---
description: >-
  Actionable stock KPI Predictions - predict stock earnings momentum before it
  happen
---

# KPI Predictions - Flagship

The Enterprise KPI Predictions Dashboard is TickerTrends' most advanced tool for institutional investors looking to forecast real-world company performance using alternative data. Designed for hedge funds, equity analysts, and quants, this dashboard delivers point-in-time predictions of Key Performance Indicators (KPIs) such as Daily Active Users (DAUs), Monthly Active Platform Consumers, revenue, orders, subscribers, and bookings.

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Unlike traditional analyst estimates, which rely on company guidance or lagging fundamentals, TickerTrends uses forward-looking signals across thousands of tickers, combining search trends, mobile app usage, website traffic, and social sentiment into a proprietary forecasting model. These KPI forecasts are updated weekly and timestamped for full transparency and auditability.

#### Why Use TickerTrends KPI Forecasts?

* Access **institutional-grade KPI predictions** with high accuracy and backtested performance.
* View **real-time consumer demand signals** before earnings calls.&#x20;
* See the **margin of error vs. historical KPIs** to evaluate predictive edge.
* Track **revision history** and confidence intervals for every prediction.
* Use forecasts for alpha-generating strategies or portfolio risk management.

The KPI Dashboard supports filters by sector, geography, and metric type. It allows users to quickly surface outlier activity, compare forecasted vs actuals, and automate research workflows.

This is the definitive product for anyone asking:\
&#xNAN;**"What will this company report next quarter based on consumer behavior happening right now?"**

Explore our live forecasts and KPI accuracy case studies at [tickertrends.io/kpi-tracker](https://tickertrends.io/kpi-tracker)!

The TickerTrends KPI Dashboard is your central hub for tracking the real-time performance of public companies using alternative data and KPI-driven metrics. Designed for investors, analysts, and researchers, the dashboard highlights curated tickers and "conclusions" of our vast corpus of alternative data in a singular data prediction. Analysts can use this resource to see what TickerTrends proprietary models are forecasting for the most important KPI reported by large public companies.&#x20;

The dashboard shows a clean interface for analysts to track their favorite tickers on a daily and weekly basis, giving users an actionable edge in their earnings. Each ticker is clickable to get a far more detailed view. Let's select **$UBER** as an example.&#x20;

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Uber reports "**Monthly Active Customers**" as a key indicator. We use our alternative data to prediction what the next reported earnings for this KPI will likely be!&#x20;

&#x20;Let's dig into each component.

* **Stock Details**: Gives more information about ticker metadata.&#x20;

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* **KPI Prediction**: The red dots show what TickerTrends is forecasting the next quarters KPI to be for the chosen company. Notice how there are red dots even on previous quarters. These are historical forecasts for this KPI that TickerTrends has made based on alternative data. This gives users an extremely detailed view into how reliable our forecasts have been in the past! All expanded views have the raw table values shown on the bottom in heatmap format. The options on the top right side allow users to export raw data values, zoom in, zoom out, and view the raw data daily values in a table form.&#x20;
  * Notice how we also see YoY and QoQ changes for last quarter ("Most Recent Reported"), last year same quarter number, our actual next quarter current forecast, and revisions (indicating how many times this quarter the current quarter prediction was revised).&#x20;

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The expanded view gives even more granularity into our prediction, as well as seasonal bands which represent a confidence interval. In the Time Series view, we see what our exact forecast was versus the actual result Uber reported.&#x20;

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Notice the "**Low**" and "**High**" sub fields in our Forecast. This represents the prediction range expected based on our model within a specified confidence interval.

Hovering over these values will show users exactly what TickerTrends expects based on our collective alternative data about the company.&#x20;

<figure><img src="https://3154453413-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Ft5RjqjXylbZA9Pzar20p%2Fuploads%2FPhytZpvlzmqfCLxMGT5M%2Fimage.png?alt=media&#x26;token=3755d8cf-9975-42eb-8659-ab12f866a590" alt=""><figcaption></figcaption></figure>

Hovering over the chart dots itself will show users the exact prediction value and range of likely outcomes as well.

