The ability to identify market shifts and predict shifts in economic sentiment is not clear-cut - the standard way is to rely on known indicators, general market reports, and even search trends.
What if there was a way to combine all these in one platform, identify your specific market indicators, and rank the most relevant indicators you should pay attention to?
In your existing process, your team might be utilizing the same indicators that you’ve used to determine last year’s sales prognosis.
What if you could integrate your internal sales data, and identify and incorporate new leading indicators that can help you test and verify your hypotheses, and boost forecast accuracy by doing so?
Time is a valuable asset when the goal is to extract insights that inform sound decisions. Decisions that move the needle for your organization.
Why spend that time on data wrangling (everything from cleaning, matching, modeling, and visualization) when you can do all that in just one click?
Backed by the latest statistical models that have been rigorously trained, back-tested, and produce statistically robust results.
Get the insights you need without the heavy lifting.
Combining your internal data & external indicators is one of the best ways to ensure an accurate forecast.
Indicio automatically processes your imported data, testing for seasonality, missing values, and outliers.
If any of these are detected, you can choose to adjust the data as you see necessary.
Select and input the variables you think will be most relevant for forecasting your primary data point. Up to 50+ leading indicators are analyzed simultaneously.
These variables are then ranked by explanatory power and relevance.
No guesswork necessary.
Leveraging on econometric and machine models generated by Indicio, you can quickly determine the best models to use on your data.
Through multivariate analyzes, Indicio automatically tests advanced models like VAR, VECM, including penalized models.
Aggregating these models, Indicio provides a performance weighting that is automatically adjusted over time.
This helps you determine the best model to use at any given moment, resulting in higher accuracy.
In these rapidly changing times, it's key to be able to make sense of how your business will react to specific events. By adding spikes, level shifts, and exponential decay effects to certain periods, you can generate a conditional forecast.
One that you can compare with your baseline model.
Within this platform that combines the latest statistical AI, and machine-learning models, you can expect to detect trend shifts at least 1-2 months earlier.
With a 40-60% forecast accuracy improvement to boot.
Whether your goal is to increase market share or safeguard against volatility,
the road to making decisions confidently lies in generating accurate forecasts you can trust.