# 4. Features & Workflows **Overview**\ TickerTrends is designed to give investors a complete view of both alternative data signals and financial context for any ticker. When a user searches a ticker in the main search bar, the workflow moves through a structured series of modules inside the KPI Dashboard, with additional tools like Exploding Trends, Unstructured Data, and Sector Trends available for deeper analysis. TickerTrends supports both quarterly and semi-annual reporting structures, ensuring consistent forecasting coverage across public and private markets. **KPI Dashboard** * **Data Overview**: High-level overview of what consumers are discussing across social platforms, with key topics automatically extracted.
* **Research Notes:** allow users to open full company-specific research reports directly within the platform. Documents are displayed in an embedded viewer, enabling seamless review of qualitative analysis alongside KPI performance and forecast data without navigating away.
* **KPI Predictions**: Forward-looking KPI forecasts with revisions, showing actual, predicted, and range bands.
* **Data Source KPIs**: Manually curated alternative data signals (search trends, app usage, web traffic, TikTok views, etc.) selected for relevance to that ticker. This Fdata is also easy to view in a weekly year-over-year format to help investors easily understand how alternative data values are trends versus last year.
* **Related Symbols**: Peer and competitor tickers surfaced for comparison.
* **Transcripts**: Last six quarters of earnings transcripts with AI-generated conference call summaries.
* **Earnings Whisper Score**: Sentiment-driven score highlighting how investor expectations are shaping up into earnings.
* **Events**: Timeline of all past alerts triggered for that ticker, including large social shifts and meaningful YoY changes.
**Exploding Trends**\ Exploding Trends highlights relevant keywords linked to a ticker that are breaking seasonal norms. These are flagged as outliers, giving investors early visibility into sudden shifts in consumer behavior, product launches, or cultural moments.
Exploding Trends also has a standalone page where users can scroll through hundreds / thousands of pages of trends for idea discovery, for each and every data type. We can for non-seasonal abnormal trends for you as well as summarize the companies that appear most frequently right on top.
**Unstructured Data**\ The Unstructured Data tab lets users view raw time series data for any dataset type covered in Section 2. Each chart includes the option to automatically calculate historical Pearson r correlations between the data and KPI or Consumer Interest Trackers. This helps determine whether a keyword, app usage trend, or social signal has historically tracked company performance.
All data sources listed in the beginning of the documentation are available to view raw terms for.
You have the option to view your unstructured data via chart or table through the "Show Table" button in the top right of the page.
The user will also notice that when they select a type, our similarity matching system automatically find related terms to the selected data source. If a user finds that something is missing, the "Add" button lets them seemlessly add a new value.
**Visualization Tools**
TickerTrends offers a set of visualization options to help investors analyze alternative data and KPI forecasts in flexible, meaningful ways. These tools allow users to view data from different perspectives, highlight patterns, and combine series for deeper insight. **YOY**\ Displays a year-over-year comparison that highlights annual growth patterns for the selected dataset.
**Stacked YOY**\ Compares individual years of data in a stacked format, making it easier to spot seasonality and year-specific trends.
**Volumetric**\ Plots volumized data on one axis for each type, helping visualize scale differences across metrics.
**Average**\ Normalizes and averages all selected data series into a single line to capture the overall trend.
**Aggregate**\ Aggregates (sums up) multiple data series into a combined view, giving a consolidated picture of activity.
**Outlier Cutoff (Beta)**\ A slider tool that lets users filter data based on outlier strength. Values range from 0 (no filtering) to 1 (aggressive filtering), allowing users to smooth charts or isolate extreme movements. This attempts to smooth out event related massive spikes or drops.
**Social Context Timeline**\ Automatically detects abnormal spikes or drops in data and overlays the related social or news events happening at that time. Helps users quickly connect data movements with real-world drivers like product launches, viral moments, or company news.
**Interval Mode**\ Allows users to set the timeframe for viewing data. It sums up all selected values within the chosen interval (weekly, monthly, quarterly, or fiscal quarter) and displays them in a bar graph format, making it easier to spot seasonality and long-term trends.
**Unified Search**\ A single search bar on top that connects across all datasets, forecasts, and trackers. Users can type in a ticker or term and immediately see all relevant KPIs, data sources, exploding trends, transcripts, and related symbols in one workflow. **Enterprise Dashboard (Data Mosaic)**\ A customizable workspace where users can build dashboards for specific tickers or sectors. Any data type in the platform can be added and displayed side by side, allowing analysts to track everything relevant in one view. This saves hours otherwise spent switching between datasets and platforms. Whether you want to monitor KPIs, web traffic, search trends, TikTok activity, or sector-wide themes, the Enterprise Dashboard keeps it all organized and updated in real time.
