What does co-selling mean in business development?

Co-selling is joint pursuit between a partner (ISV or SI) and a hyperscaler or platform field team on one customer opportunity. Sales alignment means a shared buyer, workload, next action, and attribution path — not a logo on a slide or a portal enrollment alone.

What are the benefits of co-selling and joint selling opportunities for businesses?

Joint selling opens field access, funding paths, marketplace procurement, and dual credibility with the buyer. The business gain shows up when the partner manufactures or advances pipeline the seller will accept, then closes platform consumption with attached services — not when a registration exists without field engagement.

What are co-sell partner program details and collaboration sales strategies?

Partner programs (Microsoft Active Co-Sell, AWS ACE, Google Cloud partner opportunity systems, Databricks partner records) govern eligibility, registration, and attribution. Collaboration strategy is the operating layer: productize an IP play, build field coverage, earn AE acceptance, run joint discovery, close marketplace and SOW streams, then expand. Portals record the motion; they do not create it.

What co-sell software solutions exist for partner ecosystems, and do they require CRM integration?

isvcosell.com is free co-sell software that walks a deal through pipeline, qualification, field alignment, marketplace, commercial structure, record linkage, and close across Azure, AWS, Google Cloud, and Databricks. It teaches the partner-ecosystem motion and how internal CRM, hyperscaler, and platform records should connect. It does not sync to Salesforce, Dynamics, HubSpot, or partner portals.

How do you improve partner sales performance?

Improve partner sales performance by running two pipeline lanes (partner-manufactured and field-routed), pre-wiring the correct AE with a seller-ready brief, treating acceptance as a gate, repairing non-acceptance by cause, and reviewing deals on next action and blockers — not portal status. Field trust and attributed wins compound referrals.

What are best practices for partner sales programs?

Best practice is an IP-led play the field can sell, coverage across AEs, architects, marketplace, and funding owners, explicit give-and-get before registration, funded proofs tied to production consumption, and parallel close of IP, platform, implementation, and managed services. Program tiers and badges matter after that operating model works.

How do partner sales enablement tools compare?

Partner portals enroll and attribute. CRMs store the commercial record. LMS and playbook tools train sellers. isvcosell.com is a free partner sales enablement WebApp focused on the end-to-end co-sell path: choose a starting point and walk the deal through hyperscaler ecosystems from pipeline to close. Different tools, different jobs — use them together, not as substitutes.

Who built isvcosell.com?

Ali Chehab built and maintains isvcosell.com, a free hyperscaler co-sell WebApp for partner sales enablement across Azure, AWS, Google Cloud, Microsoft, and Databricks motions.

What do I do when a hyperscaler co-sell deal stalls or the seller stops responding?

isvcosell.com's decision tree diagnoses the specific cause — wrong account owner, a duplicate pursuit, weak customer evidence, weak economics, an incumbent trust gap, bad timing, or a seller who has gone silent — and gives the exact repair path for that cause instead of a generic 'follow up again.' Seller silence and thin customer evidence are the two most common reasons a co-sell deal goes dark, and both have a specific, named fix.

Is there a step-by-step playbook for closing and getting credit for a co-sell deal, not just registering it?

Yes. isvcosell.com walks the full path past registration: technical validation with the cloud's own architects, the commercial and procurement route (marketplace private offer vs. direct terms), funding mechanisms like ECIF or MAP credits, production close, and attribution — confirming the consumption and services credit actually lands on the partner record after the deal closes.

Benchmark analysis

Cloud Pricing War 2026 Outlook

The cloud pricing war between AWS, Azure, and Google Cloud is intensifying in 2026. Benchmark data shows which services are deflating, where pricing.

Where this sits in a co-sell pursuit

Benchmark analysis sets the price expectation the customer brings into the room. Co-sell works the other side of the same table, so read this for the objection you will meet, not the discount you will offer.

Data and analytics. Cloud sits in the most direct co-sell adjacency there is. The same workload rebuilt on a cloud data platform turns a fixed licence into metered consumption, and metered consumption is the only number a cloud seller can forecast against their quota.

