RevOps Jobs-to-Be-Done
- PQL identification — Score users and accounts based on product usage to identify Product Qualified Leads. KPI: Sales team converts PQLs at 2–3× the rate of MQLs.
- Expansion signal routing — Automatically route upgrade and expansion signals to the right CSM or AE. KPI: Expansion pipeline grows without additional outbound effort.
- Usage-triggered outreach — Trigger personalised outreach when users hit usage limits or adopt key features. KPI: Outreach conversion rates improve due to perfect timing.
Key Features
- PQL scoring: Usage-based scoring model to identify Product Qualified Leads.
- Signal routing: Route expansion and upgrade signals to the right rep with context.
- Product data integration: Connects to Segment, Amplitude, Mixpanel, and data warehouses.
- Playbook triggers: Trigger outreach, tasks, or Slack alerts based on product events.
- CRM sync: Write PQL scores and signals back to Salesforce or HubSpot.
How It Fits Your Stack
Primary system of record: Salesforce, HubSpot
Key integrations: Salesforce, HubSpot, Segment, Amplitude, Mixpanel, Snowflake, BigQuery
Data flows: Product events → Correlated scoring → PQL/expansion signals pushed to CRM and sales tools.
Implementation & Ownership
- Time to first value: 2–4 weeks
- Implementation complexity: Medium
- Typical owners: RevOps, Sales Ops, CS Ops, Growth
Pricing & Contracts
- Pricing model: Annual SaaS subscription
- Indicative range: Custom; typically $15k–50k/year
- Free tier: Yes
Who It's Best For
PLG SaaS companies with self-serve product adoption wanting to layer a sales motion on top of usage signals.
Good fit if:
- Companies with free-to-paid or freemium models
- RevOps teams building PLS workflows to complement PLG
- CS teams wanting to identify expansion without manual monitoring
Probably not ideal if:
- You're purely outbound with no product self-serve
- Your product analytics infrastructure isn't in place yet
Proof & Buyer Signals
Ratings: G2 4.7 / 5 (30+ reviews)
What buyers praise:
- Surfaces real expansion opportunities
- Good product analytics integrations
- RevOps-friendly setup
Common complaints:
- Requires mature product analytics stack
- Custom pricing can be opaque
Pros
- Designed specifically for PLG companies
- Works with existing product analytics tools (Segment, Amplitude)
- Strong CRM write-back capabilities
Cons
- Requires existing product instrumentation to generate value
- Enterprise pricing out of reach for early-stage startups
Often Compared With
- June — June is lighter-weight product analytics; Correlated focuses specifically on routing revenue signals.
