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.

Use cases

AI Platform Selection

Don't overpay for AI infrastructure. Benchmark OpenAI, Anthropic, Google, AWS AI, and Azure AI pricing before you commit.

Where this sits in a co-sell pursuit

Where buyer-side pricing data gets used. Each one has a seller-side mirror somewhere in the co-sell motion.

AI and ML. AI Platform Selection is the least anchored line in most estates: newest contracts, shortest terms, weakest switching costs. That makes it the easiest spend to redirect into cloud-native services, which is why it opens pursuits that an ERP conversation cannot.

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

Commercial vehicles named on this page

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

Co-sell pursuit flow Walk the decision tree Build the seller-ready brief

AI Pricing Is the Wild West, and Vendors Know It

Enterprise AI contracts are among the most opaque in technology. Published token prices are irrelevant, enterprise agreements involve volume tiers, reserved capacity, fine-tuning fees, API rate limits, and enterprise support layers that bears no resemblance to the developer pricing page. Vendors negotiate individually and never publish what they charge enterprise accounts.

What AI Buyers Face

No published enterprise pricing, every deal is bespoke
Volume tiers structured to obscure effective per-token cost
Capacity commitments tied to models that may deprecate
Fine-tuning, inference, and storage billed separately
Hyperscaler bundles (AWS Bedrock, Azure OpenAI) obscure true AI cost
Multi-year commitments requested before market data is available
Competing vendor quotes not disclosed, removing leverage

What Benchmarking Provides

Actual enterprise contract prices, matched to your usage profile
Effective per-token pricing normalized across commitment tiers
Typical discount ranges by deal size and volume commitment
Contractual terms: SLA, uptime, IP rights, data retention
Negotiation leverage points specific to each provider
Red flags in proposed terms identified by contract veterans

AI Platform Coverage

Every Major Enterprise AI Provider, Benchmarked

Our dataset covers all enterprise AI platforms with meaningful Fortune 500 deployment. Pricing data updated as new contracts are submitted.

Platform	Key Products	Enterprise Tier	Typical Discount vs. List	Coverage
OpenAI	GPT-4o, o1, o3, GPT-4 Turbo	Enterprise API + ChatGPT Enterprise	18 to 38%	Full
Anthropic	Claude Opus 4, Sonnet, Haiku	Enterprise API + Claude for Enterprise	15 to 35%	Full
Google (Vertex AI)	Gemini Ultra, Pro, Gemini 1.5	Vertex AI Enterprise + Workspace AI	20 to 45%	Full
AWS Bedrock	Titan, Claude on Bedrock, Llama on Bedrock	Enterprise Discount Program + EDP	Varies with EDP	Full
Azure OpenAI Service	GPT-4o, o1, DALL-E 3	Enterprise Agreement + PTU	Bundled with EA	Full
Databricks	DBRX, Mosaic AI, Foundation Model APIs	Enterprise Platform	22 to 40%	Full
Cohere	Command R+, Embed, Rerank	Enterprise API	20 to 42%	Partial
Mistral AI	Mistral Large, Medium, Mixtral	Enterprise API + on-prem	25 to 50%	Partial

Process

How AI Platform Benchmarking Works

From your first inquiry to a signed contract with market pricing, our process is built for enterprise speed and legal protection.

Share Your Proposal Under NDA

Upload your vendor's proposed pricing or submit the proposal link. All submissions are protected by mutual NDA executed within 4 hours.

We Match Your Usage Profile

Our analysts match your token volumes, use case type, industry, and deal structure to comparable enterprise contracts in our dataset.

48-Hour Intelligence Report

You receive a benchmark report with anonymized peer pricing, your relative position, typical discount range, and negotiation talking points.

Negotiate from a Position of Knowledge

Walk into your vendor meeting knowing exactly what you should pay. Our clients consistently open negotiations 15 to 30 points below what vendors initially propose.

"We were about to sign a $4.2M three-year Azure OpenAI commitment. ISVCOSELL showed us comparable organizations were paying 28% less. We pushed back, vendor blinked, and we saved $1.1M over the contract term. The benchmark report was the single most valuable thing we brought into that negotiation."

VP of Engineering, Global Insurance Carrier (Fortune 500)

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Decision Framework

Key Factors in Enterprise AI Platform Selection

Pricing is one dimension. Our benchmark reports also surface contractual and operational factors that vary significantly across vendors and affect total cost of ownership.

Commercial Factors We Benchmark

Effective per-token cost at your committed volume
Overage rates and burst capacity pricing
Minimum commitment vs. actual enterprise usage patterns
Year-over-year price escalation clauses
Model deprecation protection and pricing continuity
On-premises or VPC deployment premium
Fine-tuning and custom model training costs

Contractual Terms We Flag

IP ownership of outputs and fine-tuned models
Data retention and training data opt-out provisions
Uptime SLA and credit structures
Termination for convenience clauses
Audit rights and SOC 2 / ISO 27001 coverage
Most-favored-nation pricing protections
Exit provisions and data portability

Explore Further