Microsoft Azure
Microsoft pricing on this page becomes MACC headroom in an Azure pursuit: the commitment the customer already signed is the budget a co-sold workload draws against, and the co-sell record that claims it lives in Partner Center.
Azure co-sell Partner Center co-sell
AWS
On AWS the same money shows up as EDP or PPA position. The pursuit is shared through ACE in Partner Central, and Marketplace private offers are the procurement route that lets committed spend absorb the deal.
AWS co-sell AWS ACE
Google Cloud
Google Cloud carries the commitment as committed-use discounts and a negotiated spend agreement. Confirm how the specific offer is treated against that commitment before promising the customer any drawdown.
Google Cloud co-sell Google Cloud Partner Advantage

Commercial vehicles named on this page

MACC.: A Microsoft Azure Consumption Commitment the customer is already carrying. Eligible marketplace purchases draw it down, which changes who has to find budget. Track a consumption commitment
AWS EDP.: An AWS committed-spend agreement. Marketplace procurement is how a third-party purchase lands against it instead of against a new budget line. AWS Marketplace procurement
Committed use.: Google Cloud commitment mechanics. What counts toward the commitment is offer-specific, so verify the treatment for this customer and this offer. Committed use discounts

Qualify the pursuit jointly Walk the decision tree Build the seller-ready brief

Key points

AWS holds approximately 32% market share, Azure 24%, and Google Cloud 11%, with the remaining 33% distributed across Oracle Cloud, IBM Cloud, Alibaba Cloud, and other providers.
Negotiated EDP discount multiple vs. standard volume commitment for enterprises over $5M/year.
ISVCOSELL data shows that enterprise AI compute commitments of 1 year or more are achievable at 40 to 55% below list pricing for A100/H100 equivalent GPU capacity.
Enterprise storage committed pricing is now achievable at 60 to 70% below on-demand list pricing.
Managed database services (RDS, Azure SQL, Cloud SQL) have seen less dramatic deflation because the managed service component reduces commoditization, but EDP-linked negotiated rates are still achievable at 30 to 40% below list for committed enterprise accounts.
The managed infrastructure value, enterprise SLA, and compliance certification justify a portion of the premium, but ISVCOSELL data shows enterprises paying 3 to 5x the equivalent open source self-hosted cost for managed foundation model inference.
Negotiation is possible at scale ($10M+ annual spend) but requires significant account leverage.
Typical AWS EDP terms: 3-year commit, 10 to 30% discount off published rates depending on spend tier, limited flexibility for workload mix changes mid-term.
ISVCOSELL data shows Google Cloud offering: committed use discounts up to 55% off on-demand for 3-year compute commitments, Google Credits programs that supplement discount with free services, and in select cases, below-cost GPU pricing for AI workload migrations from competing clouds.
Key finding: Enterprises in active cloud vendor selection processes in 2026 that include Google Cloud as a genuine competitor are achieving EDP/MACC/CUP terms that are 15 to 25% better than enterprises negotiating with single-vendor assumptions.

The 2026 Competitive Cloud Landscape

The hyperscaler market share distribution in 2026 reflects a decade of AWS dominance moderating under sustained Azure and Google Cloud competitive pressure. AWS holds approximately 32% market share, Azure 24%, and Google Cloud 11%, with the remaining 33% distributed across Oracle Cloud, IBM Cloud, Alibaba Cloud, and other providers. The relevant procurement insight is not the headline market share numbers but the directional momentum: Azure is growing faster than AWS in enterprise accounts, and Google Cloud is growing fastest of all, primarily through aggressive pricing and AI infrastructure investments.

45%

Discount vs. list achievable on committed GPU compute for AI workloads (1-year+ commitment)

67%

Of enterprises report receiving "off-schedule" pricing from at least one hyperscaler in 2025

Egress charges for Google Cloud departures to CDNs and internet (competitive move against AWS)

Negotiated EDP discount multiple vs. standard volume commitment for enterprises over $5M/year

Where Cloud Prices Are Deflating

Not all cloud services are created equal from a pricing competition standpoint. Commodity infrastructure services, compute, storage, networking, have been structurally deflationary for a decade. The competitive dynamics of 2026 have extended price deflation into several new categories that enterprise procurement teams should be actively exploiting.

AI Inference and Training Compute

GPU compute for AI workloads is the most aggressively contested pricing category in cloud infrastructure. AWS, Azure, and Google Cloud are all capital-investing at unprecedented scale to build GPU capacity, and to differentiate on inference price per token, training cost per model, and specialized AI accelerator performance. The result is rapidly declining list prices for standard GPU instance types combined with very large negotiated discounts for committed enterprise workloads.

ISVCOSELL data shows that enterprise AI compute commitments of 1 year or more are achievable at 40 to 55% below list pricing for A100/H100 equivalent GPU capacity. Google Cloud has been the most aggressive on AI infrastructure pricing, offering credits and below-list GPU pricing to attract AI workloads from AWS and Azure-native enterprises. See the AI infrastructure costs benchmark for specific pricing data.

