> ## Documentation Index > Fetch the complete documentation index at: https://conveo.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Storylines > Run continuous, always-on research that re-analyzes itself on a schedule and tracks how findings change over time **Storylines** (an always-on research program) are different from **Stories** (the collaborative notebook you use to build a presentation from a single study). A Storyline keeps running and re-analyzes itself over time; a Story is something you author by hand. Most studies are one-shot: you recruit a batch of participants, the interviews come in, and you analyze the result once. A **Storyline** is different — it's an always-on research program that keeps recruiting and re-analyzing on a schedule, so you always have a current read on the question you care about and can see how the answer moves over time. Think of it as the difference between taking a single photo and running a time-lapse. Each analysis cycle adds a new frame, and Conveo automatically connects the frames so you can see what's new, what's holding steady, and what's fading. Storylines are built for questions that never really "finish" — brand and category tracking, an ongoing voice-of-customer program, monitoring a rollout, or any research you'd otherwise re-run as the same study over and over. ## How a Storyline works A Storyline has two rhythms: how often it **recruits** participants, and how often it **reports**. * **Recruitment** can be continuous (a steady trickle of interviews arriving all the time) or on a cadence (a fresh batch each period). * **Reporting** runs on a cadence you choose — weekly, biweekly, monthly, or quarterly. Each reporting cycle is called a **wave**. You don't re-launch anything between waves. Interviews flow in, and when a wave's time window closes, Conveo automatically analyzes everything in that window and publishes the wave's results — new insights, updated metrics, and a written report — then starts the next wave. ## What's inside a Storyline The analysis cycles that make a Storyline continuous — what a wave is, its lifecycle, and how to pick a cadence. How findings are generated each wave and threaded across waves, with a lifecycle status showing how each one is evolving. Track the numbers that matter and watch them trend wave over wave, alongside the qualitative story. Each wave also produces a written report and quote reels, and you can Talk to your data across the whole program. A Storyline also has an **Overview** — the at-a-glance home that surfaces the latest insights, the metrics you're tracking, and suggestions for what to look at next, so each time you open it you can immediately see what changed. ## How to read a Storyline 1. **Start on the Overview** to see what changed most recently and which findings are being surfaced now. 2. **Scan the lifecycle statuses** on the [Insights](/docs/storylines/insights) board. *Emerging* and *Escalating* findings are where something new is happening; *Ongoing* findings are your stable, dependable truths. 3. **Open an insight to read its thread** — each wave's version of the finding in order, so you can see when it started and how it developed, not just where it stands today. 4. **Track a metric** you care about on the [Dashboard](/docs/storylines/dashboard-and-metrics) so you can watch it move as new waves land, and let each wave's report tell you the story in words. ## Storyline vs. a one-shot study * A one-shot **study** is analyzed once, over a fixed batch of interviews. * A **Storyline** re-analyzes on a cadence and connects findings across waves, so it answers "how is this changing?" — not just "what did we find?".