isvcosell.com — stages
Co-Sell Stages
Individual process maps. Hyperscaler translations. Databricks on top of the chosen cloud after SOW. Ali Chehab.
Spine
- Productize, earn field trust, win seller acceptance, run joint pursuit, then consume, attribute, and expand.
- Productize the solution
- Build field trust and pipeline
- Earn seller acceptance
- Run the joint pursuit
- Consume · attribute · expand
- Vertical pain becomes owned IP, cloud workload, implementation package, and managed-services path.
- Vertical pain
- Owned IP or accelerator
- Cloud and platform workload
- Implementation package
- Managed-services path
- Partner manager, AE, architect, marketplace and funding, SI sales and delivery stay connected.
- Partner manager
- AE and sales director
- Architect and specialist
- Marketplace and funding
- SI sales and delivery
- Partner-sourced and field-routed opportunities meet in qualification, then a named IP-led pursuit.
- Partner-sourced · accounts · events · CRM · executive network
- Field-routed · referrals · whitespace · RFPs · stalled workloads
- Vertical and technical qualification
- Named IP-led pursuit
- Qualified signal, seller-ready brief, correct owner, explicit give-and-get, accepted next action.
- Qualified customer signal
- Seller-ready pursuit brief
- Correct account owner
- Explicit give-and-get
- Accepted next action
- Wrong owner or duplicate gets rerouted. Weak fit gets strengthened, nurtured, re-scoped, or withdrawn.
- Wrong owner or duplicate
- No access · weak value · small consumption · bad timing
- Reroute or resolve role
- Strengthen · nurture · re-scope · withdraw
- Buyer pain, cloud commit, consumption case, and procurement path collapse into one joint pursuit plan.
- Buyer and pain
- Cloud commit and platform fit
- Consumption and services case
- Decision and procurement path
- Joint pursuit plan
- Internal CRM, hyperscaler record, Databricks record, and customer workload stay linked to the next action.
- Internal CRM
- Hyperscaler record
- Databricks record
- Customer workload and next action
- Sponsor, eligible workload, consumption-backed SOW, measured proof, production decision.
- Qualified customer and sponsor
- Eligible workload and partner
- Consumption-backed SOW
- Measured proof
- Production decision
- Marketplace offer, cloud commit, implementation SOW, and managed services close into production together.
- SI IP or marketplace offer
- Cloud and platform commitment
- Implementation SOW
- Managed-services agreement
- Production-ready close
- Win, deploy, attribute consumption, expand services, earn the next field referral.
- Qualified pipeline
- Joint win and deployment
- Attributed consumption
- Services and expansion
- More field referrals
Cloud translations
- AWS-aligned IP play through AM acceptance, ACE, POC or MAP, private offer, usage and expansion.
- AWS-aligned IP play
- AM acceptance and ACE
- POC or MAP path
- Private offer and SOW
- AWS usage and expansion
- Azure-consumptive IP play through Active Co-Sell, COS, account routing, Partner Center seller, funding, MACC path.
- Azure-consumptive IP play
- Active Co-Sell submission
- COS ops review
- Account team routing
- Seller contact in Partner Center
- Joint discovery and funding
- MACC path SOW and expansion
- Google-aligned IP play through FSR acceptance, registration, pilot or migration, marketplace path, expansion.
- Google-aligned IP play
- FSR acceptance and registration
- Pilot or migration support
- Marketplace path and SOW
- Consumption and expansion
Databricks on cloud
- One business outcome and SI IP yields Databricks usage, hyperscaler consumption, implementation, and managed services.
- Business outcome and SI IP
- Databricks usage
- Hyperscaler consumption
- Implementation services
- Managed services
- Databricks-native IP play through field network, AE acceptance, partner registration, usage, services and expansion.
- Databricks-native IP play
- Field network and AE acceptance
- Partner registration and proof
- DBU or serverless usage
- Services and expansion
- Converged platform and IP sit on Databricks. Databricks sits on the cloud. After SOW, dual consumption and attribution run in parallel.
- Converged Platform
- Artificial Intelligence
- Master Data Management
- Databricks
on top of
- Cloud · AWS · Azure · Google Cloud
- Business Systems
- Integration
- IP Suite Solutions
- Solution and IP, network and pipeline, seller acceptance, consumption and services, then attribution, expansion, referrals.
- Solution and IP
- Network and pipeline
- Seller acceptance
- Consumption and services
- Attribution · expansion · referrals