Revenue Operations & Product Led Growth

PLG is a data problem disguised as a go-to-market strategy. RevOps is the team that turns data into motion, so PLG lives here. If product usage is the new lead source, then every click, invite, and integration is pipeline. Own the telemetry, own the growth.

The backbone: product telemetry with Segment

Telemetry is the system of record for PLG. Segment makes it usable across tools without duct tape.

Event schema that actually tells a story

• User Signed Up with source, plan, geo, referral

• User Logged In with device, version, ip_country

• Team Member Invited with seat_count_before, seat_count_after

• Feature Used with feature_name, count, success_state

• Integration Connected with vendor, api_key_created

• Billing Limit Reached with limit_type, current_value, threshold

• Account Upgraded with from_plan, to_plan, seats

Identity that maps humans to accounts

• Track user_id and anonymous_id, always

• Capture email and inferred domain

• Maintain an account_id for the workspace or org

• Keep a simple deterministic rule for Account, then layer a confidence score for the messy cases

Routing that keeps GTM in sync

• Warehouse first, then HubSpot or Salesforce, plus your analytics tool

• Use Reverse ETL to hydrate CRM with product traits like last_login_at, active_seats, feature_adoption_score

• Push alerts to Slack when key events fire

From telemetry to segmentation

Static ICP is fine. Dynamic IEP, ideal engagement profile, is better. Segment your users and accounts by how they behave, not only by who they are.

Core segments

• Free teams with 3+ active users in 7 days

• Accounts that created an API key but have low usage

• Teams that hit any plan limit in the last 14 days

• Workspaces with executive logins in the last 30 days

• Customers with rapid seat growth week over week

• Feature adopters who used a premium capability 3 times

Each segment maps to a play. No segment, no play.

Clay for de-anoning and deal expansion

PLG creates a people problem. Lots of signups on personal Gmail. You need the company behind the keyboard. Clay helps tie generic emails to real firms so Sales can prioritize the right work.

How to lift Gmail to Account with Clay

• Guess domain from email patterns and social profiles

• Match LinkedIn profile to current company

• Cross-check company site, MX records, and known hiring pages

• Pull firmographic signals, employee count, tech stack, funding

• Produce a confidence score with clear thresholds for auto-attach, manual review, or suppress

Use this to upgrade anonymous usage to account-level insights. Feed the CRM with probable_company, confidence, and linked_profile so humans can validate fast.

Sales-assist triggers that print pipeline

PLG is not “self-serve only.” It is self-serve until a human makes it faster.

Create tasks or sequences when

• Someone invites 3 teammates in 7 days

• An API key gets created

• A workspace hits any billing or usage limit

• An exec persona logs in twice in a week

• A premium feature is used three times by two or more users

• Active seats grow 20 percent week over week

• SSO is enabled

• Data is exported, a leading signal of value realization

These are not vanity alerts. Each one maps to a proven talk track and offer.

Offers that match where the user is

Stop pitching random upgrades. Make the offer fit the moment.

Offer library

• “Minutes pack” or credit top-up when usage spikes

• Seat bundle when invites accelerate

• Integration unlock when the team connects a core tool

• Security add-on when SSO turns on

• Concierge setup when an API key appears but usage is low

• Annual plan with discount when active seats cross a threshold

HubSpot or Salesforce, wired for PLG

Your CRM needs product context on the record, not in a separate dashboard.

Minimum viable model

• Contact: persona, last_login_at, feature_last_used

• Company or Account: active_seats, usage_tier, plan, last_limit_hit, health_score

• Deal: created when an API key appears or a limit is hit, source = Product

• Activities: product events synced as timeline activities with clear verbs

Lifecycle that speaks PLG

• Visitor → Signup

• Activated User → PQL

• PQA when the account crosses an account-level threshold

• Sales Assist when any trigger fires

• Customer

• Expansion

Metrics that matter

You cannot manage PLG with MQLs and hope.

Scoreboard

• Time to first value

• Activation rate by persona and source

• PQL and PQA creation rate

• Self-serve conversion rate

• Seat expansion rate and time to expansion

• Feature stickiness index

• Net revenue retention, with attribution to product triggers

• Payback, by motion self-serve versus sales-assist

Operating rhythm

PLG needs a weekly drumbeat owned by RevOps.

Weekly

• Review segments and trigger volume

• Inspect five deals sourced by product events

• Audit one identity resolution case from Gmail to Company

• Ship one experiment, for example a new limit-based offer or a changed threshold

• Close the loop on fields and schema drift

Monthly

• Refresh the offer library

• Recut the IEP segments

• Publish a one-pager of learnings for Sales, Marketing, and Product

Starter checklist

• Define the event schema and identity rules in a one-page spec

• Instrument the core product events and ship to Segment

• Sync traits to CRM with Reverse ETL, keep it lean

• Build three PQA segments and wire triggers to Slack and CRM

• Stand up Clay enrichment for personal emails with confidence scores

• Create five sales-assist plays with matching offers

• Launch the weekly PLG review and assign owners

• Track activation, PQL, PQA, and expansion in one dashboard

PLG makes RevOps the nerve center of growth. When telemetry flows, identity is resolved, and plays are tied to product moments, you get a steady stream of expansion and clean pipeline. This is how you scale without burning the budget.