# Trend Decomposition

### Overview

Trend Decomposition is a deep-dive discovery tool inside TickerTrends that breaks a broad keyword, company, category, or trend into the specific underlying terms driving discussion share over time. Rather than only seeing that a topic is growing, users can identify *what products, brands, creators, memes, or related terms are causing the move*.

For example:

* Searching **Nike** may reveal popular shoes, athlete collaborations, apparel lines, or campaigns.
* Searching **FoodTok** may reveal trending restaurant chains, menu items, recipes, or creators.
* Searching **Prebiotic Soda** may reveal brands such as Olipop, Poppi, Bloom Nutrition, or viral flavors.

Trend Decomposition is ideal for identifying market share shifts, viral products, competitive momentum, and emerging consumer behavior before it becomes obvious.

### Where to Find Trend Decomposition

1. Search any company or keyword in TickerTrends.
2. Navigate to the **Social Summary** section.
3. Click the **Decomposition** icon in the top-right corner.
4. A new Trend Decomposition popup window will open.

<figure><img src="/files/um5NFYXvUFfpGgT1hsSR" alt=""><figcaption></figcaption></figure>

<figure><img src="/files/Wfpgwwt8R0uNYIQms0CM" alt=""><figcaption></figcaption></figure>

### Historical Length

Varies by source and platform. Most supported datasets include multi-year history where available.

### Granularity

Trend Decomposition primarily uses monthly visual grouping with underlying daily / weekly source data depending on the platform selected.

This allows users to analyze:

* Short-term spikes
* Seasonal patterns
* Recurring trends
* Long-term market share shifts

### Update Frequency

Most supported social sources refresh daily or near daily depending on platform availability.

## How to Use Trend Decomposition

### Main Search Bar

At the top of the popup is the main search bar.

This allows users to enter any keyword or category.

Examples:

* Nike
* FoodTok
* Running shoes
* Prebiotic soda
* Protein snacks
* Energy drinks

After entering a term, click **Run Search**.

This will generate a new decomposition based on that keyword.

<figure><img src="/files/8aIhNRs4rqeRLJlv2Cjk" alt=""><figcaption></figcaption></figure>

### Partial Match vs Exact Match

Located beside the search bar.

#### Partial Match

Returns broader related terms that may include variations, adjacent phrases, or loosely connected mentions.

Example for **prebiotic soda**:

* healthy soda
* soda brands
* gut health drink
* poppi review

Best for discovery and wider exploration.

<figure><img src="/files/jczIrdIJzKf65olG6f7P" alt=""><figcaption></figcaption></figure>

#### Exact Match

Returns only terms directly associated with the exact keyword phrase.

Example:

* prebiotic soda brands
* prebiotic soda taste
* best prebiotic soda

Best for cleaner and more precise analysis.

<figure><img src="/files/CW156KibHpebmLL9kfWJ" alt=""><figcaption></figcaption></figure>

### Sites Filter

Located in the top-right of the widget.

Users can choose which platforms to include in the search.

Examples may include:

* X / Twitter
* TikTok
* Instagram
* Reddit
* LinkedIn
* YouTube
* Facebook

<figure><img src="/files/yD3QiN0qErQPs1RhXfCq" alt=""><figcaption></figcaption></figure>

#### Example

If **TikTok + Instagram + X** are selected, the source label may display:

* tt = TikTok
* ig = Instagram
* x = X / Twitter

This source label appears next to the keyword in the Jobs/Search row.

Use site filters to compare where a trend is strongest.

Example:

* TikTok may show viral consumer products
* Reddit may show detailed product opinions
* LinkedIn may show professional software discussion

## Viral Timeline

### What It Shows

The Viral Timeline is the core feature of Trend Decomposition.

It displays top related terms underneath each monthly timestamp.

Terms are ranked from most influential to least influential based on share of discussion.

Each box represents a trending contributor for that time period.

### Color Coding

Every term is color coded consistently throughout the timeline.

This makes it easy to track recurring winners over time.

Example:

If **Pineapple Paradise** is yellow in one month, it remains yellow in future appearances within that same timeline.

<figure><img src="/files/clnfbBvFNI1KvXVbzEIl" alt=""><figcaption></figcaption></figure>

### Viral Timeline Percentage Filters

Located above timeline:

* 0.5%
* 1%
* 1.5%
* 2%

These percentages represent minimum discussion share thresholds relative to the base keyword.

#### Lower Threshold (0.5%)

Shows more terms including smaller niche contributors.

#### Higher Threshold (2%)

Shows only the strongest and most influential terms.

Use lower thresholds for discovery and higher thresholds for cleaner summaries.

## Word Filters

Located near the top.

Users can filter by:

* **All Terms**
* **1 Word**
* **2+ Words**
* **Cashtag ($)**

#### Examples

#### Nike

Use **1 Word** to see:

* Jordan
* Dunks
* Kobe

Use **2+ Words** to see:

* Air Jordan
* Dunk Low
* Running Shoes

#### Cashtag

Useful for public tickers or finance-related discussions:

* $NKE
* $AAPL
* $TSLA

## Hover and Click Functionality

Hover over or click any term in the timeline.

This opens a pop-up chart showing:

* Share of voice over time
* Peak month
* Trend rise / decline
* Historical momentum

This helps identify exactly when a product or brand began accelerating.

<figure><img src="/files/7If6qyPBcID9ZgQqPtmI" alt=""><figcaption></figcaption></figure>

## Ranked Results Table

Below the timeline is a sortable table of terms.

Common columns include:

* Term
* Absolute Share
* Share Increase
* Trend Chart

Use this table for precision ranking rather than visual timeline review.

## Compare Terms Feature

Users can compare two or more selected terms.

### How to Use

1. Select terms in the results table.
2. Click the purple **Compare** button.
3. Open the comparison chart.

### What It Shows

* Shared axis comparison
* Separate axis comparison
* Multiple time periods
* Relative momentum shifts

#### Example Comparisons

* Olipop vs Poppi
* Nike Dunk vs Adidas Samba
* Wingstop vs Chick-fil-A
* NVIDIA vs AMD

<figure><img src="/files/l5initxVOK1sVJoib84k" alt=""><figcaption></figcaption></figure>

Users can now also request for specific Dashboards to have Trend Decompositions added directly onto the interface vs going through the social summary

<figure><img src="/files/WJiwhGDL69JxH62PTw77" alt=""><figcaption></figcaption></figure>

By clicking on any combination of the suggested terms you see, then clicking the purple compare button in the top right you will receive a comparison chart exactly the same as the one mentioned above.&#x20;

<figure><img src="/files/ycKSh5tbF8MOXrNo0rPc" alt=""><figcaption></figcaption></figure>

## Recent Posts / Underlying Discussions

Inside Compare Mode or detailed charts, users can view actual posts contributing to trend movement.

This allows users to understand:

* Why a spike happened
* Which creator caused momentum
* Whether sentiment is positive or negative
* Which products are being discussed most often

#### Example

If Bloom Nutrition spikes, recent posts may show users reviewing a new flavor or viral launch.

<figure><img src="/files/PewhECHtg7RUCT7m7nng" alt=""><figcaption></figcaption></figure>

## Example Use Cases

### Nike

Search Nike to identify:

* Most discussed shoes
* Athlete endorsements
* Product launches
* Fashion cycles
* Competitor overlap

### FoodTok

Search FoodTok to identify:

* Trending restaurant chains
* Viral menu items
* Fast-growing food creators
* Seasonal menu buzz

### AI Tools

Search AI tools to identify:

* ChatGPT
* Claude
* Midjourney
* Coding copilots
* New entrants gaining share

### Prebiotic Soda

Search prebiotic soda to track:

* Olipop
* Poppi
* Bloom Nutrition
* Flavor launches
* Health positioning terms

## Best Practices

Use **Exact Match** for cleaner investment research.\
Use **Partial Match** for discovery.\
Use lower thresholds for niche trends.\
Use higher thresholds for major drivers only.\
Use Compare Mode for market share battles.\
Use Recent Posts to validate narrative shifts.

## Methodology

Trend Decomposition starts with a parent keyword and scans selected sources for related terms appearing in discussion around that keyword. TickerTrends then measures share of discussion, growth, recurrence, and persistence over time.

Values are directional and relative. They are designed to surface consumer attention shifts, competitive momentum, and emerging trends rather than represent financial disclosures or reported revenue.

## Use Cases

Track products driving brand momentum.\
Identify rising challengers within categories.\
Separate temporary hype from sustained growth.\
Monitor social market share shifts.\
Discover trends before mainstream coverage.\
Support public and private market research.


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