I'd just finished presenting our new pricing strategy to the executive team. Six weeks of market research, competitive analysis, and customer interviews. We'd restructured our packaging, clarified our value metrics, and created what I thought was a clean, defensible pricing model.
The CFO approved it. The CRO approved it. Product approved it. We were set to launch the new pricing in thirty days.
Then I got a Slack message from someone I'd never worked with: the deal desk lead.
"Can we talk about the new pricing before it goes live? I have some concerns."
I didn't really know what deal desk did. They approved non-standard deals, handled custom contracts, managed pricing exceptions. Seemed operational, not strategic.
I took the call to be polite, but I wasn't expecting much.
That conversation completely changed how I understood our business.
The deal desk lead shared his screen. He'd pulled every non-standard deal from the past year—contracts where sales had negotiated prices, terms, or packaging that deviated from our standard offering.
"Before you launch new pricing, you should understand how customers actually buy from us. Because it's not how your pricing model assumes they do."
He showed me patterns I'd completely missed:
47% of enterprise deals removed features from our Enterprise tier because customers didn't want them—and negotiated lower prices.
63% of our expansion deals were custom bundles that didn't fit any of our standard packages.
The feature we'd positioned as our "premium differentiator" had been removed from 31 deals in the past six months because customers saw it as bloatware, not value.
I'd spent six weeks building a pricing model based on how I thought customers should value our product. The deal desk had twelve months of data showing how customers actually valued it.
I asked to see more.
What I learned from deal desk over the next three months changed PMM's entire approach to pricing, packaging, and positioning. Turns out, non-standard deals aren't exceptions to your strategy—they're evidence of what your strategy gets wrong.
What Non-Standard Deals Reveal About Positioning
I'd always thought of non-standard deals as outliers—special cases where sales had to get creative to close difficult prospects. One-off exceptions that didn't reflect our core business.
The deal desk lead corrected me: "These aren't outliers. We processed 127 non-standard deals last year. At our deal volume, that's 23% of all closed business. If nearly a quarter of your revenue doesn't fit your pricing model, your model doesn't reflect reality."
He walked me through categories of non-standard deals:
Feature Removal Deals: Customers Who Don't Want Your "Value"
These were deals where customers asked to remove features from our standard packages and pay less.
Example: Our Enterprise package included advanced analytics, API access, and premium support. We'd positioned advanced analytics as a key enterprise differentiator.
But I saw deal after deal where enterprise buyers said, "We don't need the analytics features. Can we remove them and pay less?"
Sales was approving these deals—removing 30% of the features and discounting price 15-20%.
I asked the deal desk lead, "Why do enterprise customers not want the analytics?"
"They already have analytics infrastructure. They don't want another dashboard—they want API access to pipe our data into their existing BI tools. The analytics features you're charging premium for are actually friction for them."
That was a positioning failure. We'd built analytics features thinking they added value for enterprise customers. But for many enterprise buyers, they added complexity.
What this revealed: Our "premium tier differentiator" was actually driving price negotiations and feature removals. Customers were paying us to remove the thing we thought they wanted most.
If I'd launched the new pricing model without understanding this, I would've doubled down on analytics as a premium feature, making the problem worse.
Custom Bundle Deals: When Standard Packages Miss the Use Case
These were deals where customers bought features from multiple tiers in combinations we didn't offer.
Example: We had three tiers—Basic ($X), Professional ($X), Enterprise ($X). Features were bundled into these tiers based on what we thought each customer segment needed.
But I saw dozens of deals where mid-market customers wanted Basic + one Enterprise feature, or Enterprise customers wanted Professional features without Basic features we forced them to buy.
One deal stood out: a mid-market customer who wanted our Basic tier plus one specific Enterprise feature (SSO). They didn't need any other Enterprise features, but our packaging forced them to buy the full Enterprise tier.
Sales negotiated a custom bundle: Basic price + $X for SSO only.
We'd done this custom deal 19 times in twelve months.
I asked, "Why don't we just offer SSO as an add-on instead of forcing it into the Enterprise tier?"
The deal desk lead said, "That's a great question. You should probably answer it, because I've been asking Product and PMM that for a year."
What this revealed: Our packaging assumptions were wrong. We'd bundled features based on "what kind of customer needs this," but customers bought based on "what specific job am I trying to do."
A mid-market company with security requirements needed SSO. A large enterprise without security requirements didn't. Tier-based packaging missed the actual buying patterns.
Discount Pattern Deals: Where Sales Discounts to Close
These were deals where sales gave discounts above the standard approval threshold.
