Redis runs the world's fastest in-memory database, and about 150 of its people hold a quoting role. Its first CPQ made every one of them slower: a clunky interface, long load times, and a backend so rigid that deal desk carried each new rule as a manual workaround while reps rebuilt quotes in spreadsheets. Redis's deal desk replaced those workarounds with codified rules inside DealHub CPQ, and moved the deal conversation into the quote itself. The same team now writes a discount limit, a validation rule or an escalated approval per use case, and ships it in days.
Reps build a quote inside the playbook instead of rebuilding it in a spreadsheet.
Deal desk versions a new approval process itself and commits to a turnaround date.
New reps start quoting without learning the full product catalog first.
Redis had already bought a CPQ once, and the organisation had watched it fail. Its interface was slow, its backend resisted every change, and fixing a data hygiene problem or adding an automation meant an investigation rather than a task. So deal desk absorbed the difference by hand. Every new rule became a manual workaround the team carried itself, reps built quotes in spreadsheets and rebuilt them in the system afterwards, and the deal conversation ran through Slack, email and Chatter with nothing left to audit. By the time Redis went looking for a replacement, the second selection was under real internal scrutiny.
We bought a CPQ once and our own people worked around it. What makes us confident the next one gets used?
Every new rule lands on deal desk as a manual workaround. At what point does that stop scaling?
Our reps are rebuilding quotes in spreadsheets before they touch the system. What is that costing us in errors we never see?
We are rolling out a new pricing phase on a core product, and existing customers need exceptions. Can we allow those without losing the record?
| Before | After |
|---|---|
A new rep needed the product catalog in their head before building a first quote, and leaned on deal desk to get through it. | A new rep answers the playbook's questions and reaches a correct quote on day one, with peers and internal collateral as the only help needed. |
A request for a new approval process started with nobody knowing whether the old backend could do it, or what finding out would cost. | Redis's GTM Systems team versions the change itself and commits to a turnaround date before starting. |
Deal discussions ran through Slack, email and Chatter, so approvals could not be traced and past decisions could not be revisited. | Reps raise the question inside the quote, and deal desk answers the larger share of them without pulling finance or legal into the deal. |
Giving a rep discount latitude meant accepting that the pricing decision would sit outside the system. | Redis's deal desk sets a validation rule or an approval threshold per use case, and every exception it allows stays in the data. |
Deal desk was the route through complex product and pricing logic, which made it the bottleneck on every non-standard deal. | Deal desk holds the middle position it is meant to hold, and stops relaying between sales, finance and legal. |
“That led to a pretty stagnant system. And a lot of the workarounds that we would need to establish would all need to be taken on manually by the deal desk team… a lot of back and forth… either through Slack or email or Chatter…”
Phoenix Moomaw
Director, GTM Systems and Data Operations
Redis's deal desk got a quoting system it could change instead of one it had to work around. Previously, every new rule arrived as a manual workaround the team carried by hand, and the deal conversation scattered across Slack, email and Chatter with no audit trail. Now the rule lives in DealHub CPQ and the conversation lives in the quote.
Redis's go-to-market systems manager, with a team of five or six split between business administration and Salesforce ecosystem development.
Business-owned. Redis's deal desk holds discount limits, validation rules and approval thresholds, and decides per use case which of the two a situation needs.
About 150 of Redis's people hold a quoting role or another role in the platform, and 95% work inside the guided selling playbook.
Salesforce, as the CRM and the surrounding ecosystem Redis's own team develops against.
Redis's GTM Systems team makes pricing and approval changes itself, with no IT or specialist team in the change path. On the previous CPQ the same change took an investigation and, in her words, "a lot of investment".
DealHub is ISO 27001, ISO 27701, ISO 22301, and ISO 42001 certified, holds SOC 1 Type II and SOC 2 Type II attestations, and is GDPR and CCPA compliant, alongside additional security, privacy, and compliance frameworks.
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