RevOps Built Better Launch Readiness Metrics Than I Did

Three days before our biggest product launch of the year, I declared us ready.

Sales was trained—92% certification rate on the new positioning.

Enablement materials were finished—battle cards, demo scripts, FAQ docs, and competitive positioning all loaded into the sales portal.

Marketing campaigns were live—ads running, emails scheduled, webinar confirmed.

I sent a Slack message to the exec team: "Launch is go. Sales is ready."

The VP of Revenue Operations replied: "Can we talk?"

On the call, he pulled up a spreadsheet I'd never seen.

"You've trained sales on a new product. That's great. But have you checked whether we have enough pipeline coverage to support this launch?"

"What do you mean?"

"Sales needs to hit $12M in Q4. They're currently forecasted at $10.8M—$1.2M short. You're launching a new product that will consume 20-30% of their selling time for the next month. During that time, their productivity on existing products will drop. That gap is going to get bigger, not smaller."

I hadn't thought about that. I'd been focused on launch execution—training, messaging, campaigns. I hadn't thought about launch impact on existing business.

He continued: "Also, you're launching this product to all territories equally. But some territories are already behind quota and some are ahead. The territories that are behind can't afford to spend time on a new product—they need to close existing pipeline. The territories that are ahead can invest time in learning something new."

"So what should we do?"

"Phase the launch. Give the new product to territories that are ahead of plan first. Let them become experts and build case studies. Roll it to struggling territories later, once we have proven plays and they've stabilized their existing business."

This had never occurred to me. I'd thought about launch readiness as "is sales prepared?" RevOps was thinking about launch readiness as "can sales actually execute without destroying their current number?"

They were right. Launch readiness isn't just about training and content. It's about pipeline coverage, sales capacity allocation, and revenue impact.

That conversation changed how I think about launches entirely.

What PMM Gets Wrong About Launch Readiness

For years, I measured launch readiness the way most PMMs do:

Is sales trained? ✓ (92% certification)

Are materials ready? ✓ (battle cards, scripts, slides complete)

Are campaigns live? ✓ (ads, emails, webinars scheduled)

Is product actually ready to sell? ✓ (GA shipped, pricing finalized)

I'd check all those boxes and call the launch "ready."

But I'd missed the metrics that RevOps cared about—the metrics that determined whether a launch would actually succeed or fail:

Do we have enough pipeline coverage to support sales spending time on a new product?

Are territories allocated correctly based on quota attainment and capacity?

Will this launch cannibalize existing product sales or expand the total addressable pipeline?

Can sales actually absorb a new product right now, or are they already underwater?

These weren't PMM questions. They were RevOps questions.

And until I started working with RevOps on launch planning, I didn't realize how critical they were.

The Launch Readiness Metrics RevOps Actually Tracks

After that first conversation, the RevOps lead and I started collaborating on every major launch. He built a launch readiness dashboard that tracked metrics I'd never considered.

Here are the five metrics RevOps taught me actually determine launch success:

Metric #1: Pipeline Coverage Post-Launch

What it measures: Whether the company has enough pipeline in existing products to hit the number while sales ramps on the new product.

Why it matters: Launching a new product isn't free. It costs sales productivity. Reps spend time learning the new product, refining their pitch, and figuring out which prospects are a fit. During that ramp period, their productivity on existing products drops 20-30%.

If you're already behind on pipeline, launching a new product makes the gap worse.

How RevOps tracks it:

Pipeline coverage = Total pipeline / Quarterly revenue target

Healthy coverage: 3-4x (meaning you need $3-4 in pipeline to deliver $1 in closed revenue, based on historical win rates).

RevOps checks:

• Current pipeline coverage
• Expected pipeline coverage after accounting for sales productivity drop during launch ramp
• Whether that coverage is still sufficient to hit the quarterly target

What this revealed:

We planned a Q4 launch of a new product. RevOps ran the numbers:

• Q4 target: $12M
• Current pipeline: $38M (3.2x coverage—healthy)
• Expected sales productivity drop during launch: 25% for 4 weeks
• Lost pipeline progression during those 4 weeks: ~$4M
• Pipeline coverage after launch ramp: $34M / $12M = 2.8x

Still acceptable, but closer to the edge than I'd realized.

If we'd been at 3x coverage instead of 3.2x, RevOps would've recommended delaying the launch until pipeline was healthier.

PMM implication: You can't just launch whenever the product is ready. You have to launch when the sales organization can afford to invest time learning something new without jeopardizing the current quarter.

Metric #2: Territory-Level Quota Attainment

What it measures: Which territories are ahead of plan, on plan, or behind plan.

