Reviewable import assistant with bulk reimport safety
Build the migration path inside the product with a review step, selective scope choices, and a clean way to delete and rerun the import.
Why this can grow a startup
Switchers trust an importer more when it behaves like a guided workflow instead of a black box. Linear's docs show the pieces that matter: preview the fetched data, choose whether to bring only open work or the archive too, map users, and summarize everything before the run starts. The second trust lever is reversibility. If the import can be deleted in bulk and rerun, the buyer has room to experiment without feeling trapped by one bad attempt.
Source-backed example
Linear says its in-product import assistants retain more data than the CLI route, show review and mapping steps before import, and let teams delete an import in bulk so they can reimport cleanly if needed.
Source details
Source: Linear Docs: Importer · Browse Linear Docs: Importer tactics
Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.
Source discovered: May 29, 2026
When to use it
Use this when Product, Onboarding, Website is relevant to activation, migration, risk reduction and you can run a bounded test with a medium budget.
When not to use it
Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.
How to do it
- Choose one target segment and define the exact next action this tactic should prompt.
- Adapt the tactic to Product and Onboarding, using evidence from Linear Docs: Importer as context—not as a promised result.
- Record a baseline for: Share of target users completing the product's first-value action. Set a guardrail that would make you pause the test.
- Run a narrow pilot and choose a test window that fits the normal decision or use cycle; do not scale before you have observed the full cycle.
- Compare the signal with its baseline. Scale only if the intended action improves without crossing the guardrail; otherwise revise one variable or stop and record what you learned.
Compare a stack for your situation
Compare source-backed tactics against your product, stage, budget and channel strengths, then choose one experiment to test.
Explore the context
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Apply this with an operator
Choose product surfaces that compound distribution without hiding weak activation or retention.
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