Anticipate the crowd
​
Make the most of Affluences' predictive analysis algorithm for you..
We have developed a powerful algorithm that takes into account several indicators in order to make crowd forecasts that are as close as possible to reality. The purpose: to enable adjusting your organisation according to the expected crowd.
​
...and your visitors
By communicating the crowd forecasts with your visitors, you enable them to choose the best moment to come while taking into account the journey time to get on-site. As a result, you smoothen the flows of visitors and above all, you attract more visitors during off-peak hours while offering better visit conditions!
​
What data sources are used to predict peak attendance?
​
Affluences' predictive analytics algorithm, developed by our Data Science team, allows you to combine various data sources to best forecast what will happen at your venue.
Our powerful algorithm takes into account different indicators to provide attendance forecasts that are as close to reality as possible (weather, school calendars, events, historical data, etc.).
The goal: to enable you to adjust your organization based on the expected occupancy.​
FAQ
How does Affluences predict peak periods?
Affluences uses a hybrid combination of real-time data and Machine Learning algorithms to forecast attendance:
-
Sensor Data Collection: our counting systems report real-time data on what is happening at the site.
-
Historical Analysis: predictive models analyze past attendance cycles (seasonality, days of the week, off-peak hours).
-
Correlation of External Variables: Affluences' AI integrates exogenous factors impacting visitor behavior, such as weather forecasts, school holiday calendars, local cultural events, etc.
-
Algorithmic Processing: Data is processed by regression algorithms and neural networks that compare the facility's current state with historical models to project attendance for the coming hours and days.