The deal desk tracked why sales requested discounts. The patterns were brutal:
Competitive pressure: 42% of high-discount deals cited "competitor pricing" as the justification.
When I dug deeper, the competitor pricing they cited was cheaper because the competitor didn't bundle features customers didn't want. We were losing on price because our packaging forced customers to buy things they didn't value.
ROI uncertainty: 28% of high-discount deals cited "customer needs to prove ROI before paying full price."
This told me our pricing wasn't aligned with time-to-value. Customers weren't confident they'd realize value fast enough to justify full price, so they negotiated pilots, trial periods, or heavy discounts.
Feature gap discounting: 18% of high-discount deals cited "missing features competitor has."
These were deals where customers wanted to buy from us but we lacked parity on specific features. Sales discounted to compensate for the gap.
What this revealed: High discount rates weren't a sales execution problem—they were a positioning and packaging problem. Sales was discounting to compensate for PMM and Product gaps.
If I'd launched new pricing without understanding discount patterns, I would've blamed sales for "giving away margin" when the real problem was that our value proposition didn't support full price.
The Pricing Reality Check
After reviewing three months of non-standard deals with the deal desk, I had to admit some uncomfortable truths:
Truth #1: Customers didn't value what I thought they valued.
I'd positioned advanced analytics as a premium differentiator. Customers saw it as unnecessary bloat.
I'd assumed enterprise customers wanted comprehensive feature sets. They wanted specific capabilities without being forced to buy unrelated features.
I'd thought our packaging aligned with customer needs. It aligned with how we thought about customer segments, not how customers thought about their jobs to be done.
Truth #2: Our "standard pricing" wasn't standard.
Nearly a quarter of deals were non-standard. That's not exceptions—that's the norm.
If your pricing model requires constant customization to match what customers actually want to buy, your model is wrong.
Truth #3: Sales was compensating for PMM failures through discounting.
Every feature removal request was evidence that packaging didn't match needs.
Every custom bundle was evidence that standard tiers missed use cases.
Every competitive discount was evidence that positioning didn't justify the price premium.
Sales wasn't the problem. PMM was.
How We Fixed It: Pricing Operations ↔ PMM Partnership
I went back to the CFO and CRO and said, "I need to delay the pricing launch. The deal desk data shows our assumptions are wrong."
The CFO was skeptical. "We've already approved this. What changed?"
I walked them through the non-standard deal analysis. The patterns were undeniable.
The CRO said, "Why didn't we know this before?"
"Because PMM and deal desk weren't talking to each other. I was building pricing based on customer interviews and competitive analysis. Deal desk was seeing what customers actually negotiated. We were working from different realities."
We delayed the pricing launch by 60 days and rebuilt it based on deal desk data.
Change #1: Feature Unbundling
We stopped forcing enterprise customers to buy analytics features they didn't want.
New model: Core platform + optional analytics add-on.
Customers who wanted analytics could buy it. Customers who didn't could skip it.
Result: Enterprise close rates improved 14% because we stopped forcing unwanted features. Analytics attach rate was 38%, which meant 62% of customers didn't want it—exactly what deal desk data had shown.
Change #2: Use-Case-Based Add-Ons
We stopped forcing customers to buy full tier upgrades to get one specific feature.
New model: Basic tier + add-ons for SSO, advanced permissions, audit logs, and API rate limits.
Customers could buy exactly the capabilities they needed without tier upgrades.
Result: Mid-market average deal size increased 22% because customers bought add-ons instead of negotiating custom bundles or staying in lower tiers.
Change #3: Transparent Discount Policy
We analyzed why sales was discounting and created explicit discount policies for those scenarios:
- Multi-year commitments: up to X% discount (formalized what sales was already doing)
- Competitive displacement: up to X% discount if switching from named competitor (made competitive discounting strategic, not reactive)
- Early adopter pricing for new features: X% discount for 12 months (addressed ROI uncertainty by giving customers time to prove value)
Result: Average discount rate decreased from 23% to 16% because sales had structured ways to address customer objections without ad-hoc negotiation.
Change #4: Deal Desk → PMM Feedback Loop
We built a standing monthly review where deal desk shared:
- New patterns in non-standard deals
- Features being removed from packages
- Discount justifications clustering around specific objections
- Custom bundles being requested repeatedly
PMM used this data to:
- Identify packaging gaps
- Reveal positioning failures
- Find product gaps driving discounts
- Spot competitive threats before they showed up in win/loss data
This feedback loop meant PMM wasn't guessing at what customers valued—we had direct evidence from what they negotiated for.