**Create Widget** The Create Widget feature allows users to add customizable data modules to the Enterprise Dashboard. When creating a widget, users select the desired widget type and configure the relevant company, data source, or metric. Available widget types include: * **Trend Chart** – Visualize search trends and alternative data signals over time * **Financial Chart** – Display financial data and market performance trends * **Metric Tracker** – Monitor key business metrics and operational signals * **KPI Forecast** – Track projected performance indicators over time * **Data Import** – Integrate external data via CSV upload or API endpoints Widgets enable users to build a personalized dashboard that surfaces the most relevant signals, forecasts, and performance indicators aligned with their monitoring workflow.
**Forecast Revisions (Hover View)** Users can hover over forecasted quarters in the Unified Search KPI Dashboard to view revision history, including the number of updates, initial forecast, and latest value. This enables transparent tracking of forecast changes over time directly within the chart view.
**Back Button** we have installed a universal back button to allow users to easily go back and forth between pages, and trackers within the interface. Located in the top left corner on the screen.
**Sector Trends**\ Sector-level aggregation allows users to move beyond a single ticker and view broader industry patterns. This helps identify which subsectors are accelerating or losing momentum.
**Ticker Screener**\ The screener enables cross-ticker comparisons using both forecasts and consumer interest trackers. Users can rank and filter companies by growth signals, KPI forecast revisions, or outlier alerts.
**Social Context**\ Social context overlays events, news, and consumer activity directly on KPI and data charts, making it easy to tie trends back to real-world catalysts.
**Activity Feed**\ The Activity Feed acts as a central hub for key developments across all tickers. It helps users cut through noise and focus on actionable events by surfacing three main types of content: **Activity and Moves**: provides a real-time feed of changes across forecasts, KPI trackers, research coverage, and underlying alternative data signals. The page is designed to help users quickly identify meaningful updates that may impact company performance or investor expectations. The dashboard aggregates multiple types of platform activity into a single view so users can monitor forecast revisions, track shifts in consumer behavior data, review newly published research, and observe raw data signals from supported sources.
* **Forecast Revisions**: displays updates to TickerTrends financial forecasts. Each entry highlights changes to previously published forecasts and shows how the updated forecast compares to Wall Street consensus estimates. Each revision includes: * **Ticker and metric** being updated (for example, Total Revenue) * **Revision magnitude**, showing the change in the internal forecast * **VS Street**, indicating the difference between the TickerTrends forecast and analyst consensus * **Updated growth range or estimate** * **Timestamp** indicating when the revision occurred This section allows users to quickly identify when forecasts are raised or lowered and whether the updated outlook is above or below market expectations.
* **Metric Trackers:** highlights alerts generated from tracked key performance indicators (KPIs) derived from alternative data sources. These alerts signal notable changes in consumer behavior metrics such as: * Search interest * Social engagement * Platform usage * App activity * Brand attention signals Each alert includes: * The **company ticker** * The **specific KPI being tracked** * The **direction and magnitude of the change** * The **date of the signal** These signals help users detect potential changes in company momentum before they appear in financial results.
**Research Notes:** provide deeper analysis of data signals, forecast changes, and company performance trends. Each entry includes: * The **company ticker** * The **title of the research report** * A link to **open the full report** * The **publication date** Research notes provide deeper analysis of data signals, forecast changes, and company performance trends.
* **Data Source:** section aggregates raw signals from the underlying alternative datasets tracked by the platform. These signals highlight changes detected across various data feeds that contribute to forecasts and KPI alerts. Supported sources may include: * Google Trends * Instagram followers * TikTok followers * YouTube search * Subreddit subscriber activity * iOS app data * Android usage data This section helps users observe changes in the underlying datasets that feed into the platform’s analytics and forecasting models. **Upcoming Earnings:** provides a calendar-style view of companies scheduled to report earnings over the next 14 days. The page highlights expected performance based on TickerTrends forecasts compared to Wall Street consensus estimates.
**Past Forecast Revisions:** section evaluates the historical accuracy of TickerTrends forecasts compared to Wall Street consensus estimates. This panel allows users to review how previous forecasts performed once actual company results were reported.
