---
title: "Discovery: from insights to opportunities"
canonical_url: https://zentrik.ai/docs/product/insights-to-opportunities
markdown_url: https://zentrik.ai/docs/product/insights-to-opportunities.md
category: "Product guides"
learning_track: "discovery"
last_reviewed: 2026-04-07
---

# Discovery: from insights to opportunities

An **insight** states what you learned from evidence. An **opportunity** groups related insights into **problem or bet space**: what you might address or fund before you pick one solution or open an initiative.

## Overview

This guide is about **opportunities**: shared problem and bet space after you already have **signals** and **insights**. New to the flow? Start with [Evidence → insights](https://zentrik.ai/docs/product/evidence-to-insights) or the full walkthrough [From customer evidence to initiatives](https://zentrik.ai/docs/product/customer-evidence-to-initiatives).

Opportunities give teams one place to **compare bets**, weigh tradeoffs, and decide what becomes an **idea** or **initiative**. Keep **insights** linked so framing stays tied to customer wording.

## When to create an opportunity

Use an opportunity when:

- Multiple **insights** describe the same customer problem, gap, or bet.
- You need a single object for **narrative and evidence** that is larger than one insight but not yet a committed build.
- You want **discussion** before the team names a solution.

You can refine **taxonomy** and **themes** while opportunities mature; keep **insights** linked to **signals** you trust so bet narratives stay auditable.

## Shape opportunity space

In the product, edit **framing**: problem statement, impact, constraints, and links to **insights** and **signals**. Use the graphs, trees, or drafts your workspace provides to compare opportunities and see **where evidence is thin or strong**.

When new signal arrives, add **insights** to an existing opportunity or split if the learning diverges. Treat the record as **current framing**, not a locked slide deck.

## Traceability narrative

A **traceability narrative** is how you turn framing into something the room can inspect: start from the opportunity, describe the problem in your own words, and let Zentrik propose **evidence** from signals and insights already in the workspace. You confirm what belongs, fix weak links, and keep **customer language** attached.

The same flow surfaces how the bet relates to **ideas** on your opportunity tree—so backlog-shaped work stays tied to the evidence chain instead of living only in slide bullets.

See the short demo on this page (below) or read how this fits roadmap culture in [Why flat context isn't enough](https://zentrik.ai/blog/why-flat-context-isnt-enough).

## Ideas and initiatives

**Ideas** are possible solutions, usually refined from opportunities and evidence, still before full delivery commitment.

**Initiatives** are execution: specs, tasks, agents, tracking. When an idea **promotes** to an initiative, the trail back to **signals** and **insights** should stay easy to open so scope debates cite **source wording**.

**Export** (for example [Jira](https://zentrik.ai/docs/integrations/jira)) sends execution-shaped work to another tool. Zentrik remains where you record **why** that work exists.

## Troubleshooting

### Opportunity feels disconnected from evidence

Link **insights** that quote or summarize the customer, then open the **signal** behind them. If the insight layer is thin, bring in more evidence via connectors, bulk imports, or paste—see [Evidence → insights](https://zentrik.ai/docs/product/evidence-to-insights).

## Related guides

- [Bring customer evidence into Discovery](https://zentrik.ai/docs/product/evidence-to-insights)
- [Taxonomy and themes](https://zentrik.ai/docs/product/taxonomy-and-themes)
- [Use Studies to learn throughout an initiative](https://zentrik.ai/docs/product/idea-studies)