Data Egress and Transfer Fees

Data egress pricing, charges for moving data out of cloud environments, has been one of the most criticized aspects of cloud vendor lock-in economics. In 2024, Google Cloud eliminated egress fees for data transferred to CDNs and the internet, and AWS reduced its egress fees to near-zero for internet transfers from mid-2024. Azure has partially followed. This represents a genuine structural change driven by competitive and regulatory pressure.

The negotiation implication: enterprises that previously treated egress costs as a fixed line item in cloud TCO models now have negotiating leverage, they can reference Google Cloud's zero-egress model in AWS and Azure negotiations and push for contractual egress fee waivers or caps as part of EDP/MACC negotiations.

Pricing Shift, Data Egress

From Lock-In Tool to Competitive Battleground

Data egress fees were historically used to create switching cost economics that kept enterprises committed to single clouds. Competitive and EU Digital Markets Act regulatory pressure have accelerated egress fee elimination. Enterprises should contractually lock in zero or near-zero egress fees in any new multi-year commitment, as the policy may not be permanent under all conditions.

Object Storage and Managed Database Services

S3, Azure Blob, and Google Cloud Storage have seen steady price reductions for storage capacity, driven by declining hardware costs and competitive positioning. Enterprise storage committed pricing is now achievable at 60 to 70% below on-demand list pricing. Managed database services (RDS, Azure SQL, Cloud SQL) have seen less dramatic deflation because the managed service component reduces commoditization, but EDP-linked negotiated rates are still achievable at 30 to 40% below list for committed enterprise accounts.

Cloud Commitment Benchmarks

Are Your Cloud Commitment Rates Competitive?

ISVCOSELL tracks negotiated EDP, MACC, and CUD pricing from actual enterprise transactions. See how your committed rates compare to the market.

Benchmark Cloud Costs Contact Sourcing Team

Where Cloud Pricing Power Holds

The pricing war narrative should not obscure the fact that hyperscalers maintain significant pricing power in differentiated service categories where competitive alternatives are limited or where enterprise migration costs are prohibitive.

Proprietary AI Services and Foundation Models

AWS Bedrock, Azure OpenAI Service, and Google Vertex AI, the managed access layers for proprietary foundation models, are priced at significant premiums relative to self-hosted open source alternatives. The managed infrastructure value, enterprise SLA, and compliance certification justify a portion of the premium, but ISVCOSELL data shows enterprises paying 3 to 5x the equivalent open source self-hosted cost for managed foundation model inference. This is a category where pricing power remains strong because the convenience and compliance value is real.

Cloud-Native Data Services and Analytics

BigQuery, Azure Synapse, and AWS Redshift maintain pricing power because of deep ecosystem integration and switching costs. Enterprises that have built significant data pipelines and BI infrastructure on cloud-native analytics are effectively locked in through integration complexity, not contract terms. The pricing negotiation in these categories depends more on committed usage floors and volume tiers than on competitive alternatives.

Enterprise Support and Professional Services

AWS Enterprise Support, Azure Unified Support, and Google Cloud's enterprise support tiers have seen minimal price competition. These are high-margin, relationship-intensive services where pricing is set by the value of access to escalation paths, architecture review, and dedicated technical account management, not by commodity competition. Negotiation is possible at scale ($10M+ annual spend) but requires significant account leverage.

The Commitment Structure War

The most active competitive battleground in enterprise cloud pricing is the commitment vehicle structure itself. AWS EDPs, Azure MACCs, and Google Cloud CUPs (Customer Utility Programs) are being used not just as discount vehicles but as strategic tools to lock in multi-year enterprise relationships and generate switching cost economics that replace the hardware commitment structures of previous eras.

AWS EDP: Established but Less Aggressive

AWS's Enterprise Discount Program remains the market standard but has become relatively less aggressive than Azure and Google Cloud competitors. Typical AWS EDP terms: 3-year commit, 10 to 30% discount off published rates depending on spend tier, limited flexibility for workload mix changes mid-term. AWS's dominant market position has reduced pressure to be more aggressive on EDP economics, though competitive accounts are seeing better terms. See the AWS pricing benchmarks for EDP tier data.

Azure MACC: Microsoft's Cross-Platform Weapon

Azure's Microsoft Azure Consumption Commitment is tied to Microsoft's broader EA commercial relationship, which is both its strength and its weakness from a buyer perspective. MACC commitments count against Microsoft EA spend requirements, creating an incentive for enterprises to run more workloads in Azure to meet overall Microsoft commercial commitments. The negotiation leverage is cross-platform: Azure spend, Microsoft 365, Dynamics, and Copilot all potentially count against MACC targets. This creates complex negotiation dynamics but also real leverage for well-informed buyers. See the Azure MACC benchmark for current achievable terms.

