Case Study — Fintech • Revenue Operations
How the Right Salesforce Implementation Partner Rescued a Bleeding Lead-to-Cash Process
A 140-person B2B fintech had been live on Salesforce for 18 months. Pipeline was healthy on paper. Cash collected was not. Every handoff from marketing to sales to billing introduced a new place for revenue to vanish. This is the story of how we found it, fixed it, and proved it.
38%
Pipeline-to-Cash Gap Closed
14 Days
Avg. Quote Cycle Reduction
6 Weeks
Full Rescue Sprint Duration
3 Objects
Custom Objects Deprecated
What Is a Salesforce Implementation Partner?
A Salesforce implementation partner is a certified consulting firm that designs, deploys, and optimizes Salesforce environments for specific business outcomes. Unlike generalist IT vendors, true implementation partners own data architecture decisions, automation governance, and cross-cloud integration — not just license activation. They are accountable for pipeline and revenue impact, not just go-live dates.
The Situation: 18 Months Live, Revenue Still Leaking
Client Profile • B2B Fintech SaaS • 140 Employees • $18M ARR
The client — a payment infrastructure SaaS serving mid-market retailers — had gone live on Salesforce Sales Cloud and CPQ 18 months prior. The original implementation was completed by a generalist consultancy that treated it as a ticket-closure project, not a revenue architecture engagement.
By the time their VP of RevOps reached out to TeraQuint, three symptoms had compounded into a crisis:
⚠ Three Compounding Failure Signals
- ✗Opportunity data was contaminated. Sales reps had built three competing workaround fields to track deal stage because the original Stage picklist was never aligned to actual buying process milestones. Forecast accuracy was fiction.
- ✗CPQ quotes were not activating contracts. A logic gap in the CPQ-to-Contract automation meant that roughly 30% of closed-won deals required manual intervention before billing could begin. Finance had a full-time headcount dedicated to this patch job.
- ✗No attribution between marketing spend and revenue collected. Lead source was populated in fewer than 40% of Opportunities. Marketing was flying blind and could not justify budget to the CFO.
The company had already attempted two internal remediation sprints. Both stalled. The internal Salesforce Admin was capable, but the scope required architect-level decisions — object model redesign, Apex trigger refactoring, and CPQ pricing rule reconstruction — none of which were within the admin's mandate or expertise.
This is the exact pattern we see at TeraQuint when a company needs a qualified Salesforce implementation consultant focused on risk mitigation, not another round of DIY firefighting.
Revenue Audit — Fast
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Salesforce Implementation Partner Diagnosis: What the Audit Revealed
Before writing a single line of code or clicking a single Flow element, TeraQuint ran a structured technical audit across four dimensions. This is standard practice for any Salesforce implementation partner operating at architecture level — not sales methodology theater.
1. Data Model Integrity Scan
We exported the full object schema and ran a dependency map. The findings were stark: 11 custom objects had been created to solve problems that standard Salesforce objects — Opportunity, Contract, Order — were already designed to handle. This object sprawl created N+1 query patterns in key Flows and was causing governor limit warnings in peak usage windows.
The root cause was a decision made in week one of the original implementation: the prior vendor had mapped the client's internal terminology directly to custom object names instead of normalizing it to the Salesforce data model. This created short-term familiarity but long-term architectural debt that compounded with every new automation built on top.
2. Automation Layer Forensics
We catalogued every active automation: 34 Flows, 9 legacy Workflow Rules (never migrated), 4 Process Builders (also legacy), and 3 Apex triggers. Critically, no automation governance documentation existed. Nobody could tell us the execution order with certainty.
Automation Conflict Example Found
A Record-Triggered Flow on the Opportunity object was firing on Stage change to update a related Custom_Deal__c record. A separate Apex trigger on Custom_Deal__c was then attempting to update the parent Opportunity — creating a circular DML loop that was silently failing and rolling back transaction commits under specific field value conditions.
⚠ This was causing approximately 30% of CPQ quote activations to fail silently — the exact symptom the finance team had been patching manually.
3. CPQ Configuration Review
The CPQ configuration had been set up with price rules that referenced product codes directly rather than Product Family or custom product attributes. When the client's product catalog expanded (from 12 SKUs to 41 SKUs over 18 months), the existing price rules became unreliable — some firing, some not, depending on which path through the quote flow a rep took.
