Time to Value: The 5-Minute Rule for SaaS
Loom: 30 seconds to first video. Calendly: 2 minutes to first booking link. Grammarly: seconds to first correction. The faster users reach value, the more likely they convert. Best-in-class PLG products deliver time to value (TTV) in under 5 minutes.
The TTV-Activation Connection
| TTV Range | Typical Activation Rate |
|---|---|
| <2 minutes | 40-60% |
| 2-5 minutes | 25-40% |
| 5-15 minutes | 15-25% |
| >15 minutes | <15% |
Industry benchmarks1
What is time to value?
Time to value (TTV) measures how long it takes a new user to experience the core benefit of your product. It’s the gap between “I signed up” and “I get it.” TTV is the single biggest predictor of activation, and activation is where 40-60% of product-led growth signups are lost.3
TTV Variants
| Variant | Definition | Example |
|---|---|---|
| Time to Basic Value (TTBV) | Time to first meaningful interaction | Loom: Recording first video |
| Time to Exceeding Value (TTEV) | Time to “I can’t live without this” | Loom: Sharing video and getting views |
Framework: ProductLed4
The distinction matters. TTBV gets users through the door. TTEV keeps them. Most companies measure neither.
What is a good time to value for SaaS?
The 5-minute rule: Best-in-class product-led growth products deliver meaningful value within 5 minutes of signup. Every minute added to TTV decreases activation rates.4
TTV Benchmarks by Product Type
| Product Type | Target TTV | Example |
|---|---|---|
| Consumer tools | <1 minute | Grammarly (seconds) |
| Productivity SaaS | 1-5 minutes | Loom, Calendly, Canva |
| Collaboration tools | 5-15 minutes | Slack, Notion |
| Complex B2B | 15-60 minutes | Datadog, Amplitude |
Benchmarks compiled from ProductLed, OpenView41
Company TTV Examples
| Company | TTV | How They Achieve It |
|---|---|---|
| Grammarly | Seconds | Browser extension shows corrections immediately |
| Loom | 30 seconds | One-click recording, no configuration |
| Calendly | 2 minutes | Pre-built templates, calendar auto-connect |
| Canva | 2-3 minutes | Template-first design, no blank canvas |
| Zoom | 3-5 minutes | Join meeting with single click |
The 6 TTV Fixes (and What They Kill)
Reducing TTV isn’t about cutting features. It’s about removing friction between signup and value. Each fix targets a specific killer.
TTV Problems and Solutions
| TTV Killer | Impact | Fix | Example |
|---|---|---|---|
| Premature verification | 10-30% user loss4 | Verify after value, not before | Shopify removed verification → 20% MRR increase4 |
| Blank slate syndrome | Confusion, abandonment | Pre-configure defaults | Calendly pre-creates 30-min meeting type |
| Feature tours | Impatience, skip-through | Progressive disclosure | Show only what’s needed now |
| Mandatory profiles | Friction, false data | Reduce signup fields | Each field cuts completion 10-15%6 |
| Integration requirements | Complexity, abandonment | Defer to after first value | Let users experience core value first |
| No guidance | Users don’t know where to start | Guide to one action | Loom: “Record your first video” only |
Feature tours feel helpful but often hurt. Users don’t want a tour of the building. They want to use the bathroom. Get them to value first, tour later.
The DAD Test
Apply this to every onboarding step4:
- Delete: Can you remove this step entirely?
- Automate: Can the system handle this without user input?
- Delegate: Can you defer this to after value is delivered?
Signup Field Impact
| Fields | Typical Completion |
|---|---|
| 1 (email only) | 80-90% |
| 2-3 fields | 60-70% |
| 4-5 fields | 40-50% |
| 6+ fields | <30% |
Run the DAD test on your signup form first. Most teams find 2-3 fields that can be deleted or deferred.
Audit Your Current TTV
- Sign up for your own product (use a new email)
- Time every step from landing page to aha moment
- Categorize each step: Delete, Automate, or Delegate
- Calculate what percentage of steps actually deliver value
Most teams find that 60-70% of their onboarding steps can be eliminated or deferred.
