Why most onboarding metrics are vanity

Open any PLG dashboard and you will see the same four numbers: signup volume, tutorial completion rate, DAU in week one, and feature adoption counts. They look healthy. They move in the right direction. They rarely predict revenue.

Signup volume tells you marketing worked. It does not tell you whether anyone found value.

Tutorial completion measures whether users clicked through your guided tour. Many power users skip it entirely and convert anyway.

DAU in week one rewards daily habit before you know if the product solves a real problem. A spike in daily logins with zero expansion is a distraction, not a win.

Feature adoption counts inflate when you ship more surface area. Adoption of a feature nobody pays for is not activation.

These metrics are easy to instrument and easy to report. That is exactly why they persist. They are vanity metrics: activity dressed up as progress.

The question is not "Are people using the product?" It is "Did they reach the moment where paying makes obvious sense?"

Time-to-value as north star

Time-to-value (TTV) is the elapsed time from signup to the first moment a user experiences the core outcome your product promises. Not the first login. Not the first click. The first value moment.

Define the value moment

Your value moment must be specific and observable. Examples:

• A sales intelligence tool: first qualified account surfaced with a cited signal
• A collaboration product: first document edited by a second teammate
• An analytics platform: first dashboard shared outside the team that built it

If you cannot name the event in one sentence, you are not ready to measure TTV.

Instrument it

Track the event server-side, not through client-side funnels alone. Client events miss API integrations, background jobs, and users who bypass the UI. The value moment should fire when the outcome actually happened.

Track the TTV-to-conversion curve

Plot median TTV against conversion rate by cohort. You are looking for an inflection: users who reach value within X hours or days convert at Y%. Below that window, conversion drops sharply.

Segment	Median TTV	7-day conversion	Notes
Self-serve SMB	15–45 min	8–15%	Short path, low friction
Team trial	1–3 days	12–22%	Needs second user
Enterprise eval	5–14 days	25–40%	Procurement adds time

Benchmarks vary by category. The shape of the curve matters more than the absolute numbers. If conversion flatlines after 48 hours regardless of TTV, your value moment is wrong.

Activation rate

Activation rate is the percentage of signups who complete your chosen activation event within a defined window (typically 7 days).

The hard part is picking the event.

Criteria for a good activation event

1. Necessary but not sufficient. Users who activate should convert at a meaningfully higher rate. Users who do not activate should rarely convert. If everyone converts regardless, the event is too weak.

2. Achievable in one session. If activation requires a week of setup, you are measuring implementation, not product fit.

3. Precedes the buying decision. The event should happen before pricing page views, sales conversations, or upgrade clicks — not after.

Examples by product type

Product type	Weak activation	Strong activation
CRM	"Created a contact"	"Logged first outbound activity tied to a deal"
Dev tool	"Installed SDK"	"Deployed first change to production"
PLG analytics	"Connected a data source"	"Shared first insight with a stakeholder outside the team"

Run a retrospective on converted accounts. What did they do in the first 7 days that churned accounts did not? That event is your activation candidate. Validate it forward on new cohorts before enshrining it in dashboards.

PQL handoff

Product-qualified leads (PQLs) are users whose in-product behavior suggests they are ready for a sales conversation. The goal is not to interrupt self-serve. It is to offer help at the moment friction or ambition exceeds what the product can resolve alone.

Signals that trigger handoff

Signal	Why it matters
Usage or seat limit hit	Budget exists; expansion is blocked by plan tier
3+ teammates from same domain	Team adoption without a buyer conversation
Gated feature attempted	Intent is explicit; user found a wall
5+ return days in first 2 weeks	Habit forming; worth a check-in
Pricing page views (2+ in 7 days)	Active evaluation, not casual browsing

None of these alone guarantees a deal. Stack them. A user who hit a seat limit, returned five days in two weeks, and viewed pricing twice is a different conversation than someone who only opened the pricing page once.

Handoff discipline

When a PQL fires, sales should know three things: what the user did, what they tried to do next, and what changed since signup. Generic "I noticed you signed up" outreach wastes the signal. Reference the behavior that triggered the handoff.

Expansion revenue signals

Conversion is the first milestone. Expansion — seats, tiers, add-ons — is where PLG economics compound. Track these in days 14–30, when initial activation dust has settled.

Signals worth instrumenting

1. Multi-seat activation within 14 days. More than one active user on the same account before the first invoice. Team pull beats solo hero usage.

2. Integration depth. Connected to two or more systems in the stack (CRM, Slack, data warehouse). Integrations raise switching cost.

3. Power feature repeat use. Not one-off experimentation. Same advanced feature used 3+ times in 14 days.

4. Cross-functional adoption. Users from different departments or roles active in the same account. Broad adoption predicts org-wide budget.

5. Week-over-week usage growth in days 14–30. Flat or declining usage after activation is a churn signal, not an expansion signal.

Signal	Expansion correlation	Typical window
Multi-seat activation	High	Days 1–14
Integration depth	High	Days 7–30
Power feature repeat	Medium–high	Days 14–30
Cross-functional adoption	High	Days 14–45
WoW usage growth	Medium	Days 14–30

Prioritize accounts with two or more expansion signals for CS or sales outreach. One signal is worth monitoring. Two is worth a conversation.

The metrics stack

You do not need twelve dashboards. You need one rhythm.

Review weekly. Act on trends, not daily noise.

Metric	Definition	Target cadence
Median TTV	Signup to value moment	Weekly, by segment
Activation rate (7-day)	% completing activation event	Weekly, by cohort
PQL volume + conversion	Handoffs fired vs. meetings held	Weekly
Expansion signal count	Accounts with 2+ signals in days 14–30	Bi-weekly

Put these four on one screen. When median TTV rises, activation falls — that is a product problem, not a sales problem. When PQL volume spikes but conversion stays flat, your handoff messaging or timing is off.

When to get out of the way vs. start a conversation

Self-serve works when the path to value is short, the buyer is the user, and the price fits a credit card. Human conversation works when accounts are multi-seat, the use case is ambiguous, or usage signals show ambition hitting a ceiling.

Stay out of the way when:

• TTV is below your benchmark and activation is on track
• Single-user accounts with shallow usage patterns
• No PQL signals fired

Start a conversation when:

• PQL stack reaches two or more signals
• Expansion signals appear before first renewal
• Activation succeeded but usage flatlined after day 14

The failure mode in most PLG companies is the opposite: sales reaches out too early (killing self-serve momentum) or too late (after the eval team already chose a competitor).

Bottom line

Vanity metrics keep dashboards green while revenue stalls. The four that matter — median TTV, activation rate, PQL handoff quality, and expansion signals — connect product behavior to revenue outcomes.

Instrument the value moment. Validate activation against conversion. Hand off when behavior stacks, not when a calendar says so. Review weekly, not daily.

SimpL is built for teams that sell on timing, not volume: find the moment, shape the action, skip the noise.