Case Study · Google Cloud · Media & Entertainment

$11.4M Saved Renegotiating a Google Cloud Enterprise Agreement

A global media company had committed $34M to Google Cloud Platform with a top-heavy consumption obligation and no egress protections. We renegotiated the CUD structure, introduced multi-cloud flexibility clauses and reduced committed spend by $11.4M.

$11.4M
Savings Secured
34%
Commitment Reduction
5 yr
Multi-cloud Exit Rights
$0.01/GB
Capped Egress Fees

Client Context

A $5.2B revenue global media and entertainment company with a distributed infrastructure and emerging AI/ML workloads faced a critical problem: locked into a $34M Google Cloud Platform commitment with deteriorating economics and no pathway to multi-cloud flexibility.

Industry
Media & Entertainment
Annual Revenue
$5.2B
Cloud Commitment
$34M (3-year CUD)
GCP Tenure
4 years, 85% infra migrated

The Challenge

The client had signed a $34M 3-year Committed Use Discount (CUD) structure with Google Cloud, initially driven by aggressive discounts tied to exclusivity provisions. By month 18, actual consumption was tracking 28% below the committed baseline — creating a projected $9.6M shortfall charge at the end of the term.

Google's account team had begun discussing the shortfall in renewal planning meetings, using it as leverage to push the client toward additional AI/ML services from Google's Vertex AI platform. The situation was compounded by the fact that the client had no multi-cloud provisions and faced punitive egress fees if they wanted to migrate workloads to AWS — effectively trapping the company within Google's ecosystem.

This dynamic created a precarious situation: either the company would accept the $9.6M shortfall penalty, or it would be forced to adopt expensive new AI services to "fill the gap" — services that may not have aligned with their technical roadmap or budget priorities.

Our Approach

1

Consumption Gap Analysis

We modelled the true consumption trajectory using 18 months of actual billing data, identifying three categories: on-track workloads (42%), at-risk workloads (31%), and legacy workloads unlikely to migrate to GCP (27%). This gave us a defensible restructuring rationale grounded in empirical data rather than negotiation theater.

2

Competitive Positioning

We ran a parallel AWS proposal for the 27% legacy workloads. Having an actual AWS pricing proposal — not a theoretical alternative — changed the negotiating dynamic immediately. Google's account team could no longer dismiss the possibility of partial cloud migration.

3

CUD Restructuring

We proposed a "consumption-aligned CUD" with quarterly review mechanisms, eliminating the binary shortfall-or-not structure. Google accepted because the alternative was the client partially migrating to AWS and reducing GCP's total contract value.

4

Egress & Exit Negotiations

We negotiated hard limits on egress fees for any workloads moved within the next 5 years, and inserted a data portability clause requiring Google to provide structured export assistance. This eliminated Google's ability to use exit friction as a retention mechanism.

Results

  • CUD restructured from $34M to $22.6M (-$11.4M, -34%) — eliminating the projected shortfall charge
  • Quarterly consumption review mechanism inserted — the first time Google had agreed to this dynamic adjustment model for this client
  • Egress fees capped at $0.01/GB for migrations to any other cloud platform within 5 years
  • Data portability clause requiring 90-day assisted migration support — giving the client a realistic pathway to exit if needed
  • Multi-cloud addendum allowing up to 40% of workloads on non-GCP infrastructure without penalty
  • Vertex AI piloting provisions — 6-month paid pilot before any AI workload commitment
  • Removed exclusivity language from the original contract — restoring the client's negotiating flexibility

"We thought we were trapped. Our entire infrastructure was on Google Cloud and the shortfall was looming. The Negotiation Experts found leverage we didn't know we had and turned a $9.6M problem into an $11.4M solution."

— Chief Technology Officer, Global Media Group

Key Lessons

Cloud CUD shortfalls are negotiable

Especially when you can demonstrate a credible multi-cloud alternative. The key is to convert shortfalls from a binary penalty into a negotiating point. Most hyperscalers would rather restructure a CUD than watch a customer walk to a competitor.

Egress fee lock-in is Google's primary retention mechanism

Always negotiate caps before signing any GCP commitment. Egress fees that run $0.12/GB or higher can easily cost millions in a large-scale migration. Lock in per-GB limits at signing — it becomes nearly impossible to negotiate them down later.

Google's AI/ML upsell pressure is predictable

Vertex AI, Gemini, and other AI services are increasingly used as CUD "gap fillers" in renewal conversations. Use this as a negotiation chip, not an obligation. Insist on pilot programs with clear ROI metrics before committing to AI workloads.

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