Calculating Time to Value
TTV isn’t a single metric. It’s a measurement framework that depends on what “value” means for your product.
How to Calculate TTV
- 1Define your aha moment: What specific action signals a user "got it"? (See Finding Your Aha Moment if you haven't identified yours yet.)
- 2Identify the timestamp: When did signup complete?
- 3Measure the gap: Time between signup and aha moment action
TTV = Timestamp of Aha Moment - Timestamp of Signup CompleteTTV Measurement Examples
| Product | Aha Moment | TTV Calculation |
|---|---|---|
| Loom | First video recorded | Time from signup to first recording |
| Calendly | First booking link created | Time from signup to link creation |
| Slack | First message sent in a channel | Time from signup to first message |
| Canva | First design exported | Time from signup to first export |
What to Track
| Metric | What It Tells You |
|---|---|
| Median TTV | Typical user experience |
| P90 TTV | Worst-case user experience (the tail matters) |
| TTV by cohort | Whether improvements are working |
| TTV vs. retention | Correlation between speed and stickiness |
When Faster TTV Backfires
Speed without comprehension creates churn. Users who hit “value” but don’t understand why will leave. Sometimes the learning curve is the feature. Notion’s complexity filters for users who’ll actually retain. The right TTV depends on what you’re optimizing for.
Racing to value can backfire when:
- The aha moment requires context: Some products need users to invest a little upfront to appreciate the payoff.
- You’re filtering for commitment: Requiring a few extra steps can filter out tire-kickers and increase conversion quality.
When Speed Isn’t the Goal
| Situation | Optimize For |
|---|---|
| High-volume, low-ACV | Minimum TTV (speed wins) |
| Complex product, high-ACV | Understood TTV (comprehension wins) |
| Viral/collaborative product | Team TTV (network activation wins) |
Slack deliberately requires users to create a workspace and invite a teammate before the product becomes useful. This adds minutes to TTV but ensures that activated users have the context (a team) needed for retention.
Don’t blindly copy Loom’s 30-second TTV if your product requires team adoption to deliver value. Match TTV optimization to your value delivery model.
Action Items
- Race your own product: Fresh email, stopwatch running. Time from landing page to aha moment. Write down every click, every field, every loading screen. If you get bored or frustrated, your users quit.
- Ship one removal this week: Pick the step closest to signup that doesn’t directly produce value. Email verification? Profile fields? Company size dropdown? Delete it, measure signup completion rate, and keep it gone unless metrics tank.
- Find your 10% disaster: Pull P90 TTV, not median. If your median is 3 minutes but P90 is 45, one in ten users is suffering through something broken. That tail is where you’re losing the most salvageable users.
- Steal from competitors: Sign up for your top 3 competitors today. Time their TTV. What do they skip that you require? What do they defer that you demand upfront? Copy the shortcut that makes you jealous.
- Design the 60-second version: If you had to get users to value in under a minute, what would you cut? Now ask: why aren’t you cutting it anyway? The answer is usually “we’ve always asked for that,” which isn’t a reason.
Footnotes
-
OpenView, “2022-2023 Product Benchmarks Report.” TTV benchmarks and activation rate correlations. ↩ ↩2
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InnerTrends, “SaaS Onboarding Benchmarks Study.” Users completing onboarding are 38% more likely to return after one week. ↩
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Intercom, “The Onboarding Blindspot Report.” 40-60% of users never return after signup. ↩
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Wes Bush, Product-Led Growth: How to Build a Product That Sells Itself, ProductLed Press, 2019. TTV framework, email verification impact (10-30% loss), DAD test methodology, Shopify and Snappa case studies. ↩ ↩2 ↩3 ↩4 ↩5 ↩6
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Canva case study, ProductLed research. Canva reduced TTV by 50% through intent-based onboarding paths. ↩
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HubSpot, “Form Field Conversion Research.” Each additional form field reduces completion by approximately 10-15%. ↩