to your bottom line — and there’s a lag time between when you do this activity and it hits — you can really start to build that momentum.”

A Real Example: What Happens When the Translation Layer Doesn’t Exist

Here’s what happens when this translation layer doesn’t exist.

A client came to Silverback after letting go of their in-house marketer. That marketer’s reports had told a consistent story for months: paid media performing well, platform ROAS strong, path forward simple — more budget. 

Over six months, the business followed that advice. Spend went up. Revenue did not.

When Jordan’s team dug in, the pattern was familiar: branded search and Performance Max, with much of the PMax spend itself going toward branded terms. 

Organic search looked fine in aggregate, even improving. But that number was hiding something. The company had built strong non-branded organic visibility, and that growth was masking a sharp decline in organic branded clicks specifically. 

The business had a strong brand and great reviews, meaning a growing share of paid spend was just paying for customers who’d have found the business anyway.

Jordan’s team had a hypothesis. But reallocating a large share of budget on a hypothesis alone is a real risk if it’s wrong. So before changing anything, they tested it: split the client’s markets in two, held Performance Max spend steady in half, turned it down in the other half. Then watched what happened to revenue in each group.

Revenue in the markets where PMax spend dropped didn’t move. Organic brand search activity picked back up in those markets, exactly as predicted.

With that confirmed, roughly a third of the client’s budget moved out of Performance Max and branded search, into Meta and YouTube. 

Media spend stayed flat. Top-line revenue increased 14% year-over-year.

[Read the Full Case Study]

What Marketing Leaders Should Do Next

Most marketing leaders already sense something’s off. 

“I think 80% know that attribution is wrong,” Jordan says, “but only 10% have a good solution for it.” The tools to close that gap (customer unit economics, media mix modeling, incrementality testing) are more accessible to mid-market businesses than they’ve ever been.

The translation layer is the difference between a marketing team that can say, “Here’s why this is working,” with evidence the rest of the business actually trusts, and one stuck explaining, every quarter, why the dashboard and the P&L don’t agree.