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* **Revisions**: Analysts will be a revisions section. Each week, we re-run our KPI prediction models to incorporate the latest batch of alternative data values we collect in various data sources. These new values are taken into account and predictions change from week-to-week.&#x20;

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Users can select from any quarter and see our full revision history throughout the quarter. This gives a level of transparency and sense of direction shifts before a companies earnings. For example, consistent downward revisions could indicate severe slowing and even increase the likelihood the true reported number is even worse. In other words, in terms of these revisions, both the rate and magnitude of change matters!&#x20;

<figure><img src="https://3154453413-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Ft5RjqjXylbZA9Pzar20p%2Fuploads%2FtffoUkE1GsmVR6i5ACru%2Fimage.png?alt=media&#x26;token=6f122b73-7756-477e-ba71-bcd6184f4142" alt=""><figcaption></figcaption></figure>

Clicking the "Show Range" button on top puts the full confidence interval range on the chart view, giving a range of outcomes shedding light on how confident the model is in our prediction.&#x20;

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Remember that these predictions are only designed to predict the final result that a company reports at its respective quarter end for the KPI's reported on the earnings report date.&#x20;

* **Data Source KPIs**: Auto generated KPIs show analysts more individual data source granularity. Some common fields you will see are "**Google Search Trend**", "**Android US Usage Trend**", "**Web Traffic Trends**", etc. On the Analyze Page, users can analyze each of these data types in much more detail with specific keywords. However, on the KPI page, this combines the most relevant keywords within that specific data type to a business' financial performance all into one singular time series value which is displayed to users by data type. Each bar represent **YoY weekly change** in this amalgamation of keywords within data sources. This simply gives users more granularity into some components going into our final predicted KPI value. It also indicates which data sources are corroborating a large beat or miss in the KPI predicted.&#x20;

<figure><img src="https://3154453413-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Ft5RjqjXylbZA9Pzar20p%2Fuploads%2FZajiZdbaImRDOU2NzDJj%2Fimage.png?alt=media&#x26;token=e62a6c64-8550-4048-a584-e9a18d831997" alt=""><figcaption></figcaption></figure>

* **Social Discussion Trends**: Social Discussion trends summarizes the most relevant info social media users are talking about related to a ticker's product, service, or general sector. These quick summaries can shed tons of insights on feedback and sentiment the product, service or sector is getting online among today's consumers, summarizing today's chatter at a quick glance.&#x20;

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* **Earnings Transcript Insights**: Gives auto-generated summaries of the last 6 most recent earnings calls. This can save analysts tons of research hours manually going through transcripts.&#x20;

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Scrolling to the bottom, we see the "**View Full Transcript**" option&#x20;

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This button takes users to the advanced Transcript page where users can read through the full earnings transcript or search for specific keywords, view sentiment, and much more!&#x20;

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For example, all mentions of "waymo" can be found and each snippet can be marked and skipped to.&#x20;

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**Key Table Features**:

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**Filter by Sectors**&#x20;

Users can filter for specific sectors or tickers they care about and weed out other unrelated stocks.&#x20;

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In this example, we selected a few sectors ("Fintech" and "Technology") and notice the event timeline filter and lessen the displayed results. If users select the "Watchlist Only" they can only limit their ticker view to companies they have added to their watchlist upon initializing their account. This helps busy analysts cut down the noise in their data analysis and focus on sectors/tickers they truly care about.&#x20;

**Event Timeline**

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The Event Timeline is a real-time feed of the most important KPI revisions, TickerTrends Research published articles, as well as Data Source KPI large movement alerts. This gives users an actionable, digestible view of what the data is saying about sectors and tickers they care about. Every week, we post updated KPI predictions based on how the alternative data changed. The image above shows an example view. For "**Revisions**" some tickers with at least a low change in revisions stand out and the changes marked with:&#x20;

