SAP C4C to V2 Migration: A Strategy That Doesn't Break Your Business

SAP Cloud for Customer (C4C) served companies well for years. But its time is running out. SAP has stopped major feature development. Mainstream maintenance has a fixed end date. And with 91% of customer service leaders reporting executive pressure to implement AI in 2026 (Gartner, 2026), the gap between what C4C can do and what V2 delivers grows every quarter.

For organisations still on C4C, the question isn’t if — it’s how. And the “how” makes all the difference.

TL;DR: C4C is reaching end of life while 91% of service leaders face AI mandates that only V2 supports (Gartner, 2026). V2 isn’t an upgrade — it’s a rebuild on BTP with a different data model, APIs, and extension framework. Our 5-phase strategy (assess → integration redesign → parallel build → data migration → adoption) takes 6–10 months for mid-size teams. Rushing leads to broken integrations and budget overruns. Start with a full inventory and realistic timeline.

Why Isn’t V2 Just an Upgrade?

Gartner predicts that by 2029, agentic AI will autonomously resolve 80% of common customer service issues without human intervention (Gartner, 2025). C4C can’t support any of that. V2 was built from scratch on BTP and HANA Cloud to enable exactly these AI capabilities.

What this means in practice:

• Data model: different. Custom fields, business objects, and extensions don’t carry over automatically.
• APIs: different. Every integration built on C4C OData services needs a full rebuild.
• UI: different. The interface is entirely new — role-based and modern.
• Extensibility: different. C4C used key-user tools and an SDK. V2 uses BTP services — more flexibility, but different skills.

Companies that treat V2 as a version upgrade hit problems fast. We’ve seen it at multiple customers. For a detailed feature-by-feature comparison, see our Service Cloud V2: What’s Different guide.

Why Does Strategy Matter More Than Speed?

When SAP announces end-of-life timelines, the instinct is to rush. Deloitte’s 2026 survey found that only 33% of AI initiatives are meeting ROI expectations (IBM, 2025) — and hasty migrations are a big reason why. Speed without strategy leads to:

• Broken integrations that nobody mapped before the switch
• Lost business logic buried in C4C custom code, never documented
• User frustration because the new UI looks nothing like the old one
• Budget overruns because rework costs more than planning — every time

The right approach starts with a full inventory. Every custom field, every workflow rule, every integration, every report — catalogued and evaluated. Not all of them belong in V2. Some were workarounds that V2 handles natively. Others are obsolete. The ones that matter deserve a clean rebuild, not a hasty port.

What Does a Solid Migration Look Like?

SAP now provides a Readiness Check Tool (RCT) and Data Transfer Tool (DTT), with major enhancements in the 2508 and 2511 releases (SAP Community, 2025). These tools help, but they don’t replace strategy. Here’s the 5-phase approach we’ve refined through hands-on work.

Phase 1: Assessment and discovery (2–4 weeks)

Catalogue everything in the existing C4C environment: configurations, custom objects, integrations, reports, user roles, workflow automations. Classify each item as:

• Migrate — needed in V2, rebuild in the new model
• Redesign — needed, but V2 handles it natively (e.g. routing rules → skills-based routing)
• Replace — better alternatives exist in the V2/BTP ecosystem
• Retire — no longer needed or was a workaround

This phase prevents the biggest source of delay: undocumented customisations discovered mid-migration. If nobody remembers why a workflow rule exists, your team spends days investigating.

Phase 2: Integration redesign (4–6 weeks)

Most C4C integrations need a full rebuild. But this is also a chance to improve. V2 connects natively to S/4HANA, SAP Commerce Cloud, and other BTP services — fewer middleware layers, less custom glue code.

Map every integration point. Evaluate V2-native alternatives. Move from point-to-point integrations to V2’s event-driven model via SAP Event Mesh where possible — it’s a cleaner, more maintainable architecture. Define the target architecture before writing a single line of code.

Phase 3: Parallel build (8–12 weeks)

Build V2 while C4C stays live. No big-bang cutover. This lets you test properly, validate migration scripts, and train users before go-live.

Key configuration areas:

• Case lifecycle states and transitions
• Skills-based routing rules and agent skill profiles
• AI classification model training (import historical cases early)
• Knowledge base migration and restructuring
• SLA definitions and escalation rules

Phase 4: Data migration (4–6 weeks)

Historical data — accounts, contacts, opportunities, cases, activities — moves to V2 using SAP’s migration tools. Define mapping rules, run multiple test migrations with production-scale volumes, and set a clear cutover window.

Critical detail: the AI classification model needs real case data to train on. Import historical cases early so the model has time to learn before go-live. Starting with clean data means 70–80% classification accuracy from day one, improving to 90%+ within months.

