Salesforce Software / SaaS global

Perk

Sales Automation

Perk's sales reps were losing valuable selling time to browser-based prospect research, manual qualification, and delayed first outreach, which slowed pipeline creation and reduced the quality of early conversations.

3x increase in call volumes
60% of their pipeline with Prospecting Agent
doubling of email reply rates
setup to launch in just two weeks

Reported impact

Business outcome

Perk increased pipeline generation speed, improved reply and call rates, and shifted reps from manual research work to higher-value prospect conversations and personalized selling.

  • Productivity Improvement
  • Revenue Growth
  • Speed to Market

Solution

Perk implemented Prospecting Agent inside Sales Cloud to remove the shadow work that was slowing its prospecting engine. Instead of forcing reps to jump across browser tabs and research tools, the agent runs continuously inside Salesforce, identifies high-fit accounts against Perk's criteria, and places them into targeted outreach cadences automatically. Perk paired that automation with a human feedback loop so sellers can validate the agent's logic, refine targeting in real time, and build trust in the system rather than treating it like a black box. Each recommended account comes with a concise rationale that explains why the prospect fits, which gives reps warmer starting points for outreach and better-prepared meetings. With research and qualification offloaded to the agent, the team spends more of the day on personalized conversations, pipeline creation, and closing work.

Data flow

Prospecting Agent works inside Sales Cloud to identify high-fit accounts, explain why they match Perk's criteria, and place them into targeted outreach sequences. Reps then review those insights and use the curated lead list to run more personalized calls and meetings.

Solution architecture

2 components · 2 layers
  1. Compute
    • Prospecting Agent Researches, qualifies, and routes high-fit prospects into the right sales cadences.
  2. Serving
    • Sales Cloud Hosts prospect data, outreach workflows, and the operating context for the sales team.

Architecture clues

  • A feedback loop keeps humans in the loop to tune targeting logic.
  • Perk plans to extend the pattern with specialized agents for Travel, Spend, and Events.
  • The agent explains why each suggested prospect is the right fit.

Evidence from the source

"Our reps have shifted from being data researchers to true consultants."
"Perk deployed Prospecting Agent to autonomously handle the heavy lift of prospect research and qualification."
"Perk moved from setup to launch in just two weeks, seeing a 3x increase in call volumes and a doubling of email reply rates in a matter of weeks."
"The agent works 24/7 to identify high-fit prospects based on Perk's specific criteria and automatically places them into targeted email outreach cadences."
Transparency Evidence & methodology 85/100 reference value · 89% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value85/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale0/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Salesforce

    Perk customer story

    First-party
    https://www.salesforce.com/customer-stories/perk/
    Source type
    Vendor-published customer story
    Published
    May 26, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page May 26, 2026 · Salesforce · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.