* **Ticker Symbol**
* "**Low**", "**Medium**", "**High**" impact based on the **YoY % delta** in the recent weekly revisions.&#x20;
* **Before and After % YoY** changes in the metric we are predicting&#x20;

Additionally on our Substack: [https://blog.tickertrends.io/](https://blog.tickertrends.io/) we post articles on select trends we are seeing that might be market moving such as large revisions or inflection points in businesses.&#x20;

**Discover Table**\
A sortable, searchable table that lets you explore companies by we have KPI data for. Sorting this table can shed valuable light on what tickers are most interesting to focus on.&#x20;

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You can track key metrics like:

* **Ticker**
* **KPI**
* **Prediction**
* **Prediction YoY**: One-year percentage change of our KPI prediction vs last year's respective quarter
* **Prediction QoQ**:  One-quarter percentage change of our KPI prediction vs last quarter's respective actual
* **Revision Increase**: Revision change, up or down from our last prediction. Predictions are updated and revised with incoming data weekly throughout the quarter. Once, we make a revision, it is solidified and set in stone.&#x20;
* **YoY Acceleration**: Represents the predicted quarter's YoY % change and compares to the previous year's same respective quarter's actual YoY % change reported. For example, if UBER Monthly Active Customers rose **11.3% YoY** in **Q2 last year**, and we forecast it to grow **13.7% YoY in Q2 this year**, **YoY Acceleration would = 2.4%**.
* **QoQ Acceleration**: Represents the predicted quarter's QoQ % change and compares to the previous year's same respective quarter's actual QoQ % change reported. For example, if UBER Monthly Active Customers rose **1.4% QoQ** in **Q2 last year**, and we forecast it to grow **1.1% QoQ in Q2 this year**, **QoQ Acceleration would = -0.3%**.
* **Avg MOE (Margin of Error)**:&#x20;
* **Confidence Level**: There are 4 categories users will notice: "**Low**", "**Medium**", "**High**", and "**In-Progress**". The first 3 represent how much we believe our alternative data to be a good forecaster of specific company metrics. Our data strength lies in digital trends, so naturally some companies will be harder to track and predict from our data coverage. "In-Progress" essentially means that we are still working on the model and keyword curation / processing for that particular ticker.&#x20;
* **Last Updated**: Informs users when the last data revision happened. We attempt to update every KPI at least once a week but plan for more frequent revisions in specific popular tickers.&#x20;



**Prediction/Tracking Tag**\
Tickers tagged with "**Prediction**" are companies for which TickerTrends tracks structured operational metrics from public filings for. These include metrics like users, volume, bookings, subscribers, and more, matched with real-time web and social indicators.

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The tickers tagged with "**Tracking**" are companies where although we don't predict a specific exact reported metric the company releases, we track an aggregate of data where users can see an acceleration or deceleration in a specific brand a company owns. For example, users can track UGG sales for **$DECK** and although we don't issue a $ amount forecast for the next quarter, we show what an aggregate of alternative data sources indicate about that shoe brand and its rate of change.&#x20;

<figure><img src="https://3154453413-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Ft5RjqjXylbZA9Pzar20p%2Fuploads%2FjMreT70paxjMV3GKziAX%2Fimage.png?alt=media&#x26;token=683cdc34-be9c-4f4c-84ea-d8e01a7be749" alt=""><figcaption></figcaption></figure>

The KPI Dashboard is a valuable tool for identifying early-stage momentum, validating investment ideas, and tracking theme-based trends across sectors. You can filter by country, sector, or time frame, and dig deeper into any name that stands out. TickerTrends is currently tracking over 100 tickers and metrics.&#x20;

Explore it live inside the TickerTrends platform or contact us at **admin@tickertrends.io** to learn how to use the KPI Dashboard as part of your workflow.