Why it matters: A territory that's at 60% of quota in week 10 of the quarter can't afford to spend time learning a new product. They need to close existing deals.

A territory that's at 115% of quota can afford to experiment with new products and become the early expert.

How RevOps tracks it:

For each territory:

• Quota attainment % (actual closed revenue / quarterly quota)
• Week of quarter (how much time is left to make up gaps)
• Pipeline health (whether they have enough pipeline to hit quota)

Territories are categorized:

• Green: Ahead of plan (can invest time in new products)
• Yellow: On plan (can invest selectively)
• Red: Behind plan (focus on existing business only)

What this revealed:

When we planned our Q3 launch, RevOps showed me territory-level readiness:

• 3 territories: Green (120% of quota attainment, healthy pipeline)
• 5 territories: Yellow (95-105% of quota attainment)
• 4 territories: Red (65-80% of quota attainment, pipeline gaps)

I'd been planning to launch to all 12 territories simultaneously.

RevOps said, "Launch to the 3 green territories first. Let them figure out the pitch, close the first few deals, and build proof points. Then roll to yellow territories mid-quarter once we have case studies and proven plays. Don't roll to red territories until Q4—they need to focus on existing business right now."

We phased the launch. The green territories became experts, closed early deals, and generated the case studies that made the yellow territories' ramp faster.

The red territories never felt pressured to learn a product they couldn't afford to prioritize.

PMM implication: Not all territories should get new products at the same time. Launch readiness varies by territory health.

Metric #3: Sales Capacity Allocation

What it measures: How much of sales' time is currently allocated to different products, and whether there's capacity for a new product.

Why it matters: Sales reps have finite time. If they're already selling 4 products and you add a 5th, something gets deprioritized.

If you don't explicitly decide what gets deprioritized, reps will default to selling what's easiest—which might not be the new product you just launched.

How RevOps tracks it:

For each product:

• % of deals where this product is primary (how often sales leads with it)
• % of demo time spent on this product
• % of closed revenue from this product

They calculate "capacity saturation": How much of sales' time is already allocated?

If capacity saturation is >80%, adding a new product without retiring or deprioritizing something else will result in low adoption.

What this revealed:

We were planning to launch Product D into a portfolio that already included Products A, B, and C.

RevOps showed me capacity allocation:

• Product A: 55% of sales time
• Product B: 30% of sales time
• Product C: 15% of sales time
• Total: 100% saturated

There was no room for Product D unless we explicitly deprioritized something.

I asked, "What if we just launch it and let sales figure out prioritization?"

RevOps said, "Then sales will keep selling Product A (easiest to sell), ignore Product D (hardest to learn), and you'll wonder why your launch failed."

We made a hard decision: Sunset Product C. It had the lowest revenue contribution and highest support costs.

That created capacity for Product D. Sales had explicit guidance: Replace Product C selling time with Product D.

Product D adoption was high because sales had capacity to invest in it.

PMM implication: Launch success requires explicit capacity management. If you don't decide what gets deprioritized, the new product loses by default.

Metric #4: Cannibalization Risk Assessment

What it measures: Whether the new product will steal revenue from existing products or expand total addressable market.

Why it matters: Launches that cannibalize existing products can still be strategically important (better margin, better retention, more scalable), but you need to plan for the revenue impact.

If you expect 30% cannibalization and don't account for it, you'll miss your quarterly target.

How RevOps tracks it:

They analyze:

• ICP overlap between new product and existing products (how many target customers are the same?)
• Use case overlap (does the new product solve the same problem as an existing product?)
• Historical launch cannibalization rates (in past launches, what % of new product revenue came from customers who would've bought an existing product?)

What this revealed:

We launched a new mid-market tier of our product. I positioned it as "expanding our addressable market to smaller companies."

RevOps analyzed the ICP:

• 40% of mid-market prospects would've previously been sold our Enterprise tier at higher price points
• Expected cannibalization: 40% of mid-market revenue would come at the expense of Enterprise revenue

This wasn't bad—we wanted to serve mid-market—but it meant the net new revenue from the launch was 60% of total mid-market revenue, not 100%.

If I'd forecast $6M in mid-market revenue without accounting for cannibalization, RevOps would've been $2.4M short of plan.

PMM implication: Cannibalization isn't always bad, but you have to forecast it accurately. New revenue isn't always net new revenue.

Metric #5: Adoption Velocity Tracking

What it measures: How quickly sales reps ramp to using the new product in deals.

