# Audience Analytics Program

> experiment was conducted to evaluate attendance rates of smaller exhibitions based on tracking via Wifi data. This was done on the occasion of the "Degas: At the Track, on the Stage" show

**Wikidata**: [Q123156506](https://www.wikidata.org/wiki/Q123156506)  
**Source**: https://4ort.xyz/entity/audience-analytics-program

## Summary
The Audience Analytics Program was a museum AI project and forecasting model active from 2015 to 2016 at the Art Institute of Chicago. It functioned as a data enrichment experiment designed to evaluate attendance rates for smaller exhibitions by tracking visitor movement via WiFi data, specifically during the "Degas: At the Track, on the Stage" show.

## Key Facts
- **Timeline:** The program started in 2015 and ended in 2016.
- **Organization:** It was part of the Art Institute of Chicago.
- **Classification:** The entity is an instance of a museum AI project, a data enrichment process, and a forecasting model.
- **Methodology:** The program utilized WiFi data tracking and data mining to capture visitor metrics.
- **Case Study:** The primary experiment was conducted on the occasion of the "Degas: At the Track, on the Stage" exhibition.
- **Objective:** The goal was to evaluate attendance rates specifically for smaller exhibitions.
- **Technology:** The system employed artificial intelligence and data enrichment techniques to supplement missing or incomplete information.
- **Documentation:** The program is described in a Chicago Business article published on May 18, 2018.

## FAQs
### Q: What was the primary purpose of the Audience Analytics Program?
A: The program aimed to evaluate attendance rates for smaller exhibitions at the Art Institute of Chicago by supplementing incomplete data with WiFi tracking metrics.

### Q: How did the program utilize WiFi data?
A: It used WiFi data to track visitor locations and behaviors, allowing the museum to measure engagement in smaller exhibitions where traditional counting methods might be less effective.

### Q: Which specific exhibition was associated with this program?
A: The program's experiment was conducted during the "Degas: At the Track, on the Stage" show at the Art Institute of Chicago.

### Q: How is this program classified in the context of museum technology?
A: It is classified as a museum AI project and a forecasting model, falling under the broader discipline of data enrichment.

## Why It Matters
The Audience Analytics Program represents a significant step in the application of data science and artificial intelligence within the cultural sector. By leveraging data enrichment—the process of enhancing existing information by supplementing missing data—the Art Institute of Chicago moved beyond simple headcounts to gain a deeper, more granular understanding of visitor behavior in smaller exhibitions. This program demonstrated how museums could use network data (WiFi) and AI to optimize exhibition planning and improve the visitor experience, serving as a practical example of how data enrichment supports decision-making in non-profit institutions.

## Notable For
- Serving as an early application of AI and data mining for attendance forecasting in a major museum.
- Utilizing WiFi tracking to generate data for smaller exhibitions, a metric often harder to capture than main gallery attendance.
- Being a distinct instance of "data enrichment" applied to physical visitor movement.
- Operating as a specific experiment tied to the "Degas: At the Track, on the Stage" exhibition.

## Body
### Context and Classification
The Audience Analytics Program was a specialized initiative categorized as a museum AI project, a forecasting model, and an instance of data enrichment. It operated within the Art Institute of Chicago, maintained in the context of WikiProject Museum AI projects (MAp). The program's core function was defined by the principles of data enrichment: enhancing existing information by supplementing missing or incomplete data to improve data quality and usability.

### Methodology and Technology
The program utilized a combination of artificial intelligence and data mining to process information. The primary technological method involved tracking attendance via WiFi data. This approach allowed the museum to gather metrics on visitor density and flow without requiring physical tickets or manual counters for the specific areas under observation.

### Case Study: Degas: At the Track, on the Stage
The program's capabilities were put to the test during the "Degas: At the Track, on the Stage" exhibition. During this period, the system conducted an experiment to evaluate attendance rates. The focus on "smaller exhibitions" highlights the program's utility in providing visibility into niche or less-trafficked areas of the museum, ensuring that data completeness was maintained across all visitor spaces.

### Historical Timeline
The program was active for a specific duration in the mid-2010s.
- **Start Time:** 2015
- **End Time:** 2016