Salesforce often contains the account, activity, case, renewal, and customer context needed to improve CS execution. LCG helps your team identify the right use case, map the required data and process, and design a human-reviewed AI workflow that fits your existing environment.
Most Customer Success teams have more customer data than ever. The problem is that the data rarely turns into consistent action.
Renewal dates are in Salesforce. Risk signals are in notes. Executive relationships are in someone's head. Support themes live in another system. QBR prep happens manually. Expansion signals are inconsistent. Health scores are questioned.
Then AI gets introduced and everyone expects magic.
But AI does not fix broken workflows. It accelerates whatever system already exists.
If your CS motion is inconsistent, AI will summarize the inconsistency faster.
The CS AI Workflow Design Sprint helps you identify where your Customer Success workflow is ready for AI-assisted work, where the foundation is weak, and which use case is actually worth building first.
Where the real CS motion lives
Signs your CS motion is not AI-ready:
AI can do real work in Customer Success, but only when it is attached to the right workflow and a person is reviewing what it produces. The highest-value use cases are not generic chatbots or random prompt libraries. They are practical workflow improvements tied to specific CS execution.
New tier designation and case record type so scaled customers could request a CSM through the portal, gated so customers who still had one never saw it. Proactive lists and CTAs built on real usage signals. Segment retention up 6 to 7 points in year one. Read the three engagements →
The Sprint separates useful AI opportunities from AI theater.
Not another dashboard. Not a generic prompt library. A practical review of where your Salesforce-based CS motion is ready for AI-assisted work and where the foundation needs cleanup first.
This is not a separate audit. It is what the mapping and prioritization steps of the Sprint examine when your CS motion runs on Salesforce, so the workflow we design is grounded in the data and process you actually have.
Same deliverables as any CS AI Workflow Design Sprint, built around your Salesforce data and your CS process.
How your CS motion actually runs today across Salesforce, CSM notes, spreadsheets, and the steps that live in people's heads.
Three to five candidate workflows drawn from your Salesforce-based CS motion, each tied to a specific execution problem.
Every candidate scored on business value, feasibility, data readiness, risk, and adoption likelihood, so the choice is defensible.
An honest read on whether your Salesforce data is clean enough to support the workflow, and what needs cleanup first.
The prioritized workflow designed end to end: trigger, inputs, steps, decision points, outputs, and owners.
A working prompt set with representative outputs your team can review before anything touches production.
Read-only access design, human-in-the-loop checkpoints, data boundaries, and approval path guidance.
Implementation requirements, an ownership map, and a phased plan for what to fix, pilot, and scale.
A leadership-ready presentation summarizing findings, the recommended workflow, and the path forward.
Already running Customer Success in Salesforce? See where your CS motion is ready, or not ready, for AI-assisted work.
Explore the Sprint → Fixed-fee engagement. Practical executive readout. No generic AI consulting.Five workflows that come up in almost every Salesforce-based CS motion. Each one drafts, a person reviews, and the CRM only changes when someone approves it.
AI-assisted workflow that helps CSMs and account teams prepare for upcoming renewals by summarizing account history, risks, stakeholder gaps, support issues, value narrative, and recommended next steps. The CSM starts from a reviewed draft, not a blank page.
AI-assisted workflow that reviews customer context and flags potential churn signals based on CRM activity, health data, renewal timing, account notes, support trends, and engagement patterns. Flags go to a CSM or manager for review. Nothing changes in the CRM without a person deciding it should.
AI-assisted workflow that helps teams prepare stronger QBRs by pulling together customer goals, outcomes, adoption trends, open risks, stakeholder context, and value proof points. The CSM edits a draft instead of building the deck from scratch.
AI-assisted workflow that prepares concise executive-level account briefs for leadership, sponsor meetings, escalations, or strategic customer reviews. Leadership gets consistent account context without relying on CSM memory.
AI-assisted workflow that turns identified account risk into a structured action plan with owners, next steps, customer messaging, and escalation paths. Converts risk identification into coordinated execution with a consistent playbook every time.
The CS AI Workflow Design Sprint is designed for B2B SaaS companies that rely on Salesforce and want to improve retention execution without creating another layer of operational noise.
This engagement is a strong fit if your company:
The CS AI Workflow Design Sprint is a focused fixed-fee engagement with a practical executive readout and a prioritized implementation roadmap. No generic AI consulting. No tool vendor commitments. Just an honest look at where your Salesforce-based CS motion stands today and what a practical first workflow should be.
LCG is not tied to a single AI tool or platform. The focus is not the tool. The focus is the workflow.
Depending on the client environment, workflows may be prototyped using approved tools such as Claude, Salesforce, Slack, spreadsheets, MCP-compatible connectors, or other systems already in use.
Salesforce remains the central customer system of record, while AI is used selectively to reduce manual work, improve account preparation, and turn scattered customer context into better CS execution.
Governance guardrails built in from day one
Salesforce is a specialization, not a separate engagement. Start with the Sprint to identify and design the right workflow. Build it out when the business case is clear.
Map the current process, score candidate AI workflows on value, feasibility, data readiness, and risk, then fully design one implementation-ready, human-reviewed workflow your team can test in its own environment.
Operationalize the workflow inside your approved environment. LCG works alongside CS Ops, RevOps, IT, or your implementation partner, with clear ownership, testing, enablement, and handoff documentation.
The Sprint does not require a new Salesforce implementation or an LCG-hosted platform. LCG evaluates the operating process and data requirements, then helps the client test or implement the workflow inside its approved technology environment.
Book a free 30-minute discovery call. We will walk through your current Salesforce-based CS setup, identify the highest-value AI opportunities, and determine whether a CS AI Workflow Design Sprint is the right next step.
Fixed-fee engagement. No hourly billing surprises. No commitment required for discovery call.