Why it matters: Training doesn't equal adoption. Just because sales is certified doesn't mean they'll actually use the new product.

RevOps tracks how long it takes before reps consistently include the new product in their sales motions.

How RevOps tracks it:

Post-launch, they measure:

• % of demos that include the new product (week over week)
• % of opportunities that include the new product
• Time from launch to first deal closed (by rep)

They set adoption targets:

• Week 2: 30% of demos should mention the new product
• Week 4: 60% of demos
• Week 8: 80% of demos (mature adoption)

If adoption velocity is slower than expected, it signals either training gaps or product-market fit issues.

What this revealed:

We launched a new product and trained all sales reps. Certification rate: 94%.

RevOps tracked adoption velocity:

• Week 2: 12% of demos mentioned new product
• Week 4: 18% of demos
• Week 8: 23% of demos

Far below the 80% target.

I assumed training was the problem—sales didn't understand how to position the new product.

RevOps said, "It's not training. Reps understand the product. They're just not seeing opportunities where it fits."

We analyzed the ICP. The new product solved a problem that only 30% of our prospects had. Sales was certified on it, but only 30% of their deals were good fits.

The issue wasn't adoption failure—it was realistic adoption ceiling. We'd launched a product with narrower ICP fit than expected.

PMM implication: Adoption velocity reveals product-market fit issues faster than win/loss interviews. If sales isn't using a product they're trained on, the ICP might be narrower than you thought.

How This Changed Launch Planning

After learning RevOps's launch readiness framework, I completely rebuilt how PMM approaches launches.

Old launch planning:

1. Product is ready
2. Train sales
3. Create enablement materials
4. Launch campaigns
5. Declare success

New launch planning:

1. Check pipeline coverage—can sales afford productivity drop?
2. Assess territory health—which territories can launch first?
3. Model capacity allocation—what gets deprioritized to make room?
4. Forecast cannibalization—is this net new revenue or shifted revenue?
5. Set adoption velocity targets—how fast should reps ramp?
6. Phase launch to territories based on readiness
7. Track adoption velocity and adjust enablement based on data

The new approach treats launches as revenue operations, not marketing campaigns.

The Uncomfortable Reality

Working with RevOps on launch readiness revealed something I didn't want to admit: Some launches should be delayed or canceled.

Example 1: The launch we delayed three months

We were planning a Q2 launch. RevOps showed that Q2 pipeline coverage was already weak (2.6x, needed 3.5x minimum). Launching a new product would drop productivity during a quarter where we were already at risk of missing the number.

I wanted to launch anyway—we'd been building toward this launch for six months.

RevOps said, "If you launch in Q2, you'll miss the quarterly target and the launch will get blamed. If you delay to Q3 when pipeline coverage is healthier, the launch will succeed."

We delayed. Q3 pipeline coverage was 4.1x. We launched with buffer. Sales had capacity to ramp on the new product without jeopardizing the quarter.

The launch succeeded because we launched when the business could absorb it.

Example 2: The launch we phased over 8 months

We launched a complex new product that required significant sales enablement. RevOps said, "No way can all territories ramp on this simultaneously. Half of them are struggling to hit quota on existing products."

We phased the launch:

• Month 1-2: Launch to 2 top-performing territories
• Month 3-4: Expand to 4 more territories once we had proof points
• Month 5-8: Roll to remaining territories as their quota health improved

This felt slow. I wanted immediate full rollout.

But phased launch meant early territories became experts, built case studies, and refined the pitch before broader rollout. Later territories had proven plays instead of figuring it out themselves.

Adoption was higher than any previous launch because we didn't overwhelm the sales organization.

What I'd Tell PMMs About Launch Readiness

If you're measuring launch readiness without talking to RevOps, you're missing half the picture.

Here's what to ask RevOps before every major launch:

Do we have sufficient pipeline coverage to support sales productivity drop during ramp?

If not, delay the launch or accept that you'll miss the quarterly number.

Which territories are healthy enough to launch to first?

Phase launches based on territory quota health, not arbitrary rollout plans.

What are we deprioritizing to make room for this product?

Sales capacity is finite. Something has to give.

What's the cannibalization forecast?

Know whether this is net new revenue or shifted revenue from existing products.

What's the adoption velocity target, and how will we track it?

Don't assume training equals adoption. Measure actual usage.

RevOps has the data and models to answer these questions. PMM has the positioning and enablement.

Together, you can plan launches that actually succeed instead of launches that look good on paper but fail in execution.

Launch readiness isn't just "is sales trained?" It's "can the business execute successfully?"

That's a RevOps question as much as a PMM question.