Phase 5: Change management and training (2–4 weeks)

The UI change alone justifies dedicated training. But it goes deeper — V2 workflows, routing, SLA visibility, and AI features all work differently. Bring key users in during UAT. Deliver hands-on training, not slide decks. Plan for a 2–4 week stabilisation period after go-live.

Freshworks’ 2025 benchmark report (32,000 companies) found that AI-enabled teams see resolution times drop dramatically — but only when agents are properly trained on the tools (Freshworks, 2025). Don’t skip adoption.

What Have Real Migrations Taught Us?

Deloitte’s 2026 Global Contact Center Survey found that 64% of service leaders report higher agent productivity from AI — but only when the implementation is properly executed (Deloitte, 2026). Every migration teaches something. These patterns show up consistently:

Document everything in C4C before you start. The biggest delays come from undocumented customisations discovered mid-migration. If nobody remembers why a workflow rule exists, your team spends days investigating instead of building.

Don’t migrate technical debt. If a C4C workaround was always ugly, don’t rebuild it in V2. Use the migration to clean up. V2 handles many C4C pain points natively — case hierarchies, skills-based routing, SLA automation.

Plan generous time for integrations. They take longer than expected. Always. Every C4C API endpoint changes in V2. If you have 10 integrations, plan for 10 integration rebuilds and budget accordingly.

Invest in user adoption early. The best system fails if people resist it. Start change management on day one, not as an afterthought. Gartner found that 80% of organisations expect to reduce agent headcount in 18 months, but 84% are adding new skills to agent profiles instead (Gartner, 2026). The shift is about upskilling, not eliminating.

Test with real data. Synthetic test data hides problems. Run migration tests with production-scale volumes to catch issues before go-live. The AI classification model especially needs real historical cases — not fabricated test records.

Why Does Your Choice of Partner Matter?

A C4C-to-V2 migration isn’t a standard project. IBM found that only 33% of AI initiatives meet ROI expectations, with 62% of organisations worried about unpredictable costs (IBM, 2025). The partner you choose directly affects which side of that statistic you land on.

A partner who only knows V2 misses the quirks of your C4C setup. A partner who only knows C4C can’t design the V2 target state properly. You need a team that understands both platforms — the one you’re leaving and the one you’re moving to.

What to look for:

• Hands-on C4C experience — knows the old data model, API quirks, and extension patterns
• Proven V2 builds — has delivered real V2 environments, not just attended SAP courses
• Integration skills — can redesign integration landscapes across S/4HANA, BTP, and third-party systems
• A repeatable method — follows a structured process, not ad-hoc guesswork
• Change management ability — handles the human side, not just the technical one

For more on what separates effective SAP CX partners from the rest, see our guide on how to choose an SAP CX partner.

Why Not Wait Another Quarter?

SAP moved from Niche Player to sole Challenger in the 2025 Gartner Magic Quadrant for CRM Customer Engagement Center, driven by its AI-first strategy and Joule copilot (CX Today, 2025). All of that momentum is in V2. C4C gets none of it.

Every quarter you wait:

• V2 pulls further ahead with AI capabilities (classification, sentiment, Joule Agents)
• SAP Jam Collaboration — part of the V1 bundle — sunsets January 1, 2027 (Acorel, 2025)
• Your C4C technical debt accumulates, making future migration harder
• Your competitors gain the productivity advantages you’re delaying

But rushing is worse than waiting. A clear strategy, a thorough assessment, and realistic timelines turn the migration from a risk into an improvement.

For a detailed walkthrough of the migration process for service teams specifically, see our Service Cloud V2 migration guide.

FAQ

How long does a C4C-to-V2 migration take?

For mid-size organisations (50–200 agents): 6–10 months across five phases. Smaller environments (under 50 agents) can complete in 4–6 months. Complex setups with heavy customisation take 10–14 months. Integration rework consistently takes longer than estimated — budget generously.

Can we run C4C and V2 in parallel?

Yes — and you should. Building V2 while C4C stays live lets you test, validate data migration scripts, and train users before cutover. We recommend a minimum 8–12 week parallel period during the build phase.

What happens to our C4C integrations?

Every C4C integration needs review and likely a full rebuild. V2’s API endpoints and data model are different. However, V2’s native connectors to S/4HANA and BTP services are stronger than C4C’s equivalents, so some integrations actually become simpler. The shift to event-driven architecture via SAP Event Mesh is also an improvement.

Do we need new skills for V2?

V2 extensions run on SAP BTP using Node.js, Java, or SAP CAP — not C4C’s retired PDI/SDK. If your team lacks BTP experience, plan for training or partner with a team that has proven V2 delivery experience.

Is there an official C4C end-of-life date?

SAP has not published a specific end-of-maintenance date for C4C. However, the direction is unambiguous: all new AI capabilities are V2-only, V1 releases increasingly focus on migration tooling rather than new features, and key V1 dependencies like SAP Jam sunset January 1, 2027. This creates de facto urgency even without a formal deadline.