Implementation worksheet · 6 min read
A User Onboarding Software Evaluation Scorecard
Score candidates 1-5 on seven weighted criteria: implementation effort in your actual codebase, targeting depth (segment, behavior, lifecycle stage), experience quality on your real UI (not the tool's gallery), analytics that answer 'did onboarding cause activation', performance cost on load, maintenance burden when your UI changes, and price at your MAU. Weight before trialing; score only from a build in your own product.
Onboarding tools demo beautifully on their own marketing sites and diverge wildly inside real products with real DOM complexity, real routers, and real design systems. The scorecard forces the evaluation to happen where the tool will actually live.
Put it into practice
1. Define one real flow as the fixture
Your actual activation path — say, connect-data-source then invite-teammate then first-report. Every tool builds this flow in your staging app. Gallery flows prove rendering, not fit.
2. Weight the seven criteria first
Sum to 100 before any trial. An engineering-strapped team weights implementation and maintenance; a targeting-hungry growth team weights segmentation. Weights after demos are vendor-authored.
3. Build the fixture in each tool
Time it honestly, including the parts that fight your router or shadow DOM. Note what needed engineering versus what marketing shipped alone — that split is criterion one and six at once.
4. Measure the performance tax
Bundle size added, script blocking time, CLS on tour launch. Run your existing performance suite with the tool on and off; onboarding that slows first paint costs more activation than it adds.
5. Score causally, not cosmetically
The analytics criterion asks one question: can the tool show flow-completion versus activation with a holdout or at least a clean cohort split? Completion rates alone measure tour theater.
Onboarding software scorecard
Copy this structure into your review document and record your observed result for each row.
| Criterion | Weight | Tool A | Tool B | Evidence |
|---|---|---|---|---|
| Implementation effort (fixture) | 20 | timed build log | ||
| Targeting depth | 15 | fixture variants built | ||
| Experience on your UI | 15 | staging screenshots | ||
| Causal analytics | 20 | holdout capability | ||
| Performance cost | 15 | perf suite delta |
A failure worth checking
The template-gallery failure: scoring experience quality from the vendor's polished template gallery instead of the fixture in your app. Galleries are rendered on ideal DOMs the vendor controls. Your app's modals, z-index stack and design tokens are where tours actually break — and where the score belongs.
Common questions
Build or buy — when does this scorecard say build?
When implementation effort for every candidate scores worse than your team building the three patterns you actually need on a library like PLG OS. The scorecard produces that comparison honestly if you add 'build on component library' as a candidate column.
How long should the evaluation take?
One fixture-build day per tool plus a debrief — under two weeks for three candidates. Longer usually means the fixture was too big; shrink it to the single flow that defines activation.
Basis and scope
This is a proposed implementation method using illustrative examples, not a measured benchmark or a customer case study. Prepared with AI assistance. Validate product-specific behavior against current documentation and your own test environment.