> AI agents: this is one page from PostHog's docs. Full index of Markdown docs for LLMs: https://posthog.com/llms.txt

# Trends and funnels – Product Analytics pocket guide

Canonical URL: https://posthog.com/learn/product-analytics/pocket-guide/trends-and-funnels

Chapter 03

# Trends and funnels – Product Analytics pocket guide

Edgar's event history and usage data on Twig so far shows what *he* did in the product. But Edgar is one person, and Twig's engineers want to know whether other visitors use filters and finish bookings too.

An [insight](https://posthog.com/docs/product-analytics/insights.md) turns events into an answer about product behavior. The engineers use two kinds of insights: a [trend](https://posthog.com/docs/product-analytics/insights.md) to see how use changes over time, and a [funnel](https://posthog.com/docs/product-analytics/funnels.md) to see how many people finish a sequence of steps.

## Track filter use with a trend

Twig's engineers' first question is: **Did more people use Twig's stay filters this week than last week?** Twig already records a `stay_filter_selected` event for every selection and PostHog connects each of those events to a person.

To answer their question, they create a **Trends** insight for `stay_filter_selected` events, and measure **Unique users**, grouping the results weekly. They compare two selected weeks:

Scroll sideways ↔

Week 2

**19**events

→

**8**people

Inspect an event →

Trends

stay\_filter\_selected

Unique users · weekly

58Week 1Week 2

Select “Inspect an event” to see one of Edgar’s selections behind the Week 2 count.

The trend shows 5 people in week 1 and 8 people in week 2. Those 8 people generated 19 events total, but users with multiple filter selections count as one unique user. Their answer? More people used filters in week 2.

Over time, Twig's engineers can watch this trend to understand if filters are a common way to find stays. If use keeps growing, they may prioritize improving the filter experience. If it falls, they can investigate what changed and decide what to prioritize instead.

## Measure booking completion with a funnel

Twig's ultimate goal is for users to book a stay. A count of `booking_completed` events would show completions, but not how many people started booking and never completed. A **Funnel** insight connects the dots between `booking_started` and `booking_completed`.

Twig records `booking_started` when it sends a booking request and `booking_completed` when the booking is confirmed. The engineers use these as the funnel's two steps. PostHog connects events from the same account and checks that completion follows the start.

The visual first follows Edgar's confirmed booking (`user_812`), which has both funnel steps. It then switches to a different visitor whose request fails, so their trail stops at `booking_started`. Watch both examples play, or select **Book stay** to switch between them yourself:

Reset

Scroll sideways ↔

TwigEdgar Hogg

![Dark A-frame cabin among autumn trees, with a gravel path leading to the entrance at dusk](https://posthog.com/static/cabin-52b343c8c87096a619df7bf1a904bcea.jpg)

### Adiron-shack

Adirondacks, New York

4 guests · 2 bedrooms · 2 baths

**$355** / night USD