At a glance
Meet Watershed
Watershed is the enterprise sustainability platform that helps companies like Walmart, Airbnb, Stripe, and DoorDash measure emissions, report on them and cut them. With multiple product lines and a new AI product to price, Watershed’s Revenue Operations team is responsible for navigating pricing and product complexity while staying lean. To help their systems keep up with how they sell, Watershed came to Roadrunner to uplevel its quote-to-cash operation.
Our pricing model should be what's right for our customers, not determined by the constraints of our pricing system.
The problem
Road to Roadrunner
Pricing wasn’t the only pressure. As Watershed grew, they needed more granular data to drive business decisions: orders and assets that show what each customer bought and how that changes over time. The CPQ they chose had to scale alongside Watershed’s projected growth.
Before Roadrunner, quoting ran on a homegrown setup built with Salesforce Flows. It taught them what quotes and rules they needed, but as Watershed scaled, the setup started to hit its limits:
Where the old setup hit its limits
Quoting ran on a homegrown setup built with Salesforce Flows.
Approvals ran on a manual system through Slack.
Requests and sign-offs lived in Slack threads, separate from the quote.
Discount math was on the rep.
Without calculations against list and sales price, the team lacked visibility into the accuracy of quotes.
Contract changes erased history.
Amendments meant deleting lines in Salesforce, leaving no history of what happened to assets in play.
So Watershed set a clear bar for its next system: built around AI from the start, able to handle complex pricing, and something reps would actually want to use. Nine weeks after kickoff, Watershed was live on Roadrunner.
Three ways Watershed’s RevOps team runs on Roadrunner
Use case 1 · Admin Agent
Own the system in-house
In most CPQ setups, every change is a project. Adding a product, updating pricing or adjusting an approval rule means manual setup, which can take days or weeks before reps can actually quote it. With Roadrunner, Laura’s team can make those changes as fast as the business needs them.
Roadrunner’s Admin Agent is an AI assistant for the people who run the system. Admins describe what they want in plain language, and the agent helps set it up and troubleshoot it. For Watershed, the Admin Agent accelerated things from the start. It helped get pricing, product and approval rules configured quickly during implementation, and it shortened enablement time. Instead of reps and admins learning every technical setting, Watershed’s team could work with the agent in plain language, giving them more control over keeping the system aligned with their business.
An admin asks Roadrunner's Admin Agent to warn reps at 500 Enterprise seats instead of 5,000; the agent changes the rule, runs three draft tests that pass, and marks it ready to publish.
Admin AgentToday, Watershed’s RevOps runs the system end to end: configuring products, adjusting rules and building on top of the system themselves. When a change touches several parts of the system, the Admin Agent configures the update and runs tests to confirm the rules return accurately before the team pushes live.
Use case 2 · Quote Agent
Let reps build complex quotes on their own
As pricing gets more complex, quoting can turn into a bottleneck. Reps wait on RevOps or Deal Desk to get numbers right, or work through the math themselves and hope nothing slips. Roadrunner puts complex pricing in reps’ hands.
A rep describes a three-year deal in plain English; Roadrunner’s Quote Agent builds the priced quote and routes it for approval.
Now Watershed’s reps build their own quotes in plain language, even with a price book full of moving parts, and only bring RevOps in for real issues.
“It just understands our price book and how we usually structure things… We’re talking about going from 10 to 15 minutes [to generate a quote] down to a minute at most.”
That changes what RevOps spends its time on. Instead of answering every question, Laura’s team sets the rules of the road and approvals that hold. The team brought its existing rules into Roadrunner and is now “better at catching all the things that we should have been catching before.” Roadrunner’s approvals are built to keep deals moving, too: reps can see where quotes stand, approvers can review and approve right from the quote, and stuck approvals are easy to find and nudge.
Use case 3 · Roadrunner Data & MCP
Track revenue down to the product
For a company that sells multiple products, the most important planning questions happen at the product level. Which are customers keeping? Which are they dropping, swapping, or adding? With Roadrunner, Laura can dissect retention and expansion and get a more granular view of revenue data down to the individual product, something she says “is just not something that we’ve ever been able to do before.”
Before, Watershed’s reporting stopped at the deal level, which meant that they didn’t have product-level churn data. It was hard to follow a single product across renewals and changes over time. Roadrunner’s unified view of asset periods connects each product’s history from one deal to the next. Laura uses Roadrunner MCP for this product reporting, drilling into product-level churn, attach rates and white space by product.
“So now we can say what’s product churn versus logo churn over time.”
With reports that pivot by date, the team can compare any product across any period, quarter over quarter or year over year, giving them a stronger foundation for annual planning. Beyond reporting, Watershed’s one-person Deal Desk uses the MCP to run conformance checks on deals and build his own tools on top of it, so he can keep up with more deals as the company grows.
