3. KPI Tracker & Forecasting - Flagship

Overview TickerTrends provides forward-looking forecasts for company KPIs such as revenue, EPS-related metrics, daily active users, bookings, and other KPIs that move tickers. These forecasts are designed to give investors and analysts an early view into company performance by combining alternative data signals with market context variables.

Methodology Our methodology uses a unified time-series forecasting model. All relevant alternative datasets —search, downloads, web traffic, social activity, and more — are ingested together so the model can learn the joint relationships between these signals and the company’s reported KPIs. In addition to these alt-data inputs, the model also incorporates market context variables such as consensus financial estimates (EPS, revenue, etc.), treating them as one of the relationships that influence outcomes. The result is a single, forward-looking KPI forecast that reflects both consumer-driven data and the expectations embedded in the market.

Breadth of Coverage TickerTrends delivers KPI forecasts across a wide set of companies and sectors. Examples include Roblox Bookings, Shopify GMV, Meta Daily Active People (DAP), Microsoft Intelligent Cloud revenue, and Reddit DAUQ.

For the complete KPI coverage list with margin of error details, as well as all tickers with consumer interest trackers, please email [email protected].

We currently maintain more than 100 unique KPI forecasts with new ones added each quarter, and over 600 individual tickers tracked through our consumer interest models. Coverage is rapidly expanding, giving users access to one of the most comprehensive KPI forecasting and consumer trend datasets available. Raw data for 10,000's of global tickers is also available on our platform, so there is no ticker limitation in terms of what's possible to analyze.

Forecast Revisions KPI forecasts are updated weekly as new consumer data tracked through our channels comes in. Each revision is stored as a separate prediction, so users can see the exact history of how forecasts have evolved. We never overwrite past predictions, which means users can audit the accuracy of past calls and review how revisions tracked against actual company-reported KPIs.

Error Measurement To ensure transparency, our forecasts include margin-of-error ranges based on historical backtesting. Users can see high, low, and central estimates at any given time.

Consumer Interest Trackers In addition to explicit KPI forecasts, we also provide aggregate Consumer Interest Trackers. These combine multiple alternative data inputs (Google Search, Mobile App Usage, Website Traffic, TikTok Hashtag Views, Reddit activity, Wikipedia page views, Amazon Search, etc.) into a single demand-side index. Consumer Interest Trackers default to weekly year-over-year comparisons, making it easy to spot shifts in momentum from week to week. When relevant, we also display the correlation between these consumer trackers and a company’s reported KPIs, providing added context on their predictive power, along with performance metrics such as Pearson r correlations between alternative data signals and reported KPIs. Additionally, many metrics we track are unreported but helpful in terms of what narrative might be driving a stock at a particular time. Examples include our Waymo tracker on $GOOG or Base44 for $WIX. Many other alternative data provides like Yipit or M Science often fully miss to incorporate these signals that TickerTrends captures.

Consumer Usage Trackers

Consumer usage trackers are very similar to consumer interest tracks however they tend to include more alternative data sources that focus on consumer website and mobile app usage as opposed to broader search interest.

Email Alerts Users can subscribe to receive email alerts whenever KPI forecast revisions are published. Alerts include the updated forecast, revision details, and a link to the dashboard for deeper exploration. This ensures that investors and analysts never miss meaningful shifts in company performance signals. Users simply have to setup their watchlist of tickers that they care about after signing up.

Use Cases

• Anticipate earnings results before they are reported by tracking KPI forecasts and revisions.

• Compare consumer interest momentum with financial KPIs to identify divergences or confirmations.

• Use historical prediction accuracy to build confidence in forward-looking signals.

• Receive alerts on KPI revisions to stay ahead of consensus estimate changes.