Make better product decisions with the full customer contextMake better product decisions
with the full customer context

Connect feedback to journey steps

Place support themes, customer calls, analytics drops, and roadmap requests on the journey moment where users actually feel the friction.

Start with: A support theme, customer call, analytics drop, roadmap request, or sales note.

Place it: Attach the signal to the stage and step where users feel the friction.

Add evidence: Connect tickets, call notes, recordings, account impact, and current delivery work.

Result: A request like CSV import becomes a setup problem with evidence and outcome context.

Prioritize opportunities by evidence

Compare opportunities by impact, effort, affected persona, linked signals, and the product outcome they should improve.

Group friction: Turn repeated evidence on a step into an opportunity, not an immediate feature request.

Compare by: Journey moment, evidence strength, affected persona, expected impact, effort, owner, and outcome.

Decide: Prioritize the customer problem before choosing the solution shape.

Example: Compare setup failure before value against template-choice confusion, not two disconnected feature ideas.

Keep solutions tied to the problem

Attach solution ideas, specs, issues, and shipped work to the opportunity so delivery never loses the customer context.

Choose solution: Create a solution from the opportunity once the customer problem is clear enough.

Keep linked: Attach the journey step, evidence, owner, outcome, and related opportunity.

Send to delivery: Link the Linear, Jira, or GitHub issue without dropping the customer context.

Result: Design and engineering see the problem behind the requirement before they build.

Review what changed after release

Connect follow-up metrics and new customer signals back to the original journey problem so the team can learn after shipping.

After release: Keep the shipped solution tied to the original journey problem and success metric.

Review signal: Check follow-up metrics, new support conversations, and fresh customer notes.

Decide next: Close, refine, split, or reopen the opportunity based on what changed.

Use it for: Learning whether the fix improved the customer experience, not just whether the issue shipped.

Create issues for high-priority solutions

When a solution reaches high priority, open a linked Linear, Jira, or GitHub issue with the evidence, journey step, and expected outcome already attached.

Trigger: A solution is marked high priority, accepted, or ready for delivery.

Create issue: Open work in Linear, Jira, GitHub, or the team delivery tool.

Include: Customer problem, journey step, insights, affected persona, expected outcome, owner, and Custory link.

Result: Engineering starts from context instead of a thin task title.

Send updates when new insight shows

Notify the right product channel when a new insight lands on a watched journey step, so teams see important context without another status meeting.

Watch: Key journey steps, active opportunities, or product areas that need fresh signal.

Filter: Send only meaningful new evidence, not every small change.

Message: Summarize the insight, source, journey step, linked opportunity, and suggested next action.

Result: Customer learning reaches the team without a PM manually rewriting the update.

Watch activation and retention friction

Pull in signals from analytics, feedback, and support tools when key onboarding, activation, or retention moments start showing repeated friction.

Connect: Analytics, feedback, support, revenue, and product activity sources.

Detect: Find onboarding, activation, or retention signals that point to repeated friction.

Update journey: Create an insight, refresh an opportunity, or ask the owner to review the evidence.

Example: PostHog drop-off and setup tickets land on the same Activation step for review.

Summarize changes before planning

Generate a planning-ready summary of new insights, changed priorities, shipped fixes, and open risks across the product journey.

Run before: Weekly planning, roadmap review, sprint planning, or product review.

Collect: New insights, priority changes, shipped fixes, unresolved opportunities, and open risks.

Grounded in: Journey steps, evidence, owners, statuses, metrics, and linked work already in Custory.

Output: A planning-ready summary of what changed and what needs a decision.

How does Custory help us decide what to build next?

Custory helps product teams compare problems in their customer context. You can see where the problem occurs, who it affects, what evidence supports it, and how it relates to product and business outcomes before deciding whether it deserves roadmap space.

What can Custory show us that analytics cannot?

Analytics can reveal behavior and drop-offs. Custory connects those signals to the customer’s situation, qualitative evidence, product decisions, and the work intended to improve the experience.

How does Custory connect discovery and delivery?

The evidence and reasoning behind a problem remain connected when it becomes an opportunity, solution, or delivery task. Product, design, and engineering can work from the same understanding instead of relying on a condensed ticket.

What is a good first use case for a product team?

Start with a journey that already creates uncertainty or debate, such as onboarding, activation, adoption of a core feature, or an important handoff. The first useful journey should help the team make a current product decision, not attempt to document the entire customer lifecycle.

Is Custory just another feedback tool?

No. Feedback tools collect and categorize what customers say. Custory connects that evidence to the journey moment it explains, alongside behavioral signals, product decisions, and delivery work.

Can we use this with analytics and support data?

Yes. Behavioral data can show where customers struggle, while support and research evidence help explain why. Custory keeps those different forms of evidence connected to the same part of the journey.