Additionally, the Quote-to-Contract object synchronization had not been configured for the Contracted Price object. This meant that every activated contract required a sales rep to manually re-enter pricing terms that should have flowed automatically from the approved quote. The average time lost: 2.5 hours per deal.
4. Lead-to-Opportunity Attribution Gaps
Lead Source was a single-value picklist with 22 options, many of which were deprecated channel names from two years prior. Campaign influence had never been activated. The UTM-to-Lead mapping from their marketing automation platform (HubSpot) was only capturing first-touch source — and only when the sync happened within a 24-hour window, which it frequently did not due to a batch sync misconfiguration.
The result: marketing was unable to demonstrate which programs drove revenue. Budget decisions were being made on feel, not data. For a company at $18M ARR trying to make a Series B case, this was a material problem.
The Rescue Sprint: What a Real Salesforce Implementation Partner Does Differently
Our Salesforce Rescue Sprint is structured as a six-week, outcomes-first engagement. We do not bill by the hour and we do not pad scope. Every workstream maps to a measurable revenue outcome agreed upon in week one.
For this client, the sprint was organized across four parallel workstreams:
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Data Model Rationalization (Weeks 1–2)
We deprecated 3 of the 11 unnecessary custom objects and mapped their field data back to standard Opportunity, Contract, and Product objects. For the 8 objects where business logic was genuinely custom (fintech-specific regulatory fields, payment terms metadata), we retained them but rebuilt their lookup relationships to reduce query depth. Schema changes were deployed to a full sandbox, validated against a production data clone, and migrated via a scripted data loader sequence — not ad-hoc point-and-click.
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Automation Governance Reconstruction (Weeks 2–3)
All 9 Workflow Rules and 4 Process Builders were migrated to Record-Triggered Flows with proper before-save vs. after-save separation. The circular DML conflict was resolved by refactoring the Apex trigger to use a static flag pattern preventing recursive execution. We documented the full automation execution order and embedded it as a Salesforce custom metadata record — making it queryable, not just a PDF in a shared drive.
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CPQ Price Rule and Quote-to-Cash Rebuild (Weeks 3–5)
Price rules were rebuilt using Product Attributes and Product Rules rather than hard-coded product code conditions. This made the configuration catalog-agnostic — new SKUs could be added without breaking existing quote logic. The Contracted Price sync was configured and tested across 12 deal scenarios. By end of week five, quote-to-contract activation required zero manual finance intervention in 97% of test cases.
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Attribution Infrastructure Build (Weeks 4–6)
We replaced the single-picklist Lead Source with a structured Campaign Influence model using Salesforce's native First Touch, Last Touch, and Even Distribution attribution models in parallel. The HubSpot sync was reconfigured from batch (24-hour delay) to near-real-time via webhook with a fallback batch job for failed records. UTM parameters were mapped to five discrete Campaign Member fields, enabling true multi-touch attribution for the first time.
The full sprint methodology — including our governance framework for deciding between Flow, Apex, and OmniStudio — is detailed in our engagement methodology.
Salesforce Implementation Partner vs. In-House Admin: The Real Difference
This engagement made the distinction viscerally clear. Here is how the two approaches compare at the problem-type level this client faced:
| Problem Type | Salesforce Implementation Partner | In-House Admin |
|---|---|---|
| Circular DML / Governor Limits | Diagnoses root cause; refactors Apex with proper bulkification and static flag patterns | Escalates to Salesforce Support or waits for an Apex developer; typically months of delay |
| CPQ Price Rule Architecture | Rebuilds configuration for catalog scalability; separates price rules from product-specific hard-coding | Patches individual rules per SKU; creates maintenance debt with every catalog addition |
| Cross-Object Attribution Modeling | Designs multi-touch model with webhook sync and fallback batch logic; tied to revenue outcomes | Adds fields; rarely configures Campaign Influence; attribution remains incomplete |
| Data Model Redesign Under Load | Runs production data clone in sandbox; scripted migration with rollback plan; zero-downtime deployment | Point-and-click changes in sandbox; often skips production validation; risks data integrity in migration |
| Stakeholder Accountability | Contracted to outcomes: pipeline gap closed, quote cycle reduced, attribution active | Accountable to ticket closure; rarely empowered to block architectural decisions |
The in-house admin at this client was highly competent. The issue was never skill — it was scope and authority. When the problems require certified Salesforce consultants with cross-cloud architecture authority, a single admin cannot fill that gap regardless of effort.
Results: Six Weeks to a Functioning Lead-to-Cash Engine
At the six-week mark, we ran a post-sprint measurement against the four KPIs agreed upon at kick-off. The results were documented and presented to the CRO and CFO jointly — because in a lead-to-cash engagement, both functions have to see the impact.
KPI 1
38%
Reduction in Closed-Won deals requiring manual billing intervention — from 30% to 2% within 45 days of deployment.
KPI 2
14 Days
Average quote cycle time reduced from 21 days to 7 days due to CPQ automation reliability and Contracted Price sync activation.
KPI 3
91%
Opportunity Lead Source population rate — up from 38%. Marketing could now run attribution reporting with statistical confidence.
KPI 4
1 FTE
Finance headcount previously dedicated to manual billing patch work was redeployed to forecasting and financial modeling within 60 days.
CRO Statement — Post-Sprint Review
“We had been treating our CRM as a reporting problem. TeraQuint showed us it was a revenue architecture problem. The difference in how they diagnosed it — and how fast they moved without breaking anything — was unlike any vendor relationship we had experienced before.”
Salesforce Rescue Sprint
Is your CPQ-to-cash flow leaking revenue right now?
The Salesforce Rescue Sprint is a six-week, fixed-scope engagement built for exactly this situation.
Why Most Salesforce Implementation Partners Fail the Lead-to-Cash Test
This is our strong opinion, earned from rescue engagements like this one: the majority of failed Salesforce implementations fail because the original Salesforce implementation partner optimized for go-live, not for revenue motion.
Go-live is a milestone. Revenue is the mandate. These are not the same objective, and when a vendor is incentivized to close implementation tickets rather than close the gap between CRM activity and cash collected, the architecture suffers in predictable ways:
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Custom objects over standard object extension.
New terminology gets new objects. Standard objects with layout customization and field sets would have served the same purpose with 80% less technical debt. The platform already has a
Contractobject. Use it. -
No automation execution order documentation.
When nobody can tell you the order in which automations fire on a given object, you do not have a CRM implementation. You have a liability. Every subsequent customization is built on an unknown foundation.
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CPQ as a quoting tool, not a revenue architecture component.
CPQ is not a PDF generator. It is the connective tissue between your sales motion and your billing system. When it is configured without Contracted Price sync, subscription amendment logic, and renewal automation, you have paid for an expensive quoting template — not a revenue engine.
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Integration sync timing treated as a checkbox.
Whether your marketing automation platform syncs to Salesforce in real-time or in 24-hour batches is not an IT preference — it is a decision with direct revenue attribution consequences. Treating it as a default setting is architectural negligence.
We have documented these failure patterns in detail. If you are in the process of evaluating vendors, our guide on defining deliverables for an enterprise Salesforce implementation service gives you a framework for holding any partner accountable before the contract is signed.
You should also read our companion case study on how we rescue broken Salesforce implementations in fintech to see how this pattern repeats across the industry vertical.
What a Salesforce Implementation Partner Built for the Long Term Looks Like
Beyond the immediate rescue, TeraQuint left the client with three durable architectural improvements that compound in value over time — not just a cleaner org for today.
Automation Governance Registry
Every active automation is now catalogued in a custom metadata type called Automation_Registry__mdt with fields for: triggering object, trigger type (before/after/scheduled), execution order priority, owning team, last reviewed date, and business justification. Any new admin or developer can query this table before adding a new automation. No more guesswork.
Scalable CPQ Product Architecture
The rebuilt Price Rule structure uses a combination of Product Attributes and Summary Variables that can accommodate up to 200 SKUs without requiring rule changes. The client's product team can now add new payment products with a configuration checklist that takes 45 minutes — not a CPQ consulting engagement.
Multi-Touch Attribution Dashboard
The marketing team now has a native Salesforce dashboard showing Campaign Influence across First Touch, Last Touch, and Even Distribution models simultaneously. They can filter by ARR segment, product line, and time period. The CFO accepted this as the source of truth for marketing ROI reporting — removing the need for a separate BI tool for that specific use case.
To understand the ROI mechanics of engagements like this, visit our ROI framework — which outlines how we calculate and guarantee impact before a sprint begins.
For a broader view of how we approach Salesforce for financial services organizations, see our financial services industry practice.
Related Reading for Revenue Operations Leaders
Revenue Now. Not Next Quarter.
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The question is how big.
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