What Changed When PMM Started Working With Deal Desk
The partnership between PMM and deal desk became one of the most valuable sources of market intelligence in the company.
Deal desk sees positioning gaps before anyone else.
When customers repeatedly remove the same feature from packages, that's positioning failure. Deal desk sees it in real-time.
When sales consistently discounts for the same competitive threat, that's weak differentiation. Deal desk sees it before win/loss analysis does.
When customers negotiate custom bundles, that's product-market fit misalignment. Deal desk sees which use cases your standard offering misses.
Deal desk data beats customer interviews for pricing decisions.
Customer interviews tell you what people say they value. Deal desk data tells you what they actually pay for.
I'd interviewed 30 customers who said advanced analytics were "very important." But deal desk data showed 62% of customers removed analytics when given the option.
Revealed preference (what people pay for) is more accurate than stated preference (what people say they want).
Deal desk prevents pricing launches that would fail.
If I'd launched the original pricing model without deal desk review, we would've:
- Increased the price of analytics features customers didn't want
- Kept forcing tier upgrades for single features
- Blamed sales for discount rates that were actually PMM failures
The deal desk partnership saved us from a pricing strategy that looked good on paper but would've failed in market.
The Uncomfortable Question This Raised
Working with deal desk forced me to confront a hard question: If customers have to negotiate custom deals to buy what they actually want, is our standard pricing working for anyone?
The data suggested it wasn't.
The customers who bought standard pricing without negotiation were either:
- Uninformed buyers who didn't realize they could negotiate (we were overcharging them)
- Buyers who didn't have procurement leverage (small companies who couldn't negotiate)
- Buyers who wanted everything in the package (rare)
Our most sophisticated buyers, our largest deals, and our highest-value customers all negotiated non-standard terms.
That meant our standard pricing was actually for unsophisticated buyers, not our ideal customers.
The solution wasn't to eliminate negotiation—it was to make standard pricing reflect what sophisticated buyers actually wanted, so they didn't have to negotiate custom deals every time.
When we rebuilt pricing based on deal desk insights, the percentage of non-standard deals dropped from 23% to 11%. That meant more customers could buy what they wanted without custom negotiations.
Sales cycles shortened. Legal review time decreased. Deal desk could focus on truly complex deals instead of processing routine customization requests.
What I'd Tell PMMs About Working With Deal Desk
If you're building pricing strategy without talking to deal desk, you're missing the most important source of truth about what customers actually value.
Here's how to start:
Ask deal desk for the last quarter's non-standard deals.
Request a list of every deal where sales negotiated:
- Feature removals
- Custom bundles
- Discounts above standard thresholds
- Non-standard contract terms
Look for patterns. If you see the same customization requested repeatedly, that's a signal your standard packaging is wrong.
Understand why customers negotiate.
Don't just see that customers negotiated—understand why.
Did they remove features because they didn't want them? That's a packaging problem.
Did they discount because of competitive pressure? That's a positioning problem.
Did they need custom bundles because standard tiers missed their use case? That's a product-market fit problem.
The "why" behind negotiation reveals what to fix.
Build a monthly deal desk review into PMM's rhythm.
Don't make this a one-time analysis. Meet with deal desk monthly to review:
- Emerging patterns in customization requests
- New discount justifications
- Changes in negotiation frequency by segment
This keeps PMM connected to pricing reality instead of pricing theory.
Give deal desk a voice in pricing decisions.
When you're building new pricing models, show them to deal desk before you launch.
Ask: "Based on what customers actually negotiate for, would this pricing work?"
If deal desk says "customers will just negotiate around this," listen to them. They know.
The Real Lesson
The deal desk knew our pricing better than I did because they saw what customers actually paid for, not what we wanted them to buy.
PMM builds pricing based on strategy—what we think customers should value, how we want to position tiers, what differentiation we want to emphasize.
Deal desk sees pricing based on reality—what customers negotiate for, what they remove, what they discount, what they actually pay.
The gap between strategy and reality is where pricing models fail.
The only way to close that gap is for PMM to work directly with deal desk, using non-standard deal data to validate—or correct—pricing assumptions before launch.
I thought I was the pricing expert because I'd done the research and built the model.
The deal desk lead was the actual pricing expert because he'd seen 127 examples of customers revealing what they truly valued through their negotiation behavior.
Now I don't launch pricing without deal desk review. And our pricing models actually match how customers want to buy.
That's worth delaying a launch for.