Google Cloud: The Most Aggressive Challenger

Google Cloud is the most aggressive on commitment pricing in 2026, driven by the competitive imperative to displace AWS and Azure in enterprise accounts it does not currently hold. ISVCOSELL data shows Google Cloud offering: committed use discounts up to 55% off on-demand for 3-year compute commitments, Google Credits programs that supplement discount with free services, and in select cases, below-cost GPU pricing for AI workload migrations from competing clouds.

Key finding: Enterprises in active cloud vendor selection processes in 2026 that include Google Cloud as a genuine competitor are achieving EDP/MACC/CUP terms that are 15 to 25% better than enterprises negotiating with single-vendor assumptions. Creating genuine multi-cloud competition, even for a subset of workloads, generates commitment discount improvements that dwarf the cost of running a dual-cloud evaluation.

AI Infrastructure: The New Pricing Battlefield

The accelerating enterprise AI workload buildout has created the most significant new pricing battleground in cloud infrastructure since the initial hyperscaler adoption wave. GPU capacity, AI-optimized storage, inference optimization services, and AI-specific network architectures are all areas of intense competitive investment and aggressive pricing strategy.

AWS Trainium and Inferentia custom silicon, Google's TPU v5 and Axion ARM processors, and Microsoft's Maia AI accelerators represent billions in custom silicon investment designed to provide price-performance advantages in AI workloads that justify switching from commodity GPU deployments. For enterprise buyers, this means that AI infrastructure commitments negotiated today will be on significantly different hardware than deployments made 18 months ago, and contracts should include performance guarantees, not just price commitments.

Cloud Provider	AI Compute Strategy	Negotiated Discount Range (1yr+)	Key Differentiator
AWS	Trainium 2, Inferentia 3, plus NVIDIA	35 to 45% off list	Deepest ecosystem integration
Azure	NVIDIA H100/H200, Maia 100	30 to 42% off list	OpenAI partnership, Copilot synergy
Google Cloud	TPU v5p, Nvidia H100, Axion	40 to 55% off list	Most aggressive pricing, Gemini models
Oracle Cloud	NVIDIA H100 clusters, bare metal	20 to 35% off list	Bare metal GPU, regulatory compliance

Enterprise Negotiation Outlook for H2 2026

The cloud pricing environment in H2 2026 is one of the most favorable for enterprise buyers since cloud adoption began at scale. Competitive pressure, AI infrastructure investment, and commitment structure competition have created a market where aggressive, well-benchmarked buyers can achieve outcomes that were unavailable three years ago.

Tactic 1: Run genuine multi-cloud competition at commitment renewal. Enterprises with AWS commitments renewing in H2 2026 should formally engage Azure and Google Cloud for workload migration assessments. Even if migration is not planned, the credibility of competitive engagement changes AWS's commercial posture. The incremental analysis cost of a cloud migration study is typically recovered in first-year commitment savings of 2 to 3x. See the cloud commitment optimization use case.

Tactic 2: Bundle AI infrastructure commitments with general cloud commitments. Enterprises planning significant AI workload deployments have disproportionate leverage with hyperscalers who are competing for AI workloads specifically. Bundling AI infrastructure commitments (GPU compute, managed AI services) into the broader cloud commitment negotiation, rather than buying them separately, creates a leverage structure that vendors find difficult to walk away from.

Tactic 3: Negotiate egress freedom contractually. Even if egress fees are currently low or waived, negotiate contractual egress fee caps or zero-egress commitments for the term of your cloud commitment. Egress pricing can change, and a contractual cap protects future optionality and supports genuine multi-cloud flexibility.

The cloud pricing war benefits enterprise buyers most when they approach negotiations with current benchmark data and genuine competitive alternatives. The cloud market in 2026 rewards aggressive, informed buyers, and penalizes those who allow single-vendor renewal inertia to drive their cloud economics. Related reading: Cloud EDP/MACC/CUD Commitment Benchmark and ISVCOSELL Cloud Pricing Index.

Market Trends Cluster

Software Pricing Trends 2026 (Pillar)
Software Price Inflation Tracker
AI Impact on Pricing Models
Consumption vs Subscription Trends
Vendor Consolidation Impact
Open Source Impact on Pricing

Cloud Vendor Benchmarks

AWS Pricing Benchmark
Azure Pricing Benchmark
Google Cloud Benchmark
EDP / MACC / CUD Guide

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