### Buy-Side Bogeys & Market Expectations The **Market Expectations** module surfaces buy-side bogeys alongside consensus estimates to help investors understand what the market is implicitly pricing in ahead of earnings. #### Buy-Side Bogeys Buy-side bogeys represent **internal market expectation benchmarks** derived from alternative data signals, historical earnings reactions, and KPI forecasting models. Rather than reflecting a company’s reported guidance, these values estimate what investors likely expect a company to deliver for key metrics. Each row includes: * **Metric** – The KPI being tracked (e.g., MAU, Revenue, Operating Margin). * **Consensus** – The current sell-side analyst consensus estimate. * **Bogey** – The implied buy-side expectation derived from TickerTrends models. * **Δ (Delta)** – The percentage difference between the bogey and consensus estimate. * **Confidence** – Model confidence level based on signal strength and historical forecast accuracy. Negative deltas suggest the **buy-side expectation is below consensus**, indicating potential downside risk if consensus estimates are too optimistic. Positive deltas suggest the opposite.
**Earnings History** The **Earnings History table** provides historical context for how the stock reacted to previous earnings events. Columns include: * **Quarter** – Earnings release date * **P/S** – Price-to-Sales multiple at the time of earnings * **vs SPY (bps)** – Relative performance versus the S\&P 500 after earnings * **Day Reaction** – Stock move on the earnings day * **EPS Beat/Miss** – Percent difference between reported EPS and consensus This table helps users identify patterns between **valuation levels, earnings beats/misses, and market reactions**, which can inform positioning ahead of future earnings events. **Trend Alerts**\ Our system automatically flags large social shifts or unusual YoY movements in consumer data, triggering alerts. These appear in the Events module of the KPI Dashboard and can also be configured as email notifications. Users can also check or uncheck any box to filter for their own preference on which data sources they want to be shown. These alerts are designed to help investors collect an actionable set of tickers they want to further analyze.
The "**Alerts**" section will allow users to input all the tickers they care about and get emailed when a new alert surfaces. Additionally, they can also use the Unstructured Data section to add individual data source alerts.
**Watchlist**
Users will notice the purple star next to tickers on the table as well as searched tickers. By staring a ticker, they are automatically adding it to their active watchlist. This enables more filter features in the "Quick Filters" section. #### KPI Table Fields **Ticker**\ The stock ticker symbol and company name tied to the KPI forecast. **KPI**\ The specific metric being forecast (e.g., Subscription Revenue, Daily Active Users, GMV). **Prediction** \ Our current forecast value for the KPI, expressed in the relevant unit (millions, billions, etc.). **Prediction vs. Consensus**\ Our current forecast value difference versus the Visible Alpha consensus, showing the deviation in percentage terms. **Forecast Revision** \ The latest revision (typically over the last week) in TickerTrends published forecast for the specific KPI. **Consensus Revision** \ The latest revision over the last week from analysts for the first forward unreported quarter, measured by Visible Alpha consensus for the specific KPI. **Prediction YoY**\ The one-year percentage change of our KPI prediction versus the actual value from the same quarter last year. **Prediction QoQ**\ The one-quarter percentage change of our KPI prediction versus the actual value from the prior quarter. **Revision**\ The change in our forecast since the last update, shown as an increase or decrease. Predictions are revised weekly as new data comes in. Once a revision is made, it is solidified and stored in the record. **YoY Acceleration**\ The difference between the predicted YoY growth rate for the current quarter and the actual YoY growth rate reported in the same quarter last year.\ \&#xNAN;*Example: If UBER Monthly Active Customers rose 11.3% YoY in Q2 last year and we forecast 13.7% YoY growth in Q2 this year, YoY Acceleration = +2.4%.* **QoQ Acceleration**\ The difference between the predicted QoQ growth rate for the current quarter and the actual QoQ growth rate reported in the same quarter last year.\ \&#xNAN;*Example: If UBER Monthly Active Customers rose 1.4% QoQ in Q2 last year and we forecast 1.1% QoQ growth in Q2 this year, QoQ Acceleration = -0.3%.* **Avg MOE (Margin of Error)**\ The average forecast error based on historical backtesting. This provides transparency into how accurate predictions have been over time. **Confidence Level**\ A rating of how strong the alternative data signals are for forecasting this KPI. Categories include: * **Low**: Weak alignment between alt-data and reported results. * **Medium**: Moderate alignment, reasonable forecast strength. * **High**: Strong alignment, high forecast reliability. * **In-Progress**: Model and data pipeline still being developed for that KPI. **Last Updated**\ The date of the most recent forecast revision. Most KPIs are updated weekly, with higher-frequency updates for popular tickers.