Close Deals Faster with these 5 Quote-to-Cash Fixes

Here Are the Key Takeaways:

The Three Questions Every Revenue Leader Should Be Asking

How long does it take you to get a quote out? Where does the process break down across Configure Price Quote, Contract Lifecycle Management, Customer Relationship Management, and billing? And how much revenue are you leaking at renewals, where existing customers quietly disappear because no one was watching the date? 

If you can't answer those quickly, the next 51 minutes are for you. 

What's Slowing Your Deals Down — and Where the Fixes Land

The problems are consistent across industries. Pricing complexity slows everything down when rules live in spreadsheets and approvals happen over email. Slow quoting reduces win rates because buyers move fast, and the team that gets there first often wins. Revenue leakage happens when product and pricing data doesn't flow cleanly into contracts and billing; undercharging is almost never flagged by the customer. And legacy tools make all of it worse, creating gaps between systems that should be talking to each other. 

Fix 1: Standardize Pricing in a Single System

For a global software company with more than 8,000 customers across 90 countries, years of growth and multiple acquisitions had left pricing logic scattered across spreadsheets and undocumented workarounds. The product catalog had ballooned to thousands of SKUs with overlapping and outdated rules. Finance had no real-time visibility into margin. 

Forsys ran a 360-degree system health assessment using their AssessIQ tool, an X-ray of the company's Conga CPQ environment. It mapped every pricing rule, surfaced hidden loopholes, and flagged custom logic that could be replaced by out-of-the-box functionality. The result: a re-architected catalog where every seller works from one source of truth, simplified approval thresholds across regions, and real-time margin visibility for leadership. 

The hard part isn't the tool. It's the data, the rules, and the process cleanup underneath. 

Fix 2: Automate Quote Generation End-to-End

A telecom company's legacy CPQ license was about to expire, their quoting data was scattered across systems, and the business couldn't stop to wait for a migration. The move involved more than 13,000 products, 11,000+ quotes, and nearly 2 million assets — all while reps kept quoting. 

The fix: a four-week assessment to map current state, a phased roadmap to retire the legacy system ahead of the deadline, Oracle ERP integration, and multi-currency quoting, all live in Conga CPQ before the license expired. Quotes that once required manual assembly now generate automatically. 

Zero-touch quoting is the end state: a rep selects products at standard pricing, and the document goes out without any manual handoffs. The customer gets it faster. The rep never opens Excel. 

Fix 3: Stop Treating Renewals as an Afterthought

It costs five times more to acquire a new customer than to keep an existing one. And yet, most companies don't have a system that automatically flags an upcoming renewal, let alone one that surfaces usage data, signals churn risk, or enforces the 3% uplift clause sitting unactioned in every contract. 

The fixes are straightforward once the right data is flowing: automated 60–90 day triggers, self-service renewal paths for lower-touch accounts, usage and entitlement tracking to surface up- and down-sell signals, and automated billing handoff so invoices go out the moment the deal closes. None of it requires reinventing the process. It requires systems that talk to each other. 

Fix 4: Connect Your Sales Tech Stack

For a complex global sales organization, the problem wasn't any single system, it was what happened between them. Contract requests came through Slack, email, and personal messages to legal. There was no way to track cycle time, prioritize requests, or see where deals were stalling. 

Forsys digitized contracting end to end on Conga CLM: contract requests automated, signature workflows standardized, and reporting built so leadership could see deal velocity and risk in real time. The data revealed something worth knowing: the bottleneck wasn't always internal legal. Often it was the other side. Visibility makes that actionable, so you can follow up proactively instead of waiting for silence. 

Fix 5: Where Ai Actually Moves the Needle

AI is worth pursuing only if the underlying process is solid. Throwing it at a broken workflow just speeds up the chaos. 

With a clean foundation, the opportunities are real. Price optimization — machine learning and predictive models, not generative AI — surfaces each customer's price elasticity and guides reps toward the optimal price. Industry benchmarks put that at 1–4 percentage points of revenue to the bottom line. Conversational AI means a rep can ask the system to build a quote, and it handles approval routing and document generation automatically. Approval guidance tells reps what discount level will clear before they submit. Cross-sell signals surface available promotions in context. 

On the contract side: AI that extracts metadata, flags clause deviations from standard, and identifies risk across third-party paper. A $1,000 pricing gain matters. An unreviewed limitation of liability matters more. 

The Takeaway 

Five gaps. Five fixes. The companies closing them have stopped treating CPQ, CLM, and billing as separate problems and started connecting them as one process. Watch the full recording for the case studies